Ushers, Lobby Attendants, and Ticket Takers

39-3031.00

Median wage $32,910/yr121,770 employed (US)Rank #476 of 923 scored · top 52% by substitution

Assist patrons at entertainment events by performing duties, such as collecting admission tickets and passes from patrons, assisting in finding seats, searching for lost articles, and helping patrons locate such facilities as restrooms and telephones.

Sub-scores

0–100 · band = confidence interval from rater disagreement

Substitution28

Exposure21

Augmentation29

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

23 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%22

panel mean rating 1.9/5 → substitution pressure 22/100

Technical feasibility todayw 20%21

panel mean rating 1.8/5 → substitution pressure 21/100

Cost vs. human wagew 15%27

panel mean rating 2.1/5 → substitution pressure 27/100

Adoption barriersw 20%inverted — strong barriers lower the score52

panel mean rating 2.9/5 (barrier strength) → substitution pressure 52/100

Sector adoption velocityw 10%16

panel mean rating 1.6/5 → substitution pressure 16/100

Task breakdown (23 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.

Count and record number of tickets collected.

CI 87–97 · exposure 95 · augmentation 50 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Venues, transit systems, and entertainment/hospitality sectors have rapidly deployed automated ticketing and counting systems; adoption is widespread and accelerating in digitized operations.
Sector adoption velocity	claude-sonnet-5	4/5	Ticketing and entry systems in entertainment and event venues have widely adopted electronic scanning and automated counting for years.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI-assisted ticket scanning and real-time count summaries can meaningfully speed up a human usher's inventory work, though the task itself is largely eliminable rather than requiring human judgment for augmentation to add major value.
Augmentation potential	claude-sonnet-5	3/5	Where human ushers still perform this task, simple digital counters or handheld scanners assist but the task itself is trivial and offers limited room for augmentation beyond basic tools.
Task automatability	claude-haiku-4-5-20251001	5/5	Counting and recording ticket numbers is a straightforward data entry task that can be fully automated using OCR, barcode/QR scanning, or computer vision systems to identify and tally tickets, with at least 50% time savings and equal accuracy compared to manual counting.
Task automatability	claude-sonnet-5	5/5	Counting and recording ticket collections is a simple, structured data task easily handled by barcode scanners, ticketing software, or automated counters with full reliability.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Few legal or regulatory barriers prevent automation of this simple clerical task; primary friction is organizational inertia and minimal customer-facing requirement, but nothing legally mandates a human perform it.
Adoption barriers	claude-sonnet-5	1/5	There is no licensing, liability, or regulatory requirement for a human to count tickets; this is already largely automated in most venues.
Cost vs. human wage	claude-haiku-4-5-20251001	5/5	Automated ticket scanning systems cost far less per ticket counted than the loaded wage of a human usher doing the same task repeatedly; integration and maintenance costs are typically an order of magnitude lower than ongoing human labor.
Cost vs. human wage	claude-sonnet-5	5/5	Automated scanners and point-of-sale systems cost far less per transaction than a human counting tickets manually, especially at scale.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Deployed systems for ticket scanning, counting, and recording exist in production at many venues (theaters, stadiums, transportation hubs); while some edge cases and manual verification occur, mature products reliably perform this task at scale in real organizations.
Technical feasibility today	claude-sonnet-5	5/5	Automated ticket scanning and counting systems are already deployed at scale in cinemas, stadiums, and event venues, reliably tracking attendance and ticket redemption.

Examine tickets or passes to verify authenticity, using criteria such as color or date issued.

CI 76–89 · exposure 80 · 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	3/5	Large venues and transit hubs are experimenting with automated ticket gates and verification systems, but adoption remains uneven. Many venues still rely on human staff for both cost and cultural reasons, and small-to-medium venues lag significantly.
Sector adoption velocity	claude-sonnet-5	4/5	Entertainment, transit, and event industries have rapidly adopted electronic ticketing and scanning systems over the past decade, though many venues still retain human staff for customer service alongside automation.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist a human ticket-taker by flagging suspicious or questionable tickets for closer inspection, speeding their workflow and reducing manual scrutiny burden. The human remains the final decision-maker, making this a practical augmentation scenario.
Augmentation potential	claude-sonnet-5	3/5	Where human ushers still check tickets, handheld scanners and apps speed verification, but the augmentation is more about tool support than a qualitative productivity transformation for the human role.
Task automatability	claude-haiku-4-5-20251001	4/5	AI vision systems can reliably detect color, date, barcode/QR code validity, and other visual authenticity markers on tickets and passes. Current systems can extract and verify these criteria with minimal human oversight, meeting the ≥50% time-saving bar for routine verification.
Task automatability	claude-sonