Advertising and Promotions Managers

11-2011.00

Median wage $133,660/yr21,470 employed (US)Rank #164 of 923 scored · top 18% by substitution

Plan, direct, or coordinate advertising policies and programs or produce collateral materials, such as posters, contests, coupons, or giveaways, to create extra interest in the purchase of a product or service for a department, an entire organization, or on an account basis.

Sub-scores

0–100 · band = confidence interval from rater disagreement

Substitution40

Exposure34

Augmentation75

Substitution — the headline: capability discounted by cost, barriers and adoption.

Exposure — technical capability alone, regardless of whether anyone deploys it.

Augmentation — how much AI assists without replacing. High here + moderate substitution = a changing job, not a disappearing one.

Tasks on the substitution scale

30 rated tasks, binned by substitution score.

Position among all scored occupations

Distribution of 923 occupation scores; the marker is this occupation.

Tasks with substitution ≥ 70

Run 1.0.0-draft.1 · computed 2026-08-05 · rater panel: claude-sonnet-5, claude-haiku-4-5-20251001 · intervals span rater disagreement.

Why this score

The five weighted dimensions of the composite, averaged across this occupation's tasks (importance-weighted, panel mean). Exact weights and formulas: /api/v1/methodology.

Task automatabilityw 35%35

panel mean rating 2.4/5 → substitution pressure 35/100

Technical feasibility todayw 20%33

panel mean rating 2.3/5 → substitution pressure 33/100

Cost vs. human wagew 15%38

panel mean rating 2.5/5 → substitution pressure 38/100

Adoption barriersw 20%inverted — strong barriers lower the score54

panel mean rating 2.8/5 (barrier strength) → substitution pressure 54/100

Sector adoption velocityw 10%49

panel mean rating 2.9/5 → substitution pressure 49/100

Task breakdown (30 tasks)

Substitution pressure per task, weighted by O*NET importance in the composite. Expand a task for the full rater audit trail — every rating, every model, every rationale.

Track program budgets, expenses, and campaign response rates to evaluate each campaign, based on program objectives and industry norms.

CI 61–86 · exposure 62 · augmentation 100 · importance 3.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	5/5	Advertising and marketing sectors are information-intensive and highly digitalized with rapid adoption of analytics tools; BI platforms and marketing automation software are standard across mid-to-large agencies and corporate marketing teams.
Sector adoption velocity	claude-sonnet-5	4/5	Marketing and advertising are digitally mature sectors with widespread adoption of analytics and automated reporting tools, though full evaluative judgment remains human-led.
Augmentation potential	claude-haiku-4-5-20251001	5/5	AI dashboards and automated reports powerfully augment manager productivity by providing real-time budget visibility, anomaly alerts, and pre-computed comparisons to norms, freeing managers to focus on strategic decisions rather than manual data compilation.
Augmentation potential	claude-sonnet-5	5/5	AI-powered dashboards, predictive analytics, and automated reporting significantly enhance a manager's ability to monitor budgets and evaluate campaign performance in real time.
Task automatability	claude-haiku-4-5-20251001	4/5	Current AI systems can automatically extract, aggregate, and analyze campaign expense data, calculate KPIs against budgets, and compare results to industry benchmarks with minimal human input. The task requires data integration and numerical analysis, which are well-suited to automation, though human judgment on strategy interpretation remains useful.
Task automatability	claude-sonnet-5	3/5	AI can aggregate budget/expense data and calculate response rates and ROI metrics readily, but tying evaluation to nuanced program objectives and industry benchmarks still requires human judgment and contextual interpretation.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Few legal or regulatory barriers exist to automating budget and campaign tracking; it is primarily a data reporting function. Organizational friction may arise from preference for human review, but nothing prevents full substitution of the analytical work itself.
Adoption barriers	claude-sonnet-5	1/5	No licensing or regulatory requirement mandates human performance of budget tracking or campaign analytics; it's a purely internal business function.
Cost vs. human wage	claude-haiku-4-5-20251001	5/5	AI-driven analytics platforms cost a fraction of the annual loaded wage of a full-time advertising manager dedicated to budget tracking and analysis. Once deployed, marginal cost per campaign evaluation is negligible compared to manual review labor.
Cost vs. human wage	claude-sonnet-5	4/5	Automated dashboards and reporting tools are far cheaper than manual data compilation and analysis by a manager, though some human oversight and interpretation costs remain.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Mature BI and marketing analytics platforms (Tableau, Google Analytics, Salesforce, HubSpot) reliably track budgets, expenses, and campaign metrics in production environments. These tools automate budget tracking and response rate analysis at scale, though some custom configuration is often needed for specific objectives.
Technical feasibility today	claude-sonnet-5	3/5	Marketing analytics and BI platforms (e.g., HubSpot, Google Analytics, Tableau with AI features) already track spend and performance metrics in production, though holistic campaign evaluation against objectives is less automated and often manually curated.

Analyze the effectiveness of marketing tactics or channels.

CI 61–80 · exposure 62 · augmentation 100 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Marketing and advertising sectors have been early adopters of analytics automation and AI-driven dashboards; most medium-to-large enterprises now run continuous AI-powered marketing analytics in production.
Sector adoption velocity	claude-sonnet-5	4/5	Marketing and advertising is a fast-digitizing, data-rich sector where AI-powered analytics and attribution tools are already widely deployed in production across firms of many sizes.
Augmentation potential	claude-haiku-4-5-20251001	5/5	AI-powered marketing analytics dramatically augments human decision-making by providing real-time dashboards, automated anomaly detection, and predictive forecasting that managers use to refine strategy while remaining in control of campaign direction.
Augmentation potential	claude-sonnet-5	5/5	AI substantially enhances a manager's ability to analyze channel performance by automating data aggregation, pattern detection, and report generation, letting the human focus on strategic interpretation and decision-making.
Task automatability	claude-haiku-4-5-20251001	4/5	Current AI systems can automate the majority of analytics on marketing effectiveness—data ingestion, metric calculation, comparative analysis, and reporting—with significant time savings. However, contextual interpretation and strategic recommendations tied to business goals typically require human judgment, preventing a full 5 rating.
Task automatability	claude-sonnet-5	3/5	AI can process campaign data, generate performance summaries, and surface correlations across channels, but interpreting effectiveness in context of business strategy, brand goals, and competitive dynamics still requires human judgment and synthesis of qualitative factors AI can't fully capture.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Few regulatory or licensing barriers protect this task; marketing teams operate these tools internally with minimal compliance friction. Some organizational preference for human strategic interpretation remains, but technical adoption faces minimal friction.
Adoption barriers	claude-sonnet-5	1/5	No licensing, regulatory, or legal requirement mandates a human perform marketing effectiveness analysis; adoption is purely a matter of organizational choice and tooling.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	Automated analytics infrastructure costs orders of magnitude less per analysis than hiring analysts, though integration and oversight add modest overhead. The cost per insight strongly favors AI.
Cost vs. human wage	claude-sonnet-5	4/5	Automated dashboards and AI-driven analytics tools can process large data volumes at a fraction of the cost of manual analyst hours, though some human oversight and interpretation costs remain.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Mature analytics platforms (Google Analytics, Tableau, Mixpanel, marketing attribution tools) with embedded AI and ML routinely perform channel effectiveness analysis in production at scale. Minor gaps remain in cross-channel attribution and business-context reasoning.
Technical feasibility today	claude-sonnet-5	3/5	Marketing analytics platforms (e.g., Google Analytics, HubSpot, Adobe Analytics with AI features) reliably surface metrics and attribution insights in production, but full 'effectiveness analysis' combining strategic judgment and cross-channel nuance still requires human review and interpretation.

Monitor and analyze sales promotion results to determine cost effectiveness of promotion campaigns.

CI 57–81 · exposure 62 · augmentation 100 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	5/5	Marketing, retail, and e-commerce sectors have deeply and rapidly adopted AI-driven analytics platforms and dashboards to track promotion ROI; deployment is mainstream across enterprise and mid-market firms, not pilot-stage.
Sector adoption velocity	claude-sonnet-5	4/5	Marketing and advertising functions are among the fastest adopters of AI-driven analytics tools, with widespread use of automated dashboards and attribution modeling in production environments.
Augmentation potential	claude-haiku-4-5-20251001	5/5	AI dramatically amplifies manager productivity by instantly surfacing trends, anomalies, and comparisons across hundreds of campaigns that manual review would take weeks; managers stay in control of strategic decisions while AI handles computation and visualization.
Augmentation potential	claude-sonnet-5	5/5	AI substantially enhances this task by automating data aggregation, trend detection, and report generation, allowing managers to focus on strategic interpretation and decision-making with much higher throughput.
Task automatability	claude-haiku-4-5-20251001	4/5	Current AI systems can largely automate the data collection, aggregation, statistical analysis, and visualization of sales promotion results against predefined KPIs. However, nuanced interpretation of campaign context, competitor dynamics, or strategic recommendations may still benefit from human judgment, preventing a full 5-rating.
Task automatability	claude-sonnet-5	3/5	AI can process sales data, compute ROI metrics, and generate analysis reports quickly, but interpreting results in strategic context and deciding next steps still requires human judgment and business context integration.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Few legal or licensing barriers exist. Organizations may prefer human review of strategic conclusions, and some internal workflows may require sign-off, but the underlying analysis task itself faces minimal regulatory or authorization friction.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement blocks AI use here, but organizational trust in interpreting financial/marketing performance and accountability for budget decisions creates moderate friction against full delegation to AI.
Cost vs. human wage	claude-haiku-4-5-20251001	5/5	Automated analytics on promotion data cost pennies per analysis once infrastructure is in place, versus paying a manager's hourly wage ($50–150+) to manually gather, organize, and compute the same metrics; the cost advantage is at least 10–100x over time.
Cost vs. human wage	claude-sonnet-5	3/5	Analytics software and AI tools reduce time spent on data crunching significantly, but licensing costs, data integration, and oversight by skilled analysts keep costs roughly comparable to human-driven analysis at scale for many organizations.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Mature analytics and BI platforms (Tableau, Power BI, Google Analytics) with embedded AI and machine learning already perform cost-effectiveness analysis in production at scale across marketing departments. These systems reliably track promotion metrics, compare actual vs. projected ROI, and generate standard reports.
Technical feasibility today	claude-sonnet-5	3/5	BI and analytics tools (e.g., dashboards with AI-assisted insights, marketing attribution platforms) exist and are used in production, but full autonomous cost-effectiveness analysis with nuanced attribution across channels remains error-prone and requires human validation.

Read trade journals and professional literature to stay informed on trends, innovations, and changes that affect media planning.

CI 50–84 · exposure 55 · augmentation 88 · importance 3.3/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Marketing and advertising agencies increasingly use AI-powered competitive intelligence and trend-monitoring tools, but adoption is still patchy and often supplementary rather than fully replacing human reading and synthesis.
Sector adoption velocity	claude-sonnet-5	4/5	Marketing and advertising sectors have moved quickly to adopt AI tools for research, content curation, and trend monitoring, reflecting fast adoption typical of professional/information services.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI excels at high-volume literature triage, summarization, and categorization, significantly raising manager productivity by filtering and organizing content so they can focus on strategic interpretation and decision-making.
Augmentation potential	claude-sonnet-5	5/5	AI substantially enhances a manager's ability to track trends by summarizing large volumes of content, flagging relevant changes, and surfacing insights, while the human still applies judgment and context.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can retrieve and summarize trade journal content, the task requires discernment about which trends and innovations are strategically relevant to an organization's specific media planning context—a judgment that current AI struggles with consistently and without human curation.
Task automatability	claude-sonnet-5	4/5	AI can aggregate, summarize, and synthesize trade publications and news feeds efficiently, capturing most of the informational value with far less time than manual reading, though verifying nuance and applying judgment still requires human review.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Reading journals and staying informed is a self-directed, knowledge-work task with no regulatory or licensing requirement; adoption is primarily a matter of business judgment and comfort with automation quality.
Adoption barriers	claude-sonnet-5	1/5	There are no licensing, regulatory, or liability barriers to using AI for information-gathering and summarization tasks like this.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	AI-powered literature summarization and monitoring services (e.g., automated news digests, semantic search) cost far less than paying a manager to manually read and synthesize journals, though some human oversight is still needed.
Cost vs. human wage	claude-sonnet-5	5/5	AI-based summarization and monitoring tools cost a small fraction of the loaded time a manager would spend reading journals manually, offering large cost savings for equivalent informational output.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	AI tools can read and extract summaries from published literature, but no production system reliably filters noise, contextualizes relevance, or identifies non-obvious industry shifts without significant human review and direction.
Technical feasibility today	claude-sonnet-5	4/5	Deployed products (news aggregators, AI summarization tools, research assistants) reliably summarize industry content today, though curation of the most relevant trade-specific sources for niche media planning may need some manual configuration.

Prepare budgets and submit estimates for program costs as part of campaign plan development.

CI 55–72 · exposure 62 · augmentation 75 · importance 3.7/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Marketing and advertising firms have moderate AI adoption for analytics and planning, but budget automation is not yet standard practice. Pilot programs are emerging in larger agencies, but production deployment remains inconsistent.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising sectors show above-average AI tool adoption for content and planning, but structured financial estimating workflows lag creative use cases.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI excels at augmenting budget preparation by rapidly generating multiple scenarios, adjusting for past campaign performance, and stress-testing cost assumptions. Managers retain oversight while AI substantially accelerates exploration and validation of budget options.
Augmentation potential	claude-sonnet-5	4/5	AI tools meaningfully speed up drafting initial budgets, cost breakdowns, and scenario modeling, letting managers focus on judgment and stakeholder negotiation.
Task automatability	claude-haiku-4-5-20251001	4/5	Current AI can extract historical cost data, generate budget line items, and perform financial calculations with high accuracy. While some judgment about contingencies and strategic allocation remains, AI can automate 60–75% of the mechanical budgeting and estimation work, meeting the time-saving threshold.
Task automatability	claude-sonnet-5	3/5	AI can draft budget templates, pull historical cost data, and generate estimates, but requires human input on business context, negotiation constraints, and final judgment calls, limiting full end-to-end automation.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Budget submission typically requires managerial sign-off and organizational approval, but no licensing or legal requirement mandates a human prepare the underlying estimates. Organizational friction around trust in automated budgets exists but is declining.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement, but organizational approval processes and accountability for financial commitments create some friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	AI inference and integration costs for budget preparation are low relative to manager labor; a single API call can generate detailed estimates and cost breakdowns that would take a human hours. All-in cost favors automation by a significant margin.
Cost vs. human wage	claude-sonnet-5	3/5	AI can cut drafting time significantly, but oversight, data integration, and validation against vendor quotes still require paid human time, making the net cost saving moderate rather than order-of-magnitude.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Deployed tools (spreadsheet automation, business intelligence software with AI cost modeling, and finance-specific LLMs) reliably handle budget preparation and cost estimation. These products work at scale in organizations, though human review of final estimates is still standard practice.
Technical feasibility today	claude-sonnet-5	3/5	Spreadsheet AI tools and generative assistants (e.g., Copilot, ChatGPT with data) can produce budget drafts and cost estimates today, but they aren't yet reliably deployed as autonomous budget-preparation systems in agencies without heavy human review.

Contact organizations to explain services and facilities offered.

CI 38–87 · exposure 58 · augmentation 75 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Marketing, sales, and advertising sectors have rapidly adopted AI-powered outreach tools. Production deployments are common in mid-to-large organizations; SMBs are following quickly with lower-cost platforms.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising sectors are adopting AI tools moderately for CRM, lead generation, and communication drafting, though core outreach still relies on humans.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI draft prospecting messages, subject lines, and segmentation significantly boost human outreach productivity. Managers can refine AI-generated copy and focus on relationship strategy while AI handles volume and personalization.
Augmentation potential	claude-sonnet-5	4/5	AI can significantly help by drafting pitch materials, personalizing outreach messages, researching prospective organizations, and preparing talking points.
Task automatability	claude-haiku-4-5-20251001	5/5	Outbound email and message campaigns explaining services can be generated, personalized, and sent at scale by current AI systems (LLMs + automation tools). Human oversight exists but the 50% time-saving threshold is easily met in routine prospecting.
Task automatability	claude-sonnet-5	2/5	This involves relationship-building, persuasive live communication, and reading organizational needs, which current AI can support but not fully replace end-to-end at equal quality.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Minimal legal barriers; outreach is not licensed or heavily regulated. Some organizational resistance to perceived impersonal automation and email deliverability constraints exist, but no hard regulatory or liability blocks prevent substitution.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement, but organizational preference for human contact and trust-building in B2B sales creates moderate friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	5/5	AI-driven email and bulk outreach cost cents per message versus human labor (salary + overhead) at several minutes per contact. Automation is orders of magnitude cheaper for volume prospecting.
Cost vs. human wage	claude-sonnet-5	2/5	Human relationship managers remain necessary for credibility and nuanced negotiation, so AI augmentation reduces some prep time but doesn't yet replace the full labor cost.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Mature products (HubSpot, Mailchimp, sales automation platforms with AI copywriting) reliably execute templated outreach at scale. Minor gaps exist in handling nuanced objections or relationship-building, but core contact/explanation is production-ready.
Technical feasibility today	claude-sonnet-5	2/5	AI tools like chatbots and email drafting assistants exist but are not reliably deployed to autonomously conduct outreach calls or meetings explaining services to organizations.

Conduct research on consumer opinions and buying habits, and identify target audiences for products, services, or technologies.

CI 57–66 · exposure 55 · augmentation 100 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Marketing and advertising sectors have rapidly adopted AI-driven analytics, audience segmentation, and insights platforms; Fortune 500 marketing teams and agencies now routinely use these tools in production workflows. Adoption is deep in information/digital-native sectors and accelerating even in traditional marketing departments.
Sector adoption velocity	claude-sonnet-5	4/5	Marketing and advertising sectors have been fast adopters of AI analytics and consumer insight tools, with widespread production use of AI-driven market research and social listening platforms.
Augmentation potential	claude-haiku-4-5-20251001	5/5	AI significantly augments managers' productivity on this task by enabling rapid hypothesis testing, multi-source sentiment aggregation, real-time demographic drill-down, and pattern discovery that would take humans weeks to complete manually. Managers remain in the loop to validate insights and guide strategy, but their throughput and breadth of analysis improve dramatically.
Augmentation potential	claude-sonnet-5	5/5	AI substantially enhances this task by rapidly processing large volumes of consumer data, surveys, and social signals to surface patterns and segment audiences, greatly boosting manager productivity while they retain strategic judgment.
Task automatability	claude-haiku-4-5-20251001	3/5	AI can automate significant parts of this task—analyzing survey data, social media sentiment, demographic databases, and historical purchasing patterns—but typically requires human judgment to interpret findings, validate assumptions, and synthesize insights into actionable targeting strategies. The 50% time-saving threshold can be met on data analysis phases, but strategy formulation usually demands human oversight.
Task automatability	claude-sonnet-5	3/5	AI can synthesize existing survey data, analyze consumer sentiment, and generate audience segments quickly, but designing original research and validating findings still requires human oversight, so only part of the task meets the 50% bar.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Few regulatory or legal barriers prevent AI application to consumer research and audience identification; no licensing requirement mandates human sign-off. Primary friction is organizational (preference for human intuition, internal processes relying on established research workflows) and data access constraints, not legal prohibition.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement exists for this task, though organizations may prefer human judgment for strategic audience decisions, creating mild friction rather than hard barriers.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	AI-driven analytics platforms and data aggregation services cost substantially less than hiring research analysts or market research firms to conduct equivalent studies. Even with oversight and integration overhead, the per-task cost is typically 3–5× lower than human researcher labor for comparable output.
Cost vs. human wage	claude-sonnet-5	3/5	AI-powered analytics reduce time spent on data aggregation and pattern-finding, but licensing costs for enterprise research tools plus human oversight keep costs roughly comparable to traditional research staff for nuanced work.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Mature products (e.g., Brandwatch, Sprout Social, Qualtrics with AI analytics, predictive modeling platforms) reliably perform consumer sentiment analysis, demographic segmentation, and audience identification in production. Some error rates and interpretation nuances remain, but deployed systems demonstrably execute large portions of this task at scale.
Technical feasibility today	claude-sonnet-5	3/5	Tools like social listening platforms, survey analytics, and AI-driven market research products (e.g., Qualtrics AI, Sprinklr) are in production use, but they still have notable error rates and narrow scope requiring human interpretation.

Develop communications materials, advertisements, presentations, or public relations initiatives to promote awareness of products and services.

CI 61–61 · exposure 50 · augmentation 100 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Marketing and advertising are information-sector heavy hitters with strong digitization and rapid AI adoption. Agencies, e-commerce platforms, and in-house teams are actively deploying generative AI for copy and asset creation, with measurable displacement in contract creative roles.
Sector adoption velocity	claude-sonnet-5	4/5	Marketing and advertising is among the fastest-adopting sectors for generative AI, with widespread integration of AI copywriting and design tools into agency and in-house workflows.
Augmentation potential	claude-haiku-4-5-20251001	5/5	AI tools meaningfully augment human creatives by automating drafting, suggesting variations, and generating asset mockups, dramatically accelerating iteration cycles. Managers and creatives consistently report improved productivity when using generative AI as a collaborative partner.
Augmentation potential	claude-sonnet-5	5/5	AI substantially speeds up ideation, drafting, and iteration of marketing materials while managers retain control over strategy, brand voice, and final decisions.
Task automatability	claude-haiku-4-5-20251001	3/5	AI can generate draft copy, design concepts, and presentation outlines at scale, but strategy, brand voice alignment, and market positioning typically require human judgment. Roughly half the workflow—ideation, initial drafting, layout—can be accelerated, but creative direction and final approval remain human-dependent.
Task automatability	claude-sonnet-5	3/5	AI can draft copy, generate ad concepts, and produce presentation materials quickly, but final creative direction, brand strategy alignment, and stakeholder approval still require human judgment, capping full end-to-end automation.
Adoption barriers	claude-haiku-4-5-20251001	2/5	No legal licensing requirement, regulatory mandate, or liability barrier prevents AI use in this task. Organizations may prefer human creatives for brand-critical work, but nothing legally forbids substitution, and market adoption shows low friction.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement exists for advertising content creation, though brand risk, legal/compliance review for claims, and client approval processes create moderate organizational friction.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	AI-assisted generation of copy and graphics costs a fraction of hiring freelance copywriters or designers, especially for volume work. Oversight and iteration remain, but the raw production cost per asset is substantially lower than human labor.
Cost vs. human wage	claude-sonnet-5	4/5	Generating drafts of ad copy, presentations, and communications materials via AI tools costs a small fraction of a manager's or agency's billable time for the same volume of initial content.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	Deployed tools (ChatGPT, DALL-E, Canva, Adobe Firefly) produce usable ads and promotional materials, but output quality is inconsistent and often requires significant rework. Products exist in production but with material limitations on originality, message precision, and brand coherence.
Technical feasibility today	claude-sonnet-5	3/5	Products like generative AI copywriting tools, image/video generators, and presentation builders (e.g., Jasper, Copy.ai, Canva Magic Design) are used in production, but outputs typically need human editing for brand voice, accuracy, and strategic fit.

Analyze marketing or sales trends to forecast future conditions.

CI 57–61 · exposure 50 · augmentation 100 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Marketing and sales organizations are among the earliest adopters of AI analytics; most mid-to-large firms now use some form of AI-assisted forecasting and trend analysis in production, with widespread pilot programs beyond.
Sector adoption velocity	claude-sonnet-5	4/5	Marketing and advertising sectors have moved quickly to adopt AI analytics and forecasting tools as part of broader martech and data-driven decision-making trends.
Augmentation potential	claude-haiku-4-5-20251001	5/5	AI forecasting tools augment marketing managers significantly by processing large datasets, surfacing patterns, and enabling real-time dashboards while managers focus on strategic interpretation and action planning. This is a mature augmentation use case in the field.
Augmentation potential	claude-sonnet-5	5/5	AI substantially enhances a manager's ability to process large datasets, identify patterns, and generate forecast scenarios quickly, while the manager retains interpretive and strategic decision-making control.
Task automatability	claude-haiku-4-5-20251001	3/5	AI can ingest historical data and generate trend forecasts with statistical models, but interpreting context, identifying novel patterns, and translating forecasts into strategic decisions require human judgment. Current systems handle the data analysis portion but not the full decision-making loop reliably.
Task automatability	claude-sonnet-5	3/5	AI can analyze structured sales/marketing data and generate statistical forecasts, but interpreting trends in context of business strategy, competitive dynamics, and qualitative factors still requires human judgment.'
Adoption barriers	claude-haiku-4-5-20251001	2/5	Minimal legal or regulatory barriers; marketing teams are adopting these tools widely. Some organizational inertia and preference for in-house expertise exist, but nothing prevents AI deployment of trend analysis.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement, but organizational trust in AI-generated forecasts for strategic decisions, and accountability for inaccurate forecasts, creates moderate friction.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	Modern analytics and forecasting platforms have become cost-competitive with analyst time; subscription-based BI and ML tools are much cheaper than hiring skilled forecasters when amortized across organizations, though integration and oversight still add overhead.
Cost vs. human wage	claude-sonnet-5	3/5	AI-driven forecasting tools reduce analyst hours but require data infrastructure, integration, and ongoing oversight, making costs moderate rather than dramatically cheaper than skilled analyst time.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	BI tools and AI-powered analytics platforms exist and are deployed in marketing teams (e.g., Tableau, Looker with ML, industry-specific platforms), but they often require significant setup and human validation. Forecasts frequently need expert review due to changing market conditions and data quality issues.
Technical feasibility today	claude-sonnet-5	3/5	Analytics and forecasting products (e.g., demand forecasting tools, BI platforms with predictive AI) exist and are used in production, but accuracy varies and outputs typically need managerial validation before use in planning.

Devise or evaluate methods and procedures for collecting data, such as surveys, opinion polls, and questionnaires.

CI 55–61 · exposure 50 · augmentation 75 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Marketing and advertising sectors are digitally mature and actively adopting AI tools for data collection optimization, survey design automation, and analytics; many firms already use AI-driven platforms for these functions.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising sectors are moderately fast adopters of AI tools for content and data tasks, though survey methodology design specifically sees more measured, pilot-stage adoption.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI assists managers by rapidly generating multiple survey designs, identifying bias in questionnaires, and automating data collection logistics, meaningfully accelerating the evaluation and iteration cycle while the manager retains strategic oversight.
Augmentation potential	claude-sonnet-5	4/5	AI substantially speeds up drafting survey questions, structuring questionnaires, and suggesting data collection approaches, meaningfully boosting a manager's productivity while they retain oversight.
Task automatability	claude-haiku-4-5-20251001	3/5	AI can generate survey designs, questionnaire templates, and sampling strategies efficiently, saving time on method design. However, the evaluation of existing methods requires domain judgment about validity and alignment with business goals, which typically needs human oversight, placing this at roughly half-automatable.
Task automatability	claude-sonnet-5	3/5	AI can draft survey instruments, suggest sampling methodologies, and generate questionnaire items quickly, but designing valid methodologies still requires human judgment about business context and target audience nuances., especially for evaluation of existing methods.
Adoption barriers	claude-haiku-4-5-20251001	2/5	While there are some organizational and professional norms around survey design rigor, no hard regulatory or licensing barriers prevent AI-assisted method development; adoption mainly faces user preference and organizational inertia.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement, though organizational preference for experienced human judgment in survey design and stakeholder buy-in creates moderate friction.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	AI-powered survey and data collection tools are significantly cheaper than hiring research methodologists or running manual survey design workshops, with minimal per-task inference cost once platforms are in place.
Cost vs. human wage	claude-sonnet-5	3/5	AI tools can cheaply generate draft surveys and analyze structures, but methodology evaluation still requires human oversight, keeping costs roughly comparable to a skilled analyst's time for a full deliverable.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	Products exist (survey platforms with AI-assisted question generation, analytics tools) and are deployed in practice, but they operate within narrow scopes and still require material human review for methodological rigor and context-specific appropriateness.
Technical feasibility today	claude-sonnet-5	3/5	Products like survey platforms with AI-assisted question generation and analytics tools exist and are used, but full end-to-end methodology design and evaluation still commonly involves human market research expertise.

Provide presentation and product demonstration support during the introduction of new products and services to field staff and customers.

