Public Relations Managers
11-2032.00Median wage $146,910/yr74,850 employed (US)Rank #244 of 923 scored · top 26% by substitution
Plan, direct, or coordinate activities designed to create or maintain a favorable public image or raise issue awareness for their organization or client.
Sub-scores
0–100 · band = confidence interval from rater disagreement
Substitution36
Exposure31
Augmentation69
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
20 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
0%
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%31
panel mean rating 2.3/5 → substitution pressure 31/100
Technical feasibility todayw 20%31
panel mean rating 2.2/5 → substitution pressure 31/100
Cost vs. human wagew 15%32
panel mean rating 2.3/5 → substitution pressure 32/100
Adoption barriersw 20%inverted — strong barriers lower the score50
panel mean rating 3.0/5 (barrier strength) → substitution pressure 50/100
Sector adoption velocityw 10%43
panel mean rating 2.7/5 → substitution pressure 43/100
Task breakdown (20 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.
Write interesting and effective press releases, prepare information for media kits, and develop and maintain company internet or intranet web pages.
68CI 61–75 · exposure 62 · augmentation 88 · click for rater detail
Write interesting and effective press releases, prepare information for media kits, and develop and maintain company internet or intranet web pages.
68| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 4/5 | PR and marketing departments, concentrated in information-rich and digitally mature sectors, have adopted generative AI for drafting and ideation relatively quickly; many agencies and in-house teams now use AI tools to accelerate content production, with observable shifts in workflow. |
| Sector adoption velocity | claude-sonnet-5 | 4/5 | Marketing and communications functions have been fast adopters of generative AI for content drafting, with many firms integrating it into standard workflows. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI provides high-value assistance for brainstorming angles, generating initial drafts, and rapidly iterating web content variations, meaningfully raising a PR manager's output while they retain strategic oversight and brand judgment. This is one of the stronger augmentation use cases in the occupation. |
| Augmentation potential | claude-sonnet-5 | 5/5 | AI is highly effective as a drafting and ideation assistant for press releases, media kits, and web copy, substantially speeding up the writing process while the manager retains strategic and editorial control. |
| Task automatability | claude-haiku-4-5-20251001 | 3/5 | AI can generate draft press releases and web copy at scale with reasonable speed, and can prepare basic media kit content, achieving significant time savings on initial composition. However, the 'interesting and effective' standard requires strategic judgment about company voice, news angles, and audience targeting that typically demands human refinement and approval, preventing full autonomous end-to-end automation. |
| Task automatability | claude-sonnet-5 | 4/5 | LLMs can draft press releases, media kit copy, and web content quickly and often at near-professional quality, though final review for brand voice, accuracy, and strategic nuance is still needed. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | Few hard regulatory or licensing barriers exist for AI-assisted press release writing, though reputational risk and organizational standards around brand voice create friction. Most PR teams remain reluctant to publish without human sign-off, but this is preference rather than legal requirement. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement exists for writing press releases or web content, though brand risk and reputational liability create moderate organizational caution around fully unsupervised AI output. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | The cost of LLM inference plus human oversight and editing is substantially cheaper than hiring a PR professional to write press releases and web content from scratch, though not yet at order-of-magnitude savings given continued human quality control needs. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | AI drafting tools cost a small fraction of a PR manager's loaded salary per piece of content, though integration and editorial oversight add some cost. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | Deployed products (LLMs, generative AI copywriting tools) can produce press releases and web content, but material gaps remain: AI-generated copy often lacks nuance, requires significant editorial oversight, and frequently needs subject-matter expertise input. Production use exists but is typically limited to drafting and assistance rather than autonomous publishing. |
| Technical feasibility today | claude-sonnet-5 | 4/5 | Generative AI tools are already used widely in production by PR teams and agencies to draft releases and web copy, with human editing layered on top. |
Design and edit promotional publications, such as brochures.
63CI 46–80 · exposure 62 · augmentation 88 · click for rater detail
Design and edit promotional publications, such as brochures.
63| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | PR and marketing sectors show moderate uptake of AI design and copywriting tools (pilots and some production use), but adoption remains piecemeal and often assistive rather than fully automating the task. Larger firms move faster, but many still prefer human creatives for high-stakes brand work. |
| Sector adoption velocity | claude-sonnet-5 | 4/5 | Marketing and communications functions have rapidly adopted AI design and content tools, with widespread production use across companies of varying sizes. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI excels at accelerating drafts, generating layout options, editing copy, and suggesting visual elements, significantly boosting a PR manager's productivity while they retain creative direction and final approval. This is a strong augmentation scenario where the human expert benefits from AI-generated raw material and iteration support. |
| Augmentation potential | claude-sonnet-5 | 5/5 | AI substantially speeds up ideation, drafting, and iteration of brochure designs and copy while the PR manager retains creative and brand oversight. |
| Task automatability | claude-haiku-4-5-20251001 | 3/5 | AI can generate draft layouts, text, and edit promotional copy with reasonable quality, but creative direction, brand consistency, and final review typically require human judgment. A knowledgeable user might achieve 40–50% time savings with template-based or AI-assisted design tools, though full end-to-end automation at equal quality remains unclear. |
| Task automatability | claude-sonnet-5 | 4/5 | AI design tools (e.g., Canva AI, Adobe Firefly, generative layout/copy tools) can generate brochure drafts, layouts, and copy quickly, saving significant time though final polish and brand judgment still need human review. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | No legal licensing requirement exists for promotional design, but organizational brand standards, liability concerns over message accuracy, and preference for human creative judgment create meaningful friction to full automation. Customer and internal stakeholder expectations for human-led design decisions also slow adoption. |
| Adoption barriers | claude-sonnet-5 | 1/5 | No licensing, regulatory, or liability barriers restrict AI-assisted design and editing of promotional materials. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Design and editing AI tools are inexpensive to run, but integration, prompt engineering, and mandatory human review and rework add overhead. For a skilled PR manager at typical wage, the all-in cost of AI plus oversight may rival or exceed outsourcing to junior staff or freelancers. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | AI design subscriptions cost a small fraction of a designer's or manager's hourly wage for producing draft layouts and copy, though some oversight cost remains. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | Products like Canva, Microsoft Designer, and generative AI tools can produce competent brochure drafts and edits, but they often require iterative refinement, fact-checking, and brand-alignment review. Production deployment exists in some organizations, but error rates and quality variance remain material enough that human oversight is standard. |
| Technical feasibility today | claude-sonnet-5 | 4/5 | Deployed products like Canva Magic Design, Adobe Express, and Microsoft Designer reliably produce publication-ready drafts in production use today, though customization for brand nuance still requires human refinement. |
Evaluate advertising and promotion programs for compatibility with public relations efforts.
55CI 38–72 · exposure 50 · augmentation 75 · click for rater detail
Evaluate advertising and promotion programs for compatibility with public relations efforts.
55| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Marketing and PR teams are piloting content-analysis and messaging-alignment tools, but widespread production deployment remains limited. Early adopters in larger firms and agencies exist, but the task remains below mainstream automation adoption rates. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | PR and marketing sectors are moderately fast adopters of AI tools for content and sentiment analysis, but strategic evaluation tasks remain largely human-led with pilots more common than full deployment. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can rapidly flag potential conflicts, summarize compatibility findings, and draft recommendations, significantly accelerating the review process while the PR manager retains decision-making authority and strategic oversight. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI can quickly analyze sentiment, messaging consistency, and competitive positioning to inform the manager's evaluation, meaningfully speeding up the research and drafting portions of this task. |
| Task automatability | claude-haiku-4-5-20251001 | 4/5 | AI can analyze advertising and promotion materials against PR messaging frameworks, identify inconsistencies, and generate compatibility reports with high accuracy. Document review and pattern-matching are strong AI capabilities, though final strategic judgment may retain some human discretion, enabling >50% time savings. |
| Task automatability | claude-sonnet-5 | 2/5 | This requires strategic judgment about brand alignment, stakeholder perception, and organizational context that current AI cannot reliably assess end-to-end, though it can assist with parts of the analysis.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | No legal mandate requires human sign-off on this compatibility review; it is internal due diligence. Minor friction exists from organizational preference for human judgment and need for PR manager oversight of recommendations, but no hard barriers prevent automation. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement, but organizational and reputational risk means firms want experienced human judgment on brand-sensitive decisions, creating moderate friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | A single AI inference pass analyzing hundreds of promotional assets costs pennies to dollars, whereas a PR manager's hourly rate is $60–120+. Even accounting for integration and oversight, AI is 10–50x cheaper per document evaluated. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | AI can cheaply generate summaries or flag inconsistencies, but the human oversight and judgment needed to validate strategic fit keeps overall cost comparable to or only modestly below human-only performance. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 4/5 | Commercial AI tools (including LLMs and content analysis platforms) can assess messaging alignment, brand consistency, and potential PR conflicts across campaigns. Deployed systems are being used in marketing/PR contexts, though integration into full workflow pipelines remains partially manual. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | No deployed product autonomously evaluates ad/promo programs for PR compatibility; existing tools offer content analysis or sentiment scoring but not holistic strategic evaluation in production. |
Observe and report on social, economic, and political trends that might affect employers.
49CI 37–61 · exposure 42 · augmentation 88 · click for rater detail
Observe and report on social, economic, and political trends that might affect employers.
49| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | PR and communications firms are piloting AI-driven monitoring and trend analysis tools, but production-level adoption is still uneven; many organizations still rely on human curation and interpretation rather than full AI automation. |
| Sector adoption velocity | claude-sonnet-5 | 4/5 | PR and corporate communications functions are adopting AI monitoring and analytics tools quickly, following broader professional services adoption trends. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI excels at rapid scanning of large volumes of news, social media, and economic data to surface candidate trends; PR managers working with AI-assisted tools can monitor a much wider landscape and spend more time on strategic interpretation and response planning. |
| Augmentation potential | claude-sonnet-5 | 5/5 | AI substantially boosts a PR manager's ability to scan, aggregate, and summarize vast trend data, letting them focus on strategic interpretation and recommendations. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Current AI can collect and surface trend data from public sources at scale, but genuine trend analysis requires contextual judgment about what matters to a specific employer and competitive interpretation—tasks that demand human expertise. Significant setup and human validation would be necessary for any meaningful time saving. |
| Task automatability | claude-sonnet-5 | 3/5 | AI can gather and summarize news, social media, and market signals rapidly, but synthesizing which trends are strategically material to a specific employer requires contextual judgment that current systems only partially replicate.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | No hard legal barriers to automation, but organizational adoption is tempered by PR managers' need to exercise judgment on what trends matter, client relationship dynamics, and the risk of missing critical signals if automation is trusted too heavily. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing or legal requirement mandates human performance of this task, though organizations may prefer trusted internal judgment for high-stakes interpretation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI-powered monitoring and data collection can reduce labor hours, but the end-to-end service (integration, filtering false positives, contextual analysis, reporting) still requires PR manager oversight; total cost advantage is modest if present at all. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | AI-driven monitoring and summarization tools are far cheaper than dedicating analyst hours to continuous trend scanning, though some human review cost remains. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | Products exist (sentiment analysis tools, news aggregators, trend-monitoring platforms) that partially automate trend detection, but they produce noisy output and often miss nuanced signals; deployed systems require substantial human curation and interpretation to be trustworthy. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | Products like media monitoring tools, sentiment analysis platforms, and LLM-based research assistants exist and are used in production, but outputs still need human curation for relevance and accuracy. |
Maintain company archives.
49CI 37–60 · exposure 42 · augmentation 63 · click for rater detail
Maintain company archives.
49| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Many organizations use digital archival systems, but adoption remains inconsistent; while larger enterprises and information-intensive sectors deploy AI-assisted tools, many smaller firms and less digitized organizations still rely on manual processes. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | PR and communications departments are moderately digitized and adopting AI tools for content management, but archiving specifically is a low-priority, slowly automated task. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI-powered search, classification suggestions, and automated tagging assist archive managers in organizing and retrieving materials faster, but the human expert remains essential for judgment calls on sensitivity, retention policies, and organizational strategy. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI tools substantially help with tagging, searching, summarizing, and organizing archived materials, improving efficiency while a human still manages final curation decisions. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Organizing and storing documents is partially automatable through document management systems and OCR, but maintaining archives also requires significant judgment about what to keep, how to classify materials by organizational context, and metadata creation—tasks that currently need human oversight and decision-making. |
| Task automatability | claude-sonnet-5 | 3/5 | AI can assist with organizing, tagging, and retrieving digital archives, but full end-to-end archive maintenance including physical materials, judgment on retention, and organizational context still requires human oversight. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Archives often contain sensitive or proprietary information subject to regulatory compliance (GDPR, CCPA, industry-specific regulations), and organizations typically require human accountability for data governance and retention decisions, creating meaningful friction. |
| Adoption barriers | claude-sonnet-5 | 1/5 | No licensing or legal requirement mandates a human perform archival tasks; it's a low-risk administrative function. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | While software reduces labor per document processed, effective archive management still demands trained staff to oversee classification, ensure compliance, and handle exceptions; the all-in cost remains closer to human wages than significantly cheaper. |
| Cost vs. human wage | claude-sonnet-5 | 3/5 | Cloud storage and AI indexing tools are cheap, but integration, migration of legacy materials, and human curation still add meaningful cost comparable to a fraction of a manager's time. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | Document management and archival software with AI-assisted classification exist and are used in production, but they typically require substantial human curation, validation of metadata, and decisions about retention policies and sensitive content handling. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | Document management and AI-assisted metadata/search tools exist and are used in production, but comprehensive archive maintenance for PR-specific materials (media clips, campaign records) is not a mature turnkey product category. |
Draft speeches for company executives and arrange interviews and other forms of contact for them.
47CI 37–57 · exposure 42 · augmentation 88 · click for rater detail
Draft speeches for company executives and arrange interviews and other forms of contact for them.
47| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Professional services and corporate communications are moderately digitized and early-adopting of AI drafting tools, but replacing the relationship and judgment layer of PR work has been slower; pilots are common but full displacement remains limited. |
| Sector adoption velocity | claude-sonnet-5 | 4/5 | PR and corporate communications functions are adopting generative AI tools rapidly for drafting content, reflecting broader fast adoption trends in professional/knowledge-work services. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI drafting tools substantially assist PR managers by generating speech outlines and candidate interview lists, enabling faster iteration and broader research coverage while the human maintains final authority over messaging and relationship management. |
| Augmentation potential | claude-sonnet-5 | 5/5 | AI is highly effective at generating draft speeches, talking points, and background research, letting PR managers focus on final editing, tone, and relationship-based scheduling. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | AI can draft generic speeches and identify interview opportunities, but executive speeches require deep knowledge of company strategy, tone, and reputation nuance that typically need human refinement. The task involves both drafting (partially automatable) and arranging contact (mostly manual coordination), so full end-to-end automation with 50% time savings at equal quality is not reliably achievable today. |
| Task automatability | claude-sonnet-5 | 3/5 | AI can draft speech text quickly given prompts and background info, but arranging interviews and contacts requires relational coordination and scheduling that AI cannot fully handle end-to-end without human oversight. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Companies often prefer human PR managers to understand brand voice and manage executive credibility; media contacts expect human relationship stewards. However, no legal license or hard regulatory requirement prevents automation, creating moderate—not insurmountable—friction. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement, but executive-facing communications often require confidentiality, brand voice consistency, and trust that create some organizational friction against full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI drafting and research tools cost pennies per speech, but the human PR manager must still heavily edit, personalize, and manage all relationship-building and scheduling; the cost advantage is modest because human oversight and judgment remain central to the work. |
| Cost vs. human wage | claude-sonnet-5 | 3/5 | Drafting costs drop significantly with AI, but the interview-arranging component still requires human labor for outreach and relationship management, keeping overall cost savings moderate rather than dramatic. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | Products like ChatGPT can draft speeches and email templates, and CRM/outreach tools can suggest interview opportunities, but deployed systems have not demonstrated reliable production-scale performance for the full task loop of drafting executive-grade speeches and actually arranging sensitive media contacts without substantial human oversight. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | LLM tools are already used in production for speech drafting and talking points, but the interview/contact arrangement portion still relies on human networking, negotiation, and scheduling tools with limited AI autonomy. |
Respond to requests for information about employers' activities or status.
42CI 29–55 · exposure 38 · augmentation 63 · click for rater detail
Respond to requests for information about employers' activities or status.
42| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Adoption remains limited to narrow use cases (auto-responding with canned answers, drafting templates for human review). Most PR teams use AI as a drafting aid, not for autonomous response, reflecting cautious, slow adoption in a function where brand risk is high. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | PR and communications functions are increasingly using AI drafting and monitoring tools, but full delegation of external response handling to AI remains at the pilot stage in most firms. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI provides meaningful assistance: it can quickly draft initial responses, compile relevant facts, and suggest tone, allowing PR managers to focus on judgment and approval rather than blank-page composition. This is genuinely productivity-enhancing within a human-led workflow. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI tools can draft responses, pull background data, and speed up turnaround significantly, while the PR manager retains final judgment and approval. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Only limited parts of this task can be automated today. While AI can draft responses and retrieve factual information, responding to PR requests requires nuanced judgment about what information to release, tone calibration for different audiences, and understanding of organizational sensitivities—all requiring human oversight to avoid reputational damage. |
| Task automatability | claude-sonnet-5 | 3/5 | AI chatbots and drafting tools can handle routine informational requests, but nuanced, sensitive, or high-stakes inquiries (e.g., crisis, media, legal) still require managerial judgment and relationship context, limiting full automation. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Significant barriers exist: organizational policy typically requires a PR professional to approve and sign off on external communications; liability concerns mean errors carry reputational costs; regulatory constraints (especially in finance, healthcare) mandate human responsibility for disclosure; and stakeholders expect human judgment in sensitive inquiries. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement, but organizations often want a human 'face' or accountable spokesperson for external-facing statements, creating moderate reputational/liability friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 3/5 | AI tools (LLMs, drafting assistants) cost roughly comparable to or somewhat less than a PR manager's time for routine responses, but integration overhead and mandatory human review narrow the net savings. |
| Cost vs. human wage | claude-sonnet-5 | 3/5 | For simple, templated requests AI can be far cheaper, but oversight and review needed for reputational risk keep blended costs closer to parity with a skilled PR manager for material inquiries. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed product reliably handles the full task autonomously. Chatbots can answer factual queries, but production PR systems still require humans to approve content, verify accuracy, and make disclosure decisions given legal and reputational stakes. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | Deployed AI systems (chatbots, knowledge-base assistants, drafting tools) already field routine informational requests in many organizations, but for PR-specific external inquiries reliability and tone-sensitivity remain inconsistent. |
Confer with labor relations managers to develop internal communications that keep employees informed of company activities.
39CI 32–45 · exposure 33 · augmentation 75 · click for rater detail
Confer with labor relations managers to develop internal communications that keep employees informed of company activities.
39| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Information and professional services sectors are piloting AI content assistance in PR and communications roles, but the labor-relations dimension—requiring human judgment and stakeholder trust—has seen slower production adoption. Many firms still prefer human-led strategy in this area. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Corporate communications and PR functions are adopting generative AI tools for drafting at a moderate pace, but the labor relations liaison component remains largely human-driven with slower uptake. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can substantially assist by generating communication drafts, summarizing labor concerns, organizing talking points, and offering messaging variants—all while managers retain full decision authority over alignment and tone. This assistive role meaningfully boosts productivity without replacing the human conferencing requirement. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI can significantly speed up drafting, summarizing, and tailoring internal messages, giving PR managers strong productivity gains while they retain control over sensitive labor relations dynamics. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | This task requires collaborative dialogue between labor relations and PR managers to align on messaging and understand nuanced labor concerns. While AI can draft internal communications, the conferencing and relationship-building components—critical to developing credible, contextually appropriate messaging—cannot be meaningfully automated today. |
| Task automatability | claude-sonnet-5 | 3/5 | AI can draft internal communications and summarize activities quickly, but the 'conferring' with labor relations managers requires interactive judgment, negotiation of sensitive framing, and relationship context that current systems cannot fully replace. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Internal communications, especially those touching labor relations, carry reputational and legal risk. Organizations typically require human managers to own messaging decisions and be accountable for accuracy, creating moderate friction against full automation even as AI-assisted drafting becomes routine. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No strict licensing requirement, but labor relations topics often involve legal sensitivity, union considerations, and organizational trust that create moderate friction against full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | While AI drafting tools are inexpensive, the managerial conferencing and oversight required to ensure communications reflect accurate labor-relations strategy means human involvement remains the dominant cost. The time savings from AI assistance do not yet reach order-of-magnitude reductions. |
| Cost vs. human wage | claude-sonnet-5 | 3/5 | AI drafting tools reduce time spent on writing internal comms, lowering costs somewhat, but human oversight, relationship management, and sensitive judgment on labor issues keep overall costs comparable to human-led work. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | AI can generate initial communication drafts and assist with content planning, but current systems cannot reliably conduct authentic multi-party negotiations or strategic discussions that account for labor relations sensitivities. Deployed products lack the conversational depth and institutional awareness needed for this collaborative task. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Products like generative writing assistants and enterprise comms platforms exist to help draft content, but no deployed system autonomously conducts the cross-functional consultation and sensitive judgment calls involved in labor relations messaging. |
Identify main client groups and audiences, determine the best way to communicate publicity information to them, and develop and implement a communication plan.
36CI 25–46 · exposure 33 · augmentation 75 · click for rater detail
Identify main client groups and audiences, determine the best way to communicate publicity information to them, and develop and implement a communication plan.
36| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | PR and marketing sectors show uneven adoption; while some teams use AI for content drafting and analytics, strategic planning and audience determination remain largely human-driven due to accountability requirements and relationship importance in this field. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | PR and marketing sectors show moderate AI adoption with tools for content generation and audience analytics in pilot or partial use, though full strategic planning automation remains uncommon. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI substantially assists PR managers by generating audience segment analysis, suggesting communication channels, drafting messaging options, and providing data-driven insights—augmenting human judgment rather than replacing it in strategic decisions. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI significantly assists PR managers by generating audience insights, drafting communication plans, and suggesting channel strategies, substantially speeding up the planning process while managers retain final judgment. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can assist with audience segmentation and communication channel analysis, the core task of determining 'the best way' to communicate and developing strategy requires human judgment about client relationships, brand positioning, and organizational context that current systems cannot reliably handle end-to-end with 50% time savings at equal quality. |
| Task automatability | claude-sonnet-5 | 3/5 | AI can help draft audience segmentation and communication plans quickly, but the strategic identification of client groups and channel selection requires organizational judgment, stakeholder knowledge, and accountability that current AI cannot fully replace end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Strong barriers exist: PR managers have fiduciary responsibility to clients for communication strategy quality, reputational risk is high for poor decisions, and most organizations require human accountability for campaign strategy and client relationship stewardship. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement exists for this task, but organizational trust, brand risk, and the need for nuanced judgment about audience relationships create moderate friction against full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI systems (for segmentation and copy generation) require significant PR professional time for strategy validation, client relationship management, and implementation oversight, making all-in costs comparable to or higher than hiring human expertise for strategic work. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | While AI tools can cheaply generate drafts and analyses, the human oversight, strategic judgment, and stakeholder validation needed still require significant PR manager time, keeping costs roughly comparable rather than dramatically lower. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | AI tools can generate audience insights and communication suggestions, but no deployed product reliably performs the full strategic task of identifying client groups, determining optimal communication approaches, and developing implementable plans with the judgment quality required in professional PR contexts. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Marketing and PR software with AI features exist to assist with audience analysis and content planning, but no deployed product reliably performs full strategic audience identification and communication plan development autonomously in production. |
Develop and maintain the company's corporate image and identity, which includes the use of logos and signage.
34CI 28–41 · exposure 25 · augmentation 75 · click for rater detail
Develop and maintain the company's corporate image and identity, which includes the use of logos and signage.
34| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Marketing and PR firms have adopted AI design assistants and content tools in pilot and partial-production settings, but strategic brand identity management remains largely human-driven. Adoption is middling: tools support workflows rather than replace the core task. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Marketing and communications functions are moderately fast adopters of generative AI design tools, though full brand identity management remains largely human-led with AI as a support tool. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI design and copywriting tools significantly assist PR managers by rapidly generating logo concepts, brand messaging alternatives, and visual asset drafts, which the manager then curates and refines. This assistive capability materially raises productivity while keeping the human in control of strategic decisions. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI significantly speeds up logo concepting, style guide drafting, and signage mockups, letting PR managers iterate faster while retaining final creative and strategic control. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can assist with logo generation, color palette design, and brand guideline documentation, the core responsibility of *developing* and *maintaining* corporate identity requires strategic business judgment, stakeholder alignment, and creative decisions that reflect organizational values. Current AI cannot reliably execute the full task end-to-end without substantial human direction and revision. |
| Task automatability | claude-sonnet-5 | 2/5 | AI can generate logo drafts and design assets, but developing and maintaining a coherent corporate identity requires ongoing strategic judgment, stakeholder alignment, and brand governance that current AI cannot autonomously manage end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Corporate identity and brand management carry legal and reputational consequences; stakeholders (executives, legal, marketing) typically require human accountability and sign-off. Liability for brand damage, trademark conflicts, and strategic misalignment creates organizational friction against full automation. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement, but trademark/legal review, executive approval, and brand consistency oversight create moderate organizational friction against pure automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI design tools reduce some costs (faster logo mockups, automated asset generation), but hiring a dedicated PR manager or design team remains necessary for strategic oversight. The all-in cost of AI tooling plus required human review and decision-making approaches or exceeds the cost of human expertise for this task. |
| Cost vs. human wage | claude-sonnet-5 | 3/5 | AI can cheaply generate visual drafts and mockups, but human oversight, strategic decision-making, and legal/trademark review keep overall costs comparable to a skilled human doing the full task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | Design tools with AI components exist (Canva, Adobe Firefly), but deploying them for cohesive corporate identity management requires human oversight; no mature product autonomously develops and maintains a company's brand identity across all touchpoints at production scale. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Design tools (Canva AI, Midjourney, logo generators) exist and are used for asset creation, but no deployed product manages full brand identity strategy and consistency across an organization reliably. |
Manage in-house communication courses.
34CI 30–38 · exposure 25 · augmentation 63 · click for rater detail
Manage in-house communication courses.
34| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | While some PR organizations use AI-assisted content and LMS tools, deep adoption of AI for full course management remains limited; most operations retain human managers for design and quality control rather than automation. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Corporate L&D and PR functions are increasingly using AI for content but adoption of AI-run internal training programs remains at pilot stage in most organizations. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can assist PR managers by drafting course materials, automating scheduling, tracking participation metrics, and suggesting content updates, meaningfully boosting productivity on administrative and content tasks while the manager retains pedagogical control. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI can significantly assist in creating training materials, presentations, quizzes, and communication guidelines, boosting the manager's efficiency in designing courses. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can generate course content and handle administrative scheduling, managing communication courses requires designing curricula, assessing learning outcomes, adapting to participant feedback, and making pedagogical decisions that currently demand human judgment. AI cannot end-to-end replace this with 50% time savings at equal quality. |
| Task automatability | claude-sonnet-5 | 2/5 | Designing and running in-house communication training involves interpersonal facilitation, organizational context, and adaptive coaching that current AI cannot fully replicate end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Public relations managers retain organizational authority over communication strategy and training outcomes, with some regulatory and brand-risk considerations around internal training quality. Adoption faces moderate friction from preference for human instructional judgment, though no strict licensing barrier exists. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement exists, but organizational preference for human-led training and internal culture fit create moderate friction against full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Current AI tools for course management assistance (LMS automation, content drafting) are moderately priced, but the human expertise required for effective educational program design and oversight means the total cost advantage is minimal or absent. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | While AI can cut content-creation time, human facilitation, coordination, and management overhead still require significant labor, keeping costs comparable rather than dramatically lower. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | AI tools exist for content generation and scheduling support, but no deployed product reliably manages the full scope of course management (curriculum design, instructor coordination, quality assurance, participant assessment) at production scale without significant human oversight. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | AI tools exist for generating training content or quizzes, but no deployed product manages full internal course delivery, scheduling, and facilitation reliably in production. |
Produce films and other video products, regulate their distribution, and operate film library.
31CI 30–32 · exposure 25 · augmentation 63 · click for rater detail
Produce films and other video products, regulate their distribution, and operate film library.
31| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Adoption of AI in video production remains at the pilot and experimental stage in most PR and media organizations; widespread displacement of production roles has not yet occurred. While tech-forward firms are testing generative video, the sector overall remains cautious about delegating creative direction and quality assurance to AI. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Media and PR sectors are adopting generative AI video tools moderately quickly, with pilots common in marketing content creation but full production/distribution workflows still human-led. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can meaningfully assist with video editing, subtitle generation, asset management, and initial drafts, raising a human producer's efficiency on technical tasks. However, creative vision, client alignment, and quality judgment remain human-centered, limiting augmentation to roughly half the production value chain. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI substantially speeds up video editing, generation of b-roll or drafts, and metadata tagging for library management, meaningfully boosting producer productivity while humans retain creative and legal oversight. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can generate basic video content and manage some technical aspects like formatting and metadata tagging, producing professional films requires creative direction, narrative judgment, and stakeholder management that current systems cannot execute end-to-end. Operating a film library involves policy decisions and relationship management beyond automation's current scope. |
| Task automatability | claude-sonnet-5 | 2/5 | AI video generation tools can assist with parts of production, but end-to-end producing, distribution regulation, and library operations require coordination, legal, and physical/organizational work beyond current AI capability at equal quality. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | PR managers producing films for corporate or organizational distribution face client expectations for human creative direction and brand alignment, creating organizational friction. Regulatory requirements around distribution (licensing, compliance) and liability for content quality introduce moderate friction, though no hard legal licensing barrier exists for the human producer role itself. |
| Adoption barriers | claude-sonnet-5 | 3/5 | Distribution regulation involves licensing, copyright, and contractual obligations that typically require human sign-off, though no strict professional licensure mandates a human for this specific task. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Current AI video generation and editing tools require significant human oversight, custom prompting, and integration work to match professional broadcast or PR standards. The all-in cost of AI-assisted production with quality control remains comparable to or higher than hiring production professionals for this work. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | AI can cut costs for some video editing/generation subtasks, but human producers still needed for creative direction, rights management, and distribution decisions, keeping overall cost comparable to human-led teams. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | AI tools exist for video editing, some generative video tasks, and basic asset management, but no deployed product reliably handles the full production workflow, distribution regulation, and library operations. Professional video production typically requires human creative oversight and client interaction that production systems have not yet standardized. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Products like Runway, Synthesia, and Adobe tools can generate/edit video segments, but no deployed product manages full production, distribution rights regulation, and library archiving as an integrated workflow reliably. |
Manage communications budgets.
29CI 25–32 · exposure 25 · augmentation 63 · click for rater detail
Manage communications budgets.
29| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | PR and communications departments have adopted analytics and dashboards slowly relative to finance; budget management remains largely manual or spreadsheet-based, with limited production AI deployment even among larger firms. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | PR and marketing departments are adopting AI analytics and budgeting tools moderately, with pilots for spend tracking and ROI analysis but limited full automation of budget decisions. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can meaningfully assist with budget tracking, spend alerts, trend analysis, and scenario modeling, helping managers optimize allocation and catch anomalies, though the core strategic decisions remain human-driven. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI can meaningfully assist with budget tracking, forecasting, scenario modeling, and identifying cost-saving opportunities, significantly boosting a manager's efficiency. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | AI can assist with budget forecasting, variance analysis, and reporting, but managing communications budgets requires strategic judgment about resource allocation across campaigns, vendor negotiations, and real-time reprioritization based on business context—tasks that demand human decision-making and accountability. |
| Task automatability | claude-sonnet-5 | 2/5 | Budget management involves judgment calls on resource allocation, negotiation, and strategic priorities that current AI cannot fully replicate end-to-end, though it can assist with tracking and analysis. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Public relations managers typically have fiduciary responsibility and sign-off authority over communications spending; organizational policies, audit trails, and stakeholder approval requirements create material friction against full automation of budget decisions. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing requirement, but organizational accountability for budget decisions and financial sign-off authority creates friction against full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Current AI solutions for budget management are expensive relative to the labor they displace, often requiring custom integration, ongoing training, and significant human oversight, making them comparable to or more costly than human budget managers in most organizations. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | AI tools can cheaply handle spreadsheet analysis and reporting, but the human oversight, vendor negotiation, and strategic reallocation still require a manager, keeping overall cost comparable to human labor. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | While financial software and analytics tools exist, no deployed AI system reliably manages an entire communications budget end-to-end; tools are largely advisory and require human oversight of allocation decisions, vendor relationships, and stakeholder sign-off. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Financial/budgeting software with AI features exists for tracking spend and forecasting, but no deployed product autonomously manages a PR budget's strategic allocation decisions reliably. |
Develop, implement, or maintain crisis communication plans.
29CI 25–32 · exposure 25 · augmentation 63 · click for rater detail
Develop, implement, or maintain crisis communication plans.
29| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Adoption of AI in PR is nascent; most organizations still rely on human-led crisis planning with occasional tool support. Crisis management remains a high-stakes, relationship-driven function where organizations have been slow to delegate end-to-end responsibility to AI. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | PR and corporate communications functions are adopting AI writing and monitoring tools at a moderate pace, with pilots for drafting and sentiment analysis common but full crisis-plan automation still rare. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can assist meaningfully by generating scenario templates, analyzing past crises, suggesting messaging frameworks, and automating routine documentation—helping PR managers work faster. However, the human typically remains essential for final judgment, stakeholder consultation, and legal/brand considerations. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI is quite useful for drafting template language, scenario brainstorming, monitoring media/sentiment, and quickly generating first-draft statements, meaningfully speeding up the human-led planning process. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can draft crisis communication templates, gather data, and suggest messaging strategies, the task requires understanding organizational context, stakeholder relationships, legal implications, and real-time judgment calls that demand human discretion. Current AI cannot independently develop or implement crisis plans end-to-end at the quality and accountability level required. |
| Task automatability | claude-sonnet-5 | 2/5 | Drafting components of a crisis communication plan is feasible for AI, but the task requires organizational judgment, stakeholder-specific risk assessment, and scenario anticipation tied to institutional context that current AI cannot fully replicate end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Crisis communication carries high reputational and legal stakes; organizations require human accountability, sign-off, and judgment. Regulatory expectations, liability concerns, and the need for a licensed or experienced communicator to oversee execution create substantial barriers to full automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing requirement exists, but liability exposure from a poorly handled crisis and the need for executive sign-off create meaningful organizational friction against fully automating this task. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI tools for crisis planning require integration, customization, and continuous human oversight to ensure appropriateness and legal compliance. The all-in cost approaches or exceeds that of having experienced PR managers perform or refine the work. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | While AI can cheaply generate draft language, the human cost of validating scenarios, aligning with legal/executive stakeholders, and maintaining currency of the plan keeps overall costs comparable to a skilled human doing this work. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | Products exist for crisis communication support (some PR platforms offer templates and scenario modeling), but no deployed AI system reliably performs the full scope of developing, implementing, and maintaining crisis plans independently. Existing tools require substantial human oversight and customization. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | AI writing tools can produce template crisis plans or draft statements, but no deployed product reliably develops and maintains a full, organization-specific crisis communication strategy in production without heavy human oversight. |
Formulate policies and procedures related to public information programs, working with public relations executives.
29CI 25–32 · exposure 25 · augmentation 63 · click for rater detail
Formulate policies and procedures related to public information programs, working with public relations executives.
29| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | PR departments are adopting AI for content and media monitoring, but not for core policy formulation. Adoption of AI in policy/governance tasks is lagging even within professional services; most organizations view policy-making as requiring experienced human judgment and maintain gatekeeping over this function. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | PR and corporate communications functions are adopting AI tools for drafting and research at a moderate pace, but strategic policy-setting remains largely human-led with pilots rather than production automation. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can meaningfully assist by summarizing best practices, organizing policy templates, identifying compliance gaps, and generating initial drafts that a manager then refines. However, augmentation is limited by the need for human strategic alignment and organizational context that AI cannot fully capture. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI can meaningfully assist by drafting policy language, summarizing precedents, analyzing media trends, and preparing briefing materials, substantially speeding up the human-led formulation process. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Formulating policies and procedures requires strategic judgment about organizational values, risk tolerance, and stakeholder needs that remain beyond reliable AI capability. While AI can draft templates or organize existing frameworks, the core work of deciding what policies should exist and how to align them with corporate strategy demands human decision-making. |
| Task automatability | claude-sonnet-5 | 2/5 | This is a strategic, judgment-heavy task involving negotiation and organizational politics among executives; AI can draft policy language but cannot own the formulation process end-to-end.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Organizational governance, legal compliance, and executive accountability create strong barriers: PR policies must be signed off by senior management and often legal review is required. These human sign-off requirements and the fiduciary responsibility of managers to set organizational direction create material friction against full automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing requirement, but organizational authority, accountability for public-facing policy, and need for executive consensus create real friction against full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI tools can reduce the labor cost of initial drafts and research, but a PR manager's oversight, revision, and final decision-making still dominates the cost structure. The all-in cost of AI assistance plus human supervision remains competitive with or more expensive than direct human policy development. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | Human executive time and relationship-based negotiation dominate this task's cost, so AI assistance only marginally reduces overall cost versus the human labor required for buy-in and judgment. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed product reliably performs end-to-end policy formulation for public relations programs. AI can assist with drafting and research, but production systems do not autonomously generate organizational policies that executives would deploy without substantial revision and human judgment. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | No deployed product autonomously formulates organizational PR policy in collaboration with executives; tools exist for drafting but not for the collaborative decision-making itself. |
Direct activities of external agencies, establishments, or departments that develop and implement communication strategies and information programs.