CI 38–70 · exposure 45 · augmentation 75 · importance 3.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Marketing and sales organizations are rapidly adopting AI-powered presentation tools, automated video creation, and interactive product demos in production environments. These are information-sector jobs with high digitization, and adoption data shows meaningful displacement of manual presentation labor.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising functions have moderately fast AI adoption for content creation and sales enablement tools, though live demo/support roles lag behind pure content tasks.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI significantly assists managers by auto-generating presentation slides, creating product demo videos, personalizing content for different audiences, and handling routine Q&A, allowing the manager to focus on high-value relationship-building and strategic messaging with key stakeholders.
Augmentation potential	claude-sonnet-5	4/5	AI significantly aids managers by generating slide decks, talking points, FAQs, and product summaries, and can power interactive demo tools, substantially boosting preparation efficiency even though a human still delivers the live support.
Task automatability	claude-haiku-4-5-20251001	4/5	AI can automate most components of presentation delivery and product demonstrations through automated slide generation, video synthesis, and interactive product explainers, achieving significant time savings. However, live audience engagement and real-time Q&A handling with nuance may still benefit from human oversight, preventing a perfect 5.
Task automatability	claude-sonnet-5	2/5	This task involves live, interpersonal presentation and demonstration support requiring real-time adaptation, relationship management, and physical/product handling that current AI cannot fully replicate end-to-end. Only content-generation portions (slides, scripts) are automatable.
Adoption barriers	claude-haiku-4-5-20251001	2/5	There are minimal legal or licensing barriers to automating presentation delivery and product demonstrations. Organizational friction around customer preference for human interaction exists but is weak; companies routinely substitute webinars and automated demos for in-person briefings.
Adoption barriers	claude-sonnet-5	2/5	No licensing is required, but organizational preference for human presenters, customer relationship expectations, and the need for real-time judgment during live demos create moderate friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	AI-generated presentations, video demos, and interactive content tools cost substantially less per deployment than hiring managers to deliver live presentations repeatedly across multiple locations and audiences. Over many product launches, the cost differential is likely 5-10x in AI's favor.
Cost vs. human wage	claude-sonnet-5	2/5	While AI can cheaply draft supporting materials, the core live-demonstration and support function still requires a human presence, so overall cost savings versus a manager's wage are modest.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	Products exist for presentation automation, video generation, and interactive demos, but they typically require human curation, real-time monitoring, and customization for different audiences. Reliable end-to-end unattended operation at scale remains limited, with material gaps in handling diverse customer contexts.
Technical feasibility today	claude-sonnet-5	2/5	AI tools can generate presentation materials and talking points, but no deployed product autonomously delivers live product demonstrations or handles the interactive support role with field staff and customers.

Prepare and negotiate advertising and sales contracts.

CI 32–70 · exposure 50 · augmentation 88 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Contract automation and AI review tools have achieved significant adoption in finance, tech, and large enterprises; legal operations and procurement teams are actively deploying these systems in production. Mid-market and smaller firms lag, but adoption is accelerating.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising sectors are moderately fast adopters of AI tools for drafting and analytics, but contract negotiation specifically remains largely human-led with limited production deployment.
Augmentation potential	claude-haiku-4-5-20251001	5/5	AI substantially augments human managers by auto-generating contract drafts, highlighting key terms, comparing against templates, and flagging unusual clauses, freeing managers to focus on negotiation strategy and relationship management rather than document mechanics.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist by drafting contract templates, summarizing terms, benchmarking rates, and suggesting negotiation points, significantly speeding up preparation while the manager retains control of the actual negotiation.
Task automatability	claude-haiku-4-5-20251001	4/5	AI can now draft, review, and flag key contract terms with high accuracy using language models and document analysis, saving substantial time. However, final negotiation and strategic decision-making on high-stakes deals typically still require human judgment, though AI handles 60–80% of the mechanical work.
Task automatability	claude-sonnet-5	2/5	AI can draft contract language and flag terms, but genuine negotiation involves relationship management, strategic trade-offs, and judgment calls that current systems cannot autonomously execute end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	3/5	While no licensing requirement prevents AI use for contract prep, many organizations retain human lawyers for final review and signing due to liability concerns, professional norms, and client expectations. Regulatory and insurance frameworks often still expect human legal review, creating organizational friction.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement mandates a human, but liability for contract terms, client relationship expectations, and organizational sign-off processes create moderate friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	AI contract tools cost far less per document than hiring specialized contract lawyers or spending manager hours on initial drafting and review, typically 10–50× cheaper than human-equivalent effort for routine or moderately complex agreements.
Cost vs. human wage	claude-sonnet-5	2/5	AI can cheaply generate draft contracts, but the negotiation portion still requires paid human time, oversight, and relationship-based back-and-forth, keeping overall cost savings modest.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Mature contract drafting and review tools (e.g., specialized legal AI platforms) are deployed in corporate legal and procurement teams, with demonstrated reliability in flagging risks and generating first drafts. Deployed systems handle routine contracts reliably, though complex negotiations still involve humans.
Technical feasibility today	claude-sonnet-5	2/5	Contract drafting tools and CLM software exist and are used in production, but AI-led negotiation of advertising/sales terms is not a deployed, reliable capability—humans still drive the actual negotiation.

Inspect layouts and advertising copy, and edit scripts, audio, video, and other promotional material for adherence to specifications.

CI 44–55 · exposure 50 · augmentation 75 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Advertising and marketing sectors show moderate digitization but conservative automation of creative judgment. Pilots of automated QA tools exist, but production replacement of manager review remains rare; human creatives and managers retain gatekeeping roles in most organizations.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising are moderately fast adopters of AI tools for content review and generation, with many pilots and growing production use, though full manager-level oversight tasks lag behind simpler copy-editing use cases.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI excels at flagging technical errors, generating compliance checklists, and highlighting deviations from specs, allowing managers to focus on strategic and creative judgment rather than tedious format inspection. This materially raises manager productivity while keeping human decision-making central to approval.
Augmentation potential	claude-sonnet-5	4/5	AI substantially speeds up initial review passes—catching spec violations, inconsistencies, and errors in copy, audio transcripts, and video metadata—while the manager retains final approval authority.
Task automatability	claude-haiku-4-5-20251001	3/5	AI can assist with format checking, spell-checking, and flagging deviations from templates or brand guidelines automatically, but subjective quality judgment on creative content and context-specific adherence still requires human oversight. Roughly half of the inspection workflow (technical specs, copy errors) can be automated; the creative and strategic approval remains human-dependent.
Task automatability	claude-sonnet-5	3/5	AI can review copy and layouts for spec adherence and flag issues quickly, but final judgment on brand fit, tone, and creative quality still requires human review, limiting full end-to-end automation.
Adoption barriers	claude-haiku-4-5-20251001	3/5	Industry norms strongly favor human creative review and sign-off for brand and legal compliance; marketing managers are expected to take accountability for output quality. While no hard licensing barrier exists, organizational practice, liability concerns, and client expectations create meaningful friction against full automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement exists for this task, though organizational approval processes and brand/legal liability create some friction before AI-only sign-off would be accepted.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI tools for inspection (video analysis, text flagging, metadata extraction) cost hundreds to thousands monthly, while a manager's loaded wage is substantial. For small batches, AI overhead is significant; only at very high volume does cost per-task favor AI, and even then human review remains necessary.
Cost vs. human wage	claude-sonnet-5	3/5	AI tools for text/image checking are cheap, but comprehensive review across scripts, audio, video, and layouts requires integration and human oversight that narrows the cost advantage compared to a single manager doing holistic review.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	Production tools exist for automated QA on video/audio metadata, closed-caption accuracy, and basic copy compliance, but they struggle with nuanced brand voice, strategic messaging fit, and subjective creative judgment. Deployed systems work reliably on narrow, rule-based checks but have material error rates on holistic creative evaluation.
Technical feasibility today	claude-sonnet-5	3/5	Tools like Grammarly, Adobe AI features, and content review platforms exist and are used in production, but multi-modal review (audio/video/layout together) against nuanced specifications still has notable error rates and gaps.

Formulate plans to extend business with established accounts and to transact business as agent for advertising accounts.

CI 32–62 · exposure 45 · augmentation 75 · importance 3.7/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Ad agencies and marketing firms (information/services sectors) are piloting AI account analysis and recommendation tools, but full autonomous transacting on accounts remains rare in production. Adoption is picking up in larger organizations but slower in relationship-driven agencies where client preference for human contact remains strong; overall middling adoption with pockets of early deployment.
Sector adoption velocity	claude-sonnet-5	3/5	Advertising and marketing sectors are adopting AI tools quickly for content and analytics, but account management and client relationship functions still see mostly pilot-level AI assistance rather than deep production use.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI excels at augmenting account managers: rapid account health scoring, opportunity identification via data mining, draft proposal generation, and competitive benchmarking all enhance human decision-making and planning efficiency. A manager using such tools can process more accounts and spend more time on relationship building rather than analysis, creating significant productivity gains while the human retains strategic control.
Augmentation potential	claude-sonnet-5	4/5	AI tools can meaningfully assist by drafting proposals, analyzing account data, generating insights, and preparing pitch materials, boosting the manager's efficiency while they retain relationship ownership.
Task automatability	claude-haiku-4-5-20251001	4/5	Current AI systems can competently draft business development plans, analyze account data, identify growth opportunities, and propose transaction structures. The task involves significant pattern recognition and synthesis work (leveraging historical account data, market trends, competitor analysis) that AI handles well; however, the final strategic approval and relationship finalization typically still require human judgment, limiting the full end-to-end automation to high but not complete savings.
Task automatability	claude-sonnet-5	2/5	This task requires relationship management, negotiation, and strategic judgment about client accounts that current AI cannot execute end-to-end; AI can support research and drafting but not the core relational/strategic work.
Adoption barriers	claude-haiku-4-5-20251001	3/5	Client relationships and account authority expectations create moderate friction: many established accounts expect personal relationship continuity and human decision-making from their account manager. Some industries/regulatory contexts (financial services accounts, high-liability contracts) may require licensed human review. Organizational culture and client-facing norms slow substitution, but no hard legal mandate prevents an AI-assisted or AI-first approach.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement, but strong organizational and client-relationship friction exists since clients expect a human account manager they trust, and errors in account handling carry real business/liability costs.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	AI-driven plan generation and account analysis cost substantially less than paying a manager's full loaded wage to research and draft plans iteratively. Integration and oversight costs are modest relative to the time saved on data gathering, scenario modeling, and initial drafting, though the ratio is not quite order-of-magnitude due to human review overhead.
Cost vs. human wage	claude-sonnet-5	2/5	Because AI cannot perform the relational and negotiation core of the task, human labor remains necessary, so cost savings are limited to peripheral research/admin support rather than full task replacement.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	AI products (generative AI, business intelligence dashboards, and CRM agents) can produce draft plans and analyses, but few organizations have deployed fully autonomous agents that reliably transact on established accounts without human oversight. Deployed systems typically require human review of recommendations and final approval before account action, reflecting material gaps in production reliability.
Technical feasibility today	claude-sonnet-5	2/5	No deployed product autonomously manages account relationships or negotiates advertising deals; existing CRM/AI tools only assist with data organization and communication drafting.

Plan and prepare advertising and promotional material to increase sales of products or services, working with customers, company officials, sales departments, and advertising agencies.

CI 25–57 · exposure 38 · augmentation 88 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	While marketing departments piloting AI copy-generation are common, widespread production adoption of AI for strategic campaign planning remains limited. Most organizations use AI for assistive tasks (drafting, ideation) rather than autonomous planning.
Sector adoption velocity	claude-sonnet-5	4/5	Marketing and advertising is among the fastest-adopting sectors for generative AI, with widespread pilot-to-production use of AI content tools in agencies and marketing departments.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI significantly augments managers through rapid draft generation, market trend analysis, demographic targeting insights, and A/B testing support. Humans retain strategy and stakeholder management while AI accelerates content iteration and data synthesis.
Augmentation potential	claude-sonnet-5	5/5	AI substantially boosts productivity in ideation, drafting, and asset production for campaigns while managers retain control over strategy, client relationships, and final decisions.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can generate draft copy, design concepts, and analyze market data, the task fundamentally requires strategic planning tied to customer relationships, company objectives, and cross-functional coordination that demand human judgment. Current AI lacks the contextual understanding to independently plan multi-stakeholder campaigns end-to-end.
Task automatability	claude-sonnet-5	3/5	AI can draft copy, generate creative concepts, and produce campaign materials quickly, but coordinating with customers, sales departments, and agencies plus strategic decision-making still requires substantial human involvement.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Significant barriers exist: brand liability for messaging accuracy, regulatory compliance for promotional claims, client approval workflows, and strong preference for human strategic judgment and relationship management. Organizations rarely delegate final campaign planning to automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing or regulatory requirement mandates human execution, though client relationships and brand accountability create some preference for human oversight and sign-off.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI-generated content requires substantial human oversight, revision, and strategic direction; the all-in cost of oversight and iteration often exceeds the marginal savings from draft generation, keeping costs near parity with human-performed work.
Cost vs. human wage	claude-sonnet-5	3/5	AI tools significantly reduce time spent on drafting and ideation at low cost, but the coordination, negotiation, and oversight portions still require paid managerial time, keeping overall cost comparable rather than dramatically lower.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	AI tools can assist with copywriting and layout suggestions, but deployed products do not reliably handle the full scope of planning, stakeholder management, and strategic positioning required. No production system performs this task end-to-end with acceptable error rates.
Technical feasibility today	claude-sonnet-5	3/5	Generative AI tools (Jasper, Copy.ai, Adobe Firefly) are deployed in production for content drafting and asset creation, but full campaign planning integrating stakeholder input remains largely human-led.

Maintain portfolios of marketing campaigns, strategies, and other marketing products or ideas.

CI 32–38 · exposure 25 · augmentation 75 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Marketing and advertising sectors show moderate AI adoption in data analysis and customer insights, but strategic portfolio maintenance remains predominantly human-led; pilots of AI-assisted tools exist but production-scale displacement is limited.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising sectors are moderately fast adopters of AI tools for content and campaign management, though portfolio curation specifically remains a human-led task.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI can meaningfully assist by auto-categorizing campaigns, surfacing patterns in past performance, suggesting organizational frameworks, and flagging underperforming ideas—allowing managers to focus on strategic evaluation and creative refinement rather than manual curation.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist by organizing, summarizing, and retrieving campaign materials, freeing up manager time for strategic decisions.
Task automatability	claude-haiku-4-5-20251001	2/5	Current AI can assist in organizing and retrieving campaign information, but maintaining a strategic portfolio requires judgment about which campaigns succeed, why, and how to evolve them—tasks that demand human interpretation of nuanced market feedback and strategic intent that AI systems cannot yet perform reliably end-to-end.
Task automatability	claude-sonnet-5	2/5	Maintaining and organizing a portfolio involves curation, judgment about strategic fit, and stakeholder communication that current AI cannot fully replicate end-to-end, though it can assist with organizing and summarizing content.
Adoption barriers	claude-haiku-4-5-20251001	3/5	While there are no hard legal barriers preventing AI-assisted portfolio management, organizational inertia, reliance on tacit managerial judgment, and stakeholder preference for human strategic curation create moderate friction to full automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement, but organizational trust in strategic judgment and internal review processes create moderate friction for full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Integration of AI systems into portfolio management workflows, combined with necessary human oversight to validate strategic decisions, yields costs comparable to or potentially exceeding the wage of a manager performing the work, especially when accounting for error correction and judgment calls.
Cost vs. human wage	claude-sonnet-5	2/5	Human managers still need to curate, evaluate strategic relevance, and update portfolios, so AI tools mainly reduce some administrative time rather than replacing the core cost.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While document management and basic categorization tools exist, no mature product today reliably maintains a strategic portfolio by evaluating campaign performance, refining strategies, and curating ideas with the contextual judgment a manager applies; most solutions are generic content databases lacking strategic reasoning.
Technical feasibility today	claude-sonnet-5	2/5	Some content management and marketing asset tools use AI for tagging and search, but no deployed product autonomously maintains a full campaign portfolio reliably at scale.

Coordinate with the media to disseminate advertising.

CI 32–38 · exposure 25 · augmentation 75 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Larger advertising agencies and tech-enabled marketing departments are adopting programmatic tools and AI-assisted planning, but many mid-market and smaller agencies still rely on manual media coordination; adoption is increasing but uneven across the sector.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising sectors have moderate AI adoption, particularly in programmatic buying and campaign analytics, but the coordination and relationship aspects lag behind pure digital tasks.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI can meaningfully assist by analyzing media performance data, recommending optimal channels and timing, drafting outreach templates, and tracking delivery metrics—allowing managers to focus on relationship-building and strategic decisions while the system handles data synthesis and routine scheduling.
Augmentation potential	claude-sonnet-5	4/5	AI tools significantly assist with media planning, audience targeting, campaign performance analysis, and drafting communications, improving efficiency while managers retain relationship and decision-making roles.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can draft communications and suggest media channels, the task requires negotiating rates, managing relationships, ensuring brand consistency, and handling exceptions—activities that benefit from human judgment and ongoing relationship management that current systems cannot fully automate end-to-end.
Task automatability	claude-sonnet-5	2/5	Coordinating with media outlets involves relationship management, negotiation, and judgment calls about placement strategy that current AI cannot fully replicate, though scheduling and communication drafting can be assisted.'
Adoption barriers	claude-haiku-4-5-20251001	3/5	While not legally restricted, media partnerships often require trust, signed agreements, and accountability that organizations prefer to maintain through human points of contact, creating moderate friction to full automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement, but this task relies heavily on personal relationships, trust, and negotiation with media partners, creating organizational and interpersonal friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Media coordination involves contract negotiation, relationship stewardship, and exception handling that currently require human oversight; the all-in cost of AI tools plus necessary human supervision approaches or exceeds the cost of a junior coordinator performing the task.
Cost vs. human wage	claude-sonnet-5	2/5	While programmatic ad platforms reduce costs for digital placement, the relationship-based coordination with media outlets and negotiation still requires human oversight, keeping all-in costs comparable to human labor.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Some products exist for media planning and scheduling (e.g., programmatic ad platforms), but coordinating with media partners typically requires human negotiation, contract oversight, and relationship management that deployed systems do not reliably perform independently at scale.
Technical feasibility today	claude-sonnet-5	2/5	Some tools exist for automated media buying and programmatic ad placement, but human-to-human coordination with media contacts, negotiating rates and placements, remains largely manual in production settings.

Identify and develop contacts for promotional campaigns and industry programs that meet identified buyer targets, such as dealers, distributors, or consumers.

CI 32–38 · exposure 25 · augmentation 75 · importance 3.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Mid-market marketing and advertising firms are piloting AI-powered lead identification and segmentation tools, but widespread production adoption of end-to-end contact development remains limited; most use AI as a research aid rather than for autonomous relationship development.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and sales functions are moderately fast adopters of AI for lead generation and CRM enrichment, though partner relationship development remains largely human-led.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI substantially augments this task by automating prospect research, identifying lookalike segments, scoring lead quality, and organizing contact databases, allowing managers to focus time on relationship-building and strategic targeting decisions rather than manual list compilation.
Augmentation potential	claude-sonnet-5	4/5	AI can significantly assist by researching potential distributor/dealer contacts, analyzing market data, and drafting outreach materials, boosting manager productivity substantially.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist in identifying and segmenting potential contacts through data analysis and pattern recognition, developing meaningful relationships and tailoring outreach to specific buyer targets requires strategic judgment, negotiation, and industry understanding that remains largely human-dependent. The task involves nuanced contact cultivation that AI cannot execute end-to-end at the quality level expected in professional promotion.
Task automatability	claude-sonnet-5	2/5	Identifying and cultivating business contacts and partnerships requires relationship-building, negotiation, and judgment that current AI cannot autonomously execute end-to-end, though it can assist with research and lead lists.
Adoption barriers	claude-haiku-4-5-20251001	3/5	Modest friction exists: organizations prefer human judgment in selecting distribution partners and industry contacts to protect brand relationships and ensure strategic fit. However, no legal or licensing barrier prevents AI-assisted or semi-automated contact identification and outreach.
Adoption barriers	claude-sonnet-5	2/5	No strict licensing requirement, but business relationships often depend on trust, industry reputation, and personal rapport that create organizational friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Current AI-assisted contact identification and segmentation tools carry integration, data licensing, and human oversight costs that approach or exceed the cost of a junior marketer performing preliminary contact research, especially when quality and relationship outcomes matter.
Cost vs. human wage	claude-sonnet-5	2/5	AI tools can cheaply generate contact lists, but the relationship development component still requires human labor, keeping overall costs comparable to human-led processes.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	AI tools can perform parts of contact identification (database mining, prospect segmentation) but no mature product reliably performs the full task of developing contacts and assessing fit for specific promotional campaigns. Existing CRM and marketing platforms lack the contextual judgment needed to vet and cultivate industry relationships at scale.
Technical feasibility today	claude-sonnet-5	2/5	Some CRM and lead-generation tools help surface potential contacts, but no deployed product reliably identifies and develops relationships with dealers/distributors autonomously.