26CI 20–32 · exposure 20 · augmentation 75 · click for rater detail
Direct activities of external agencies, establishments, or departments that develop and implement communication strategies and information programs.
26| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | PR and communications sectors show modest AI adoption (analytics tools, content assistance) but lag in autonomous agent deployment; most use remains at pilot or partial-augmentation stage, with strategic direction decisions retained by humans due to reputational and fiduciary risk. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | PR and communications functions in professional services and corporate sectors are adopting AI tools moderately fast for content and analytics, but managerial direction of agencies remains largely untouched. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI offers substantial assistance in research, draft strategy development, competitive analysis, audience segmentation, and campaign performance monitoring, enabling PR managers to synthesize data and explore options faster while retaining strategic judgment and agency direction. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI tools can meaningfully assist by drafting briefs, summarizing campaign performance, and tracking deliverables, helping the manager oversee external activities more efficiently while retaining decision authority. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can assist with drafting communication strategies and analyzing audience data, the core task requires strategic direction, stakeholder negotiation, and real-time adaptation to organizational context that demands human judgment. Current systems cannot reliably replace the full portfolio of oversight, relationship management, and accountability inherent in directing external agencies. |
| Task automatability | claude-sonnet-5 | 2/5 | This is a managerial coordination and oversight task involving directing external parties, requiring judgment, relationship management, and accountability that current AI cannot autonomously perform end-to-end.9 |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Strong organizational and legal barriers exist: PR managers are accountable for external agency performance and brand risk, reputation liability falls on human decision-makers, and clients typically require direct human relationship management and sign-off on strategic direction. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing requirement exists, but organizational authority, accountability for vendor relationships, and reputational risk create meaningful friction against full AI substitution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI infrastructure for partial automation (content drafting, data analysis) remains costly relative to specific outputs, and human oversight of AI-directed external agencies would still require significant PR manager involvement, making the all-in cost favorable to human direction. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | AI can cheaply assist with drafting materials or tracking status, but the actual directing, negotiating, and evaluating of external agencies still requires costly human oversight, making all-in AI substitution not cheaper. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed product reliably manages relationships with external agencies or provides genuine strategic direction at scale. AI tools exist for content generation and analytics, but none demonstrate production-grade capability to independently direct multi-stakeholder communication programs in real organizations. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product manages or directs external agencies and departments on behalf of a PR manager; this remains a human managerial function with only ancillary AI tools for drafting or scheduling. |
Facilitate consumer relations or the relationship between parts of the company, such as the managers and employees, or different branch offices.
25CI 20–30 · exposure 20 · augmentation 50 · click for rater detail
Facilitate consumer relations or the relationship between parts of the company, such as the managers and employees, or different branch offices.
25| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | While some information and professional services sectors use AI for communications drafting, actual adoption of AI-driven relationship facilitation remains limited and experimental. Most organizations continue to rely on human PR managers for strategic relationship building and conflict resolution. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | PR and corporate communications functions use AI for content generation and monitoring, but adoption for internal mediation and relationship facilitation specifically remains nascent. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can usefully assist with drafting talking points, analyzing sentiment in feedback, scheduling, and managing routine communication workflows, improving human PR manager productivity. However, the core work of building trust and facilitating genuine dialogue remains human-centric. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI can help managers draft messaging, summarize sentiment, and prepare talking points for these relationship-building conversations, offering moderate productivity support. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can assist with routine internal communications and drafting relationship-building content, facilitating genuine consumer relations and internal manager-employee dynamics requires human judgment, emotional intelligence, and real-time negotiation that current systems cannot reliably perform end-to-end at equal quality. The core facilitation and mediation work remains difficult to automate. |
| Task automatability | claude-sonnet-5 | 2/5 | This task centers on relationship management, mediation, and trust-building across stakeholders, which requires in-person judgment, negotiation, and political sensitivity that current AI cannot autonomously execute end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Relationship facilitation and consumer representation carry implicit organizational trust requirements and liability exposure; there is strong organizational friction and stakeholder preference for human judgment in sensitive internal and consumer-facing matters. Regulatory and reputational risk also limits pure automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing requirement exists, but organizational trust, internal politics, and the need for a credible human intermediary create real friction against automating this interpersonal function. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI systems can reduce costs for routine surveys and templated communications, but the overhead of oversight, correction, and genuine relationship management integration means the all-in cost remains comparable to or higher than human PR managers for this task. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | AI could cheaply support communication drafting but cannot replace the manager's relational role, so the human cost remains dominant and total substitution is not cheaper overall. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | Some products exist for automating customer communication and feedback collection, but they handle only narrow aspects of relationship facilitation. Genuine mediation between organizational units and authentic consumer relationship-building still require human intermediaries in production systems, with AI playing only a support role. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs cross-organizational relationship facilitation or internal mediation reliably; existing tools only support communications drafting, not the interpersonal facilitation itself. |
Manage special events, such as sponsorship of races, parties introducing new products, or other activities the firm supports, to gain public attention through the media without advertising directly.
19CI 7–30 · exposure 13 · augmentation 63 · click for rater detail
Manage special events, such as sponsorship of races, parties introducing new products, or other activities the firm supports, to gain public attention through the media without advertising directly.
19| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | PR and events remain heavily relationship- and judgment-driven in practice. While adoption of AI-assisted drafting and scheduling tools is growing in corporate communications, active displacement of event managers is minimal. Most firms still treat event strategy and execution as distinctly human-led activities requiring senior judgment. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | PR and marketing functions are adopting AI for content and analytics, but event management and sponsorship activation remain largely manual with slow AI penetration into this specific sub-task. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can meaningfully assist PR managers by generating event concepts, drafting media invitations, researching attendee interests, managing timelines and vendor coordination, and analyzing post-event media coverage. These capabilities can raise a manager's productivity significantly while they retain strategic control and media relationship ownership. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI can assist with event planning logistics, drafting press materials, analyzing media coverage, and identifying sponsorship opportunities, meaningfully aiding the human planner without replacing execution. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can assist with elements like event logistics, scheduling, and media list generation, managing special events requires real-time decision-making, stakeholder negotiation, relationship management, and creative judgment that current systems cannot execute end-to-end. The human-facing and unpredictable nature of event management (vendor issues, press interaction, on-site problem-solving) prevents meaningful 50% time savings at equal quality. |
| Task automatability | claude-sonnet-5 | 1/5 | This task involves in-person event management, vendor coordination, live logistics, and relationship-based sponsorship activation that cannot be executed end-to-end by current AI systems.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Event management for brand reputation carries material liability and error costs; reputational damage from a poorly executed sponsorship or media event is significant. Organizations strongly prefer human judgment and accountability, and clients expect a named PR professional directing strategy. Organizational culture and risk aversion create substantial friction against full automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing requirement exists, but organizational reliance on human relationship-building, negotiation with media/sponsors, and on-site presence creates significant practical barriers to automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Current AI tools (chatbots, scheduling systems, content generators) are inexpensive per unit but require substantial human oversight and refinement for event management. The loaded cost of a PR manager remains lower than the combination of AI services, integration, and required human quality control for a high-stakes event. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | Executing physical events, coordinating vendors, and managing media presence on-site requires human labor and judgment that AI cannot substitute for at any meaningful cost advantage. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed product reliably manages the full lifecycle of special events autonomously. AI can draft press releases, identify media contacts, and organize logistics, but cannot negotiate with vendors, handle live media interactions, or make contextual decisions during execution at scale in production environments. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed AI product manages physical special events, sponsorships, or on-site activations; this remains fundamentally a human operational and relational task. |
Establish and maintain effective working relationships with clients, government officials, and media representatives and use these relationships to develop new business opportunities.
16CI 7–25 · exposure 13 · augmentation 75 · click for rater detail
Establish and maintain effective working relationships with clients, government officials, and media representatives and use these relationships to develop new business opportunities.
16| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | PR and communications are relationship-driven; adoption remains limited to email drafting and research assistance. Full automation of relationship and opportunity development has not achieved meaningful production deployment in professional services. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | While PR as a profession uses AI tools for content and monitoring, the core relationship-management and business-development function shows little displacement or agent-driven automation in practice. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI significantly assists PR managers by analyzing media sentiment, generating outreach templates, identifying relevant contacts and journalists, and tracking relationship history; these augmentations raise research and prospecting productivity even though humans lead relationship negotiations. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI can meaningfully assist by tracking media contacts, summarizing stakeholder communications, drafting outreach messages, and surfacing relationship-relevant insights, boosting a manager's efficiency while they remain central to the relationship. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can draft outreach messages and identify prospects, the core task requires sustained relationship-building, trust negotiation, and contextual judgment about client/official preferences that humans must ultimately execute. AI cannot authentically represent the organization or close deals independently. |
| Task automatability | claude-sonnet-5 | 1/5 | Building trust-based relationships with clients, officials, and media, and converting them into new business, is fundamentally interpersonal and relies on reputation, negotiation, and in-person rapport that AI cannot perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Strong organizational and client-expectation barriers exist: clients expect direct relationships with named human representatives, government and media contacts prefer human-to-human trust, and legal/reputational risk from fully automated business development is high. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Strong organizational and reputational barriers exist since clients and officials expect to deal with accountable, trusted human representatives, and business development relies on personal credibility and liability considerations. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI tools for prospecting and draft outreach cost relatively little per month, but the task still requires a full-time PR manager for credibility, negotiation, and relationship maintenance; the all-in cost of human supervision is comparable to retaining the human directly. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | AI cannot substitute for the human relationship function itself, so there is no meaningful cost comparison—the human is required and AI adds cost as a support tool rather than replacing labor. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | CRM and email-drafting tools exist, but no deployed system reliably performs the full relationship-development and opportunity-identification cycle without human decision-making and trust-building at every stage. Products assist but do not own the outcome. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product autonomously manages relationship-building or business development; these remain human-led activities with AI only playing a peripheral support role. |
Assign, supervise, and review the activities of public relations staff.
4CI 0–7 · exposure 0 · augmentation 38 · click for rater detail
Assign, supervise, and review the activities of public relations staff.
4| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | There is no meaningful adoption of AI for personnel management and supervision roles; this remains a purely human function even in digitally advanced sectors. No quantifiable displacement or adoption trend exists. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | While PR and marketing functions see growing AI tool adoption for content tasks, the specific managerial/supervisory function of overseeing staff activities sees minimal AI-driven displacement or workflow integration. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI can assist with scheduling, document drafting, or analytics on team output, but cannot meaningfully transform the core supervisory and evaluative judgment required. Augmentation is limited to administrative support tasks only. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI can help managers track team output, summarize staff activity reports, draft performance feedback, and flag scheduling conflicts, providing moderate productivity support to the supervisory process. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Assigning, supervising, and reviewing staff activities require nuanced human judgment about individual capabilities, interpersonal dynamics, and contextual decision-making that current AI systems cannot perform end-to-end. No AI system today can reliably manage personnel workflows at the autonomy and accountability level required. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a people-management task involving assigning work, evaluating performance, and providing supervisory judgment—AI cannot conduct performance reviews, resolve interpersonal issues, or exercise managerial authority end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Employment law, labor regulations, and organizational liability create hard barriers: only a human manager with direct authority and accountability can legally assign work, evaluate performance, and make employment decisions. These functions are legally bound to human discretion and responsibility. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Personnel management carries legal/HR responsibilities (performance reviews, accountability, employment law) that require a human manager with organizational authority and liability, creating strong structural barriers to automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Current AI systems cannot perform this task at all, making direct cost comparison moot; any attempted automation would require extensive human oversight, easily exceeding the loaded wage of a PR manager. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI substitute performing this managerial function, so no meaningful cost comparison exists—the human manager remains necessary and AI adds cost as a support tool rather than a replacement. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed product manages staff supervision and performance review independently; such systems exist only as narrow scheduling or task-tracking tools that lack the judgment and accountability required for genuine staff management. The responsibility and liability of personnel management remain exclusively human functions in practice. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product manages, assigns, and reviews human staff activities autonomously; workforce management tools only provide scheduling/tracking support, not supervisory judgment. |
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.