Develop comprehensive marketing strategies, using knowledge of products and technologies, markets, and regulations.

CI 25–38 · exposure 25 · augmentation 75 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	While marketing teams actively experiment with AI writing and analytics tools, adoption of AI for core strategic planning remains limited and mostly supplementary. Strategy remains a high-judgment, human-led function in most organizations, with AI integration slow and cautious.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising sectors show above-average AI tool adoption for content and analytics, but strategic planning itself remains a slower-adopted, judgment-heavy function.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI excels at augmenting strategy work: rapid competitive analysis, market segmentation, regulatory landscape summaries, and drafting multiple strategic scenarios. Marketing managers using modern AI tools can substantially accelerate research, brainstorming, and option generation while retaining final judgment.
Augmentation potential	claude-sonnet-5	4/5	AI substantially aids market research synthesis, competitive analysis, drafting, and scenario generation, meaningfully boosting a manager's productivity while they retain ultimate strategic control.
Task automatability	claude-haiku-4-5-20251001	2/5	Strategic marketing development requires original synthesis of market data, competitive positioning, and regulatory nuance tailored to specific products and organizational contexts. While AI can assist with data gathering and analysis, the creative and executive judgment needed to develop a comprehensive strategy—choosing among competing options and integrating disparate factors—remains substantially human-dependent today.
Task automatability	claude-sonnet-5	2/5	Developing a full marketing strategy requires synthesizing market context, competitive positioning, regulatory nuance, and organizational judgment that current AI can support but not independently produce with equal quality end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Marketing strategy is typically developed by licensed or credentialed professionals and approved by C-suite executives who retain accountability for market outcomes and regulatory compliance. Organizational risk tolerance for fully autonomous strategy generation is low, and errors carry reputational and financial consequences that create strong friction against automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement mandates a human do this, but organizational accountability, brand risk, and regulatory compliance concerns create moderate friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	The cost of AI prompting, iteration, expert oversight, and human refinement to produce a strategy suitable for leadership review approaches the cost of a skilled strategist's time, especially when accounting for errors and rework. No order-of-magnitude savings is evident.
Cost vs. human wage	claude-sonnet-5	2/5	While AI can cheaply generate drafts, the human oversight, market research verification, and regulatory review needed keep total cost closer to a manager's loaded wage than to a fraction of it.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed products reliably generate end-to-end marketing strategies that organizations trust without heavy human oversight. AI tools (ChatGPT, Claude) can draft outlines and tactical suggestions, but strategic decisions require human validation, market expertise, and accountability that production systems do not yet provide autonomously.
Technical feasibility today	claude-sonnet-5	2/5	AI tools (e.g., ChatGPT, Jasper, Copilot) can draft strategy outlines or market summaries, but no production system reliably generates comprehensive, compliant marketing strategies without heavy human authorship and validation.

Coordinate with marketing team members, graphic artists, and other workers to develop and implement marketing programs.

CI 28–32 · exposure 25 · augmentation 75 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Marketing and advertising sectors show moderate AI adoption, with widespread use of analytics and design tools, but team coordination and program management remain largely human-driven. Pilots of AI-assisted planning exist, but production-level replacement of manager-level coordination is not yet common.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising are relatively fast-adopting sectors for AI tools (content generation, analytics), but the specific coordination/management function still sees mostly pilot-level AI assistance rather than deep integration.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI can meaningfully assist managers in this role by summarizing team feedback, drafting communications, tracking milestones, and flagging scheduling conflicts—tasks that free time for strategic and creative judgment. Current tools (LLMs, project dashboards) already provide useful productivity lift while managers remain in the loop.
Augmentation potential	claude-sonnet-5	4/5	AI tools significantly help managers draft briefs, summarize campaign data, generate creative options, and streamline communication, meaningfully boosting productivity while the manager remains central to coordination.
Task automatability	claude-haiku-4-5-20251001	2/5	This task requires real-time coordination, stakeholder management, and creative synthesis across multiple disciplines. While AI can help draft communication templates and summarize input, the core work—prioritizing competing needs, negotiating timelines, and making judgment calls on creative direction—requires human leadership. Current AI cannot reliably manage async team dynamics or resolve conflicts end-to-end.
Task automatability	claude-sonnet-5	2/5	This task is fundamentally interpersonal coordination and cross-functional leadership, which AI cannot perform end-to-end; AI can assist with scheduling, drafting briefs, and content generation but not the human coordination itself.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Marketing leadership roles typically require organizational authority, stakeholder trust, and accountability for creative outcomes. Companies are reluctant to delegate creative direction or team coordination to AI without human judgment, and clients often expect human account management. These norms and organizational friction pose material adoption barriers.
Adoption barriers	claude-sonnet-5	3/5	No formal licensing requirement exists, but organizational reliance on human judgment, trust, and interpersonal relationship management creates real friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Current AI tools for coordination and content summarization are inexpensive per inference, but the overhead of human review, re-prompting, and conflict resolution means the all-in cost rivals or exceeds a junior coordinator's wage. Savings only emerge with very high task volume and low error tolerance.
Cost vs. human wage	claude-sonnet-5	2/5	Since the core coordination and relationship management must remain human-led, AI only supplements the task; the human manager's wage cost is largely unavoidable, so cost savings are limited to sub-tasks like status updates or content drafts.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed product reliably orchestrates multi-disciplinary marketing team coordination. AI can assist with scheduling tools, email drafting, or summarizing feedback, but no production system handles the full workflow of program planning, stakeholder alignment, and creative synthesis without substantial human oversight.
Technical feasibility today	claude-sonnet-5	2/5	Products like project management AI tools and content generators exist to support pieces of marketing coordination, but no deployed system manages team coordination and stakeholder alignment reliably at scale.

Plan and execute advertising policies and strategies for organizations.

CI 28–32 · exposure 25 · augmentation 75 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Marketing and advertising sectors are adopting AI tools (generative AI, ad-tech optimization, analytics) at a rapid clip, but adoption remains concentrated on assistive functions (copy ideation, audience segmentation, performance tracking) rather than managerial strategy execution. Production deployment of autonomous strategy planning is rare.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising are among faster-adopting sectors for AI tools (copywriting, targeting, analytics), but strategic planning functions remain largely human-led with AI used only as an aid.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI offers substantial augmentation for this task: generative models can draft multiple campaign concepts, analytics can surface market trends and competitor intelligence, and optimization tools can forecast audience response. A human manager using these tools can accelerate research and testing phases significantly while retaining strategic control.
Augmentation potential	claude-sonnet-5	4/5	AI substantially augments this task by generating campaign ideas, analyzing market data, drafting strategy documents, and predicting performance, significantly speeding up the planning process while humans retain final decision-making.
Task automatability	claude-haiku-4-5-20251001	2/5	AI can assist with data analysis, trend research, and drafting strategy components, but planning and executing advertising policies requires business judgment, stakeholder negotiation, market intuition, and accountability that remain firmly human-driven. No current system can end-to-end replace a manager's strategic oversight and decision authority at ≥50% time savings with equal quality.
Task automatability	claude-sonnet-5	2/5	This is a strategic, judgment-heavy task involving organizational goals, brand positioning, budget allocation, and stakeholder alignment that AI cannot autonomously perform end-to-end today. AI can assist with research and drafting components but cannot own the strategic planning and execution accountability.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Advertising and promotions managers are typically employed in professional-service and corporate roles where organizational authority, accountability, and client relationship management are vested in the human role. Liability for campaign outcomes, brand stewardship, and stakeholder trust create strong friction against full substitution.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement, but organizational trust, accountability for brand reputation, and the need for executive judgment create meaningful friction against full delegation to AI.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI can reduce some research and content-drafting costs, but strategic planning requires senior human judgment that remains much cheaper to obtain than attempting to automate it reliably. The all-in cost of AI infrastructure and human oversight would not undercut a manager's loaded wage for this integrative role.
Cost vs. human wage	claude-sonnet-5	2/5	AI tools reduce cost for supporting research and content generation, but the strategic planning, stakeholder negotiation, and execution oversight still require expensive human expertise, keeping overall cost comparable to human-led work.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While AI tools (generative models, analytics dashboards) can support research and drafting phases, no deployed product reliably performs independent strategic planning and policy execution for advertising organizations. Tools exist in narrow scopes (copy generation, audience analytics) but not for the full managerial task.
Technical feasibility today	claude-sonnet-5	2/5	No deployed product independently plans and executes full advertising strategy for an organization; existing tools handle discrete sub-tasks like ad copy, targeting, or analytics but require human strategic oversight throughout.

Coordinate activities of departments, such as sales, graphic arts, media, finance, and research.

CI 25–32 · exposure 25 · augmentation 75 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	While information-sector organizations experiment with workflow automation, actual replacement of coordination roles remains rare. Adoption of AI-augmented coordination tools is slow because managers retain primary responsibility and real decisions still require human judgment.
Sector adoption velocity	claude-sonnet-5	3/5	Marketing and advertising sectors are moderately fast adopters of AI tools for workflow and content tasks, though managerial coordination functions lag behind content-generation use cases.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI excels at gathering cross-departmental data, highlighting scheduling conflicts, summarizing progress, and surfacing bottlenecks—tasks that significantly reduce the manual burden on a coordinator and let them focus on negotiation and decision-making. This represents meaningful productivity uplift while keeping humans central.
Augmentation potential	claude-sonnet-5	4/5	AI tools (project trackers, communication summarizers, scheduling assistants) meaningfully help managers track cross-departmental activities and status, improving efficiency while the manager still directs coordination.
Task automatability	claude-haiku-4-5-20251001	2/5	Coordinating across multiple departments requires understanding organizational context, negotiating competing priorities, and making judgment calls about resource allocation. Current AI can assist with scheduling and information synthesis but cannot reliably own cross-functional coordination without constant human oversight and decision-making.
Task automatability	claude-sonnet-5	2/5	Cross-departmental coordination requires relationship management, negotiation, and contextual judgment across teams that AI cannot fully replicate; only scheduling and status-tracking sub-pieces are automatable today.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Coordination roles typically require management authority, accountability for outcomes, and organizational decision-making power that are legally and structurally bound to a human manager. Organizations strongly prefer humans in roles where accountability and judgment over personnel and budgets is essential.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement, but organizational trust, accountability, and interpersonal dynamics create real friction against full automation of managerial coordination roles.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI tools for task management and reporting are inexpensive, but the human cost of a manager doing this coordination work is lower than deploying AI systems that still require significant human oversight and decision-making to maintain quality.
Cost vs. human wage	claude-sonnet-5	2/5	Human managers remain necessary for interpersonal coordination and accountability; AI tools reduce some administrative overhead but don't replace the managerial cost structure.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While AI scheduling and project management tools exist, coordinating departments end-to-end involves stakeholder management, conflict resolution, and organizational knowledge that current products handle only partially. No mature system reliably replaces a human coordinator across heterogeneous teams.
Technical feasibility today	claude-sonnet-5	2/5	Project management and collaboration tools offer AI-assisted scheduling and status updates, but no deployed product autonomously coordinates cross-functional departments at the managerial level.

Direct and coordinate product research and development.

CI 16–26 · exposure 20 · augmentation 63 · importance 3.4/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Advertising and promotions sectors show moderate AI adoption in analytics and content creation, but adoption of autonomous R&D direction remains minimal; most organizations retain human managers in core strategic roles and use AI only for assistive functions.
Sector adoption velocity	claude-sonnet-5	2/5	While marketing and R&D functions are adopting AI tools for research and data analysis, the managerial coordination and directing role itself sees little direct AI displacement or agentic adoption.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can meaningfully assist R&D managers by synthesizing market research, competitor analysis, and trend data, accelerating insight generation. However, the strategic direction and coordination authority remain with the human, making this a strong augmentation case rather than replacement.
Augmentation potential	claude-sonnet-5	4/5	AI tools can strongly assist by synthesizing market research, generating insights, tracking project data, and drafting reports, meaningfully boosting the manager's productivity while they retain decision authority.
Task automatability	claude-haiku-4-5-20251001	2/5	Product R&D direction requires strategic decision-making, stakeholder alignment, and judgment calls that depend on market context and organizational goals. While AI can assist with data synthesis and trend analysis, the core coordination and directional authority remain fundamentally human; current systems cannot autonomously own this end-to-end.
Task automatability	claude-sonnet-5	2/5	Directing and coordinating R&D efforts involves strategic judgment, cross-functional leadership, and decision-making that current AI cannot autonomously perform end-to-end; AI can support analysis but not direct people or set strategy.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Substantial organizational and fiduciary barriers exist: R&D direction typically carries accountability for outcomes, budget allocation, and strategic risk that require human judgment and sign-off. Liability, reputation, and regulatory expectations around product strategy strongly favor human decision-making authority.
Adoption barriers	claude-sonnet-5	3/5	No formal licensing requirement, but organizational structure, accountability, and the need for human leadership and interpersonal coordination create substantial practical barriers to automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Comprehensive AI direction of R&D requires significant customization, integration with organizational workflows, and human oversight; total cost per output remains comparable to or exceeds the loaded manager wage, especially when quality and accountability are factored in.
Cost vs. human wage	claude-sonnet-5	1/5	Since AI cannot perform the core coordination and directing functions, there is no viable AI substitute cost to compare; the human manager remains necessary.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No mature product reliably performs autonomous R&D direction and coordination at production scale. AI tools can support research analysis and reporting, but deployed systems do not yet reliably orchestrate the multi-stakeholder, judgment-heavy aspects of directing development efforts.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product exists that autonomously directs or coordinates product research and development activities; this remains a managerial function requiring human leadership.

Confer with department heads or staff to discuss topics such as contracts, selection of advertising media, or product to be advertised.

CI 7–32 · exposure 13 · augmentation 50 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Advertising and marketing sectors digitize moderately, but conferencing with department heads remains fundamentally interpersonal and hierarchical; adoption of autonomous AI for this task is minimal, and most adoption to date involves only assistive tools (scheduling, note-taking).
Sector adoption velocity	claude-sonnet-5	3/5	Advertising/marketing is a fast-digitizing professional services sector with growing AI tool use, but this specific interpersonal conferring task sees little direct AI adoption yet.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist by preparing briefings, summarizing prior decisions, suggesting media options, or drafting contract language before or after conferences, moderately raising manager productivity without replacing the human's role in the actual dialogue.
Augmentation potential	claude-sonnet-5	3/5	AI can help prepare briefing materials, summarize contract terms, or analyze media options ahead of these discussions, but does not participate in or replace the actual conferring.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can summarize contracts and suggest media options, the task requires real-time dialogue, judgment about stakeholder concerns, and negotiation—activities that need human presence and decision-making authority. Current AI cannot reliably handle the interpersonal dynamics and contextual nuance of department-level conferencing.
Task automatability	claude-sonnet-5	1/5	This is a live interpersonal negotiation and decision-making meeting requiring relationship management, persuasion, and real-time judgment that AI cannot conduct end-to-end today.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Management authority and organizational hierarchy create strong barriers: only a human manager with real accountability and organizational standing can effectively confer with peers on contracts and strategy. Stakeholders expect human judgment and commitment, and liability for decisions typically rests with the human.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement exists, but organizational norms, trust, accountability for contract decisions, and stakeholder preference for human interaction create meaningful friction.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Even with AI assistance, a manager must still attend and lead the meeting; AI cost savings are marginal since the human labor remains essential. The all-in cost of AI oversight and setup likely exceeds any time reduction for this human-centric activity.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this conferring function, so cost comparison favors the human by default since no viable AI alternative exists.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Chatbots can draft meeting agendas or generate media recommendations, but no deployed product reliably conducts actual multi-stakeholder conferences with the credibility and authority required in a business context. Meeting transcription and note-taking assistants exist, but not autonomous task performance.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product autonomously confers with staff or department heads to negotiate contracts or media selection; this remains firmly a human-led interaction.

Train and direct workers engaged in developing and producing advertisements.

CI 7–30 · exposure 13 · augmentation 50 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Despite digitization of advertising, the actual training and direction of creative workers remains firmly human-driven; adoption of AI for this function is minimal and limited to experimental pilots rather than production displacement.
Sector adoption velocity	claude-sonnet-5	2/5	While marketing/advertising as a sector adopts AI content tools quickly, the specific managerial task of training and directing workers sees little AI-driven displacement or adoption.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist managers by drafting training materials, analyzing worker performance data, and suggesting constructive feedback points, meaningfully raising manager productivity on preparation and analysis while the manager retains decision-making and mentorship authority.
Augmentation potential	claude-sonnet-5	3/5	AI can help managers create training materials, review ad drafts, and provide feedback templates, moderately aiding but not transforming the core people-management task.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist with content generation and idea synthesis, the core task of training and directing human workers requires real-time judgment, mentorship, and adaptive feedback that AI cannot reliably replicate end-to-end. AI might accelerate parts of training material creation, but cannot manage the interpersonal dynamics or make contextual management decisions.
Task automatability	claude-sonnet-5	1/5	Training and directing staff requires interpersonal leadership, mentorship, and real-time judgment that current AI cannot perform end-to-end; at most it can supply supporting materials.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Organizations strongly prefer humans to make directional and mentorship decisions; liability concerns arise if AI-generated guidance harms worker development or morale. Customer and employee expectations create organizational friction against removing human judgment from training and direction.
Adoption barriers	claude-sonnet-5	3/5	No formal licensing is required, but organizational structure, accountability, and the inherently interpersonal nature of supervising/training staff create strong practical barriers to automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	The cost of integrating AI into management training systems, maintaining accuracy of feedback, and requiring human oversight to correct poor guidance would approach or exceed the cost of human managers performing the task directly.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this managerial function, so no meaningful cost comparison favors AI; a human manager remains necessary.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed product reliably trains and directs creative teams as a manager would. AI can generate content drafts and suggest feedback, but lacks the contextual understanding of individual worker performance, team dynamics, and project-specific direction that production management demands.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product manages or trains creative teams autonomously; this remains a human management function with only ancillary AI tools (e.g., content generation aids).

Manage sales team, including setting goals, providing incentives, and evaluating employee performance.

CI 7–28 · exposure 13 · augmentation 75 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Mid-market and enterprise companies have adopted analytics-driven performance dashboards and some automated goal tracking, but autonomous team management remains rare; most adoption is still in the pilot or support phase rather than full replacement of managerial oversight.
Sector adoption velocity	claude-sonnet-5	2/5	While marketing/advertising is a digitally advanced sector, actual AI adoption for direct people-management tasks like goal-setting and performance evaluation remains nascent and mostly advisory.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI significantly augments sales managers through performance dashboards, predictive analytics on rep behavior, automated report generation, and data-driven recommendation engines for goal-setting and compensation; these tools measurably raise managerial productivity while the manager retains decision authority.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist managers via performance data analysis, goal-tracking dashboards, and draft feedback, enhancing but not replacing the manager's judgment.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist with data analysis for performance metrics and goal-setting frameworks, the core activities—setting contextual goals, providing meaningful incentives tailored to individuals, and conducting nuanced performance evaluations—require human judgment about motivation, team dynamics, and career development that current AI cannot reliably handle end-to-end.
Task automatability	claude-sonnet-5	1/5	People management—setting goals, motivating, and evaluating employees—requires interpersonal judgment, trust-building, and accountability that current AI cannot perform end-to-end without a human manager driving it.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Legal and organizational barriers are significant: employment law requires human accountability for performance decisions, incentive allocation, and disputes; labor regulations and company liability mean that a licensed HR professional or manager must legally review and sign off on personnel actions and compensation changes.
Adoption barriers	claude-sonnet-5	4/5	Organizational structure, legal accountability for HR decisions (evaluations, incentives, terminations), and need for human judgment and trust create strong barriers to automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI tools (analytics platforms, CRM integrations) can reduce clerical overhead, but the total cost of implementation, data infrastructure, and required human oversight remains comparable to or exceeds the value of automating clerical portions only; the manager's core judgment role cannot be cheaply replaced.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this managerial function, so no meaningful cost comparison exists; a human manager remains required.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Deployed HR and performance management tools exist but primarily handle dashboarding and data aggregation; they do not autonomously manage sales teams or make substantive personnel decisions. Production systems require human managers to interpret insights and make final calls.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product autonomously manages a sales team; existing tools only provide analytics or performance dashboards that inform, not replace, a human manager.

Direct, motivate, and monitor the mobilization of a campaign team to advance campaign goals.

CI 5–16 · exposure 8 · augmentation 50 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Despite digital transformation in marketing, team leadership and motivation remain deeply human functions in advertising and promotions work; adoption of AI to replace campaign managers is negligible.
Sector adoption velocity	claude-sonnet-5	2/5	While marketing/advertising sectors adopt AI tools quickly for content and analytics, adoption of AI for actual people-management and team motivation remains minimal.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can provide managers with real-time dashboards on campaign performance, predictive analytics on team productivity, and automated scheduling, meaningfully augmenting their ability to monitor and coordinate; however, motivation and strategic direction remain human.
Augmentation potential	claude-sonnet-5	3/5	AI can assist with campaign dashboards, progress tracking, and communication drafts that help a manager monitor and direct the team more efficiently.
Task automatability	claude-haiku-4-5-20251001	2/5	This task requires real-time human judgment, interpersonal motivation, and adaptive leadership in response to team dynamics and campaign performance. While AI can assist with monitoring metrics and scheduling, the core work of directing and motivating people toward dynamic goals remains fundamentally human.
Task automatability	claude-sonnet-5	1/5	This is a leadership and interpersonal management task requiring real-time human motivation, relationship building, and team direction that AI cannot perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Campaign teams require human leadership for accountability, legal responsibility for campaign compliance, and organizational expectations that management roles carry human authority and trust. Employment law and professional norms strongly protect human manager positions.
Adoption barriers	claude-sonnet-5	4/5	Organizational structure requires a human manager with authority, accountability, and interpersonal trust to direct staff, creating strong practical and hierarchical barriers to automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The cost of building and maintaining AI team-management systems, plus required human oversight, substantially exceeds the salary of entry-level campaign coordinators or junior managers, making substitution economically infeasible.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute for this managerial function, so cost comparison favors the human entirely since AI cannot deliver the output.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI product reliably performs team direction and motivation at scale in production. AI management or coordination tools exist for workflow, but none demonstrably substitute for human managers directing and motivating campaign teams toward strategic goals.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product manages or motivates human teams autonomously; AI tools at best support scheduling or reporting, not team leadership itself.

Assemble and communicate with a strong, diverse coalition of organizations or public figures, securing their cooperation, support, and action, to further campaign goals.

CI 0–13 · exposure 0 · augmentation 38 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Adoption is near-zero because the task cannot be automated; even AI-forward organizations rely entirely on human managers to build and maintain coalition relationships, as no alternative exists.
Sector adoption velocity	claude-sonnet-5	2/5	Marketing and advertising sectors adopt AI tools quickly for content and analytics, but coalition-building and stakeholder negotiation remain untouched by automation in practice.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could modestly assist by identifying potential coalition partners, drafting outreach messaging, or tracking stakeholder communications, but the core work of persuasion, negotiation, and securing commitment remains human-driven and AI provides limited leverage.
Augmentation potential	claude-sonnet-5	3/5	AI can help draft outreach messages, track stakeholder communications, research potential partners, and manage CRM-like coordination, meaningfully supporting but not replacing the relational work.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires building trust, negotiating with stakeholders, and securing genuine commitment—inherently human relationship and persuasion work that AI cannot perform end-to-end today. Current AI cannot independently identify, approach, negotiate with, or secure binding cooperation from real organizations or public figures.
Task automatability	claude-sonnet-5	1/5	This is fundamentally relationship-building, negotiation, and persuasion work requiring trust and human judgment that current AI cannot execute end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Hard legal and organizational barriers exist: securing cooperation from external organizations requires authorized human signatories, contracts, and liability accountability that only humans can legally provide. Trust-building inherently requires human-to-human or human-to-organization contact.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement exists, but strong organizational and reputational friction exists since coalition partners expect to engage with accountable human representatives, not AI.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	AI cannot perform this task meaningfully, so cost comparison is not applicable; a human manager remains essential and cannot be replaced by current systems regardless of cost.
Cost vs. human wage	claude-sonnet-5	1/5	AI cannot substitute for the human relationship capital and trust-building involved, so there is no meaningful cost comparison—human effort is required regardless of AI cost.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product reliably performs stakeholder coalition-building and securing organizational or public figure cooperation autonomously. This requires human credibility, legal authority, and negotiation capability that AI systems do not possess in production.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product autonomously builds coalitions, negotiates cooperation, or secures commitments from organizations or public figures; this remains a human relational task.

Attend or participate in conferences, community events, and promotional events related to products or technologies.

CI 0–7 · exposure 0 · augmentation 38 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	This task is not automatable by design—it depends on human presence and relationship-building, so sectors are not adopting AI substitutes because none exist or are relevant.
Sector adoption velocity	claude-sonnet-5	2/5	Marketing/advertising sectors adopt AI tools quickly for content and analytics, but the physical event-attendance component sees essentially no AI displacement.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI can modestly assist with event preparation (scheduling, briefing materials, lead identification) but does not materially transform a manager's productivity at the core task of attending and participating in events.
Augmentation potential	claude-sonnet-5	3/5	AI can help managers prepare materials, research attendees, draft talking points, and follow up post-event, but the on-site participation itself is not augmented in real time.
Task automatability	claude-haiku-4-5-20251001	1/5	This task fundamentally requires human presence and relationship-building at physical or synchronous events. AI cannot attend conferences, network, or participate in community engagement in any meaningful way today.
Task automatability	claude-sonnet-5	1/5	Physical attendance and in-person networking/representation cannot be performed by current AI systems; this is an inherently embodied, relational task.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Strong barriers protect this task: relationship-building, brand representation, and networking require human judgment and presence; clients and stakeholders expect human interaction and decision-making authority at promotional events.
Adoption barriers	claude-sonnet-5	4/5	While not licensed work, strong organizational and social expectations require a human representative for relationship-building, networking, and real-time judgment at events.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The task inherently requires human time and travel; an AI system has no meaningful cost savings when the output is human presence itself.
Cost vs. human wage	claude-sonnet-5	1/5	AI has no way to perform physical attendance, so there is no viable AI cost basis to compare; the human is the only option.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product performs physical or synchronous event attendance. AI might assist with event briefing materials or follow-up tasks, but cannot substitute for the core requirement of human presence and participation.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product substitutes for a human physically attending and representing a company at events; this remains entirely research-irrelevant/human-only territory.

Represent company at trade association meetings to promote products.

CI 0–7 · exposure 0 · augmentation 38 · importance 3.4/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	No measurable adoption of AI agents attending trade association meetings in any sector. This remains entirely human-driven across advertising, marketing, and corporate functions.
Sector adoption velocity	claude-sonnet-5	2/5	Marketing/advertising functions adopt AI tools for content and analytics fairly quickly, but the specific in-person representation task sees little to no AI adoption.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could assist by preparing talking points, summarizing competitor activities, or drafting follow-up communications, but these are peripheral to the core task of in-person representation and relationship-building.
Augmentation potential	claude-sonnet-5	3/5	AI can help managers prepare talking points, research attendees, draft promotional materials, and summarize meeting outcomes, but cannot perform the representation itself.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires real-time interpersonal negotiation, relationship-building, and company representation at live events. Current AI systems cannot meaningfully substitute for a human executive presence, credibility signaling, or dynamic negotiation needed at trade association meetings.
Task automatability	claude-sonnet-5	1/5	This is an in-person relationship-building and representation task requiring physical presence, networking, and real-time social judgment that current AI cannot perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Significant barriers exist: corporate legal authority to represent the company typically requires a designated human; liability and reputational risk demand human accountability; and trade associations expect human relationship and networking, which are core to the function.
Adoption barriers	claude-sonnet-5	4/5	Physical presence, personal relationships, trust-building, and organizational representation create strong practical barriers to any automated substitution, though not a formal licensing requirement.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Even if AI could attend meetings (it cannot), the cost of human oversight, liability management, and ensuring appropriate representation would far exceed the loaded wage of sending a manager directly.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this physical representational function, so any comparison favors the human at essentially infinite relative AI cost for the core task.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product can reliably represent a company at trade association meetings independently. This requires human judgment, legal authority, corporate accountability, and genuine relationship management that AI cannot perform in production today.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product attends trade association meetings or represents a company in person; this remains entirely a human activity.

Related occupations — Management

How to read this

A high substitution score does not mean this job disappears — it means a large share of its current tasks face replacement pressure, so the mix of tasks is likely to change. High augmentation alongside substitution typically means the occupation reorganizes around the protected tasks. Wide confidence intervals mean the rater panel disagreed: treat those scores as open questions, not verdicts.

What would change this score

New model capabilities (automatability, feasibility), falling inference costs (cost ratio), regulation and licensing shifts (barriers), and measured sector adoption (velocity) all re-enter at every index release. Each release is recomputed, versioned and kept queryable — scores are claims with a date on them, not permanent labels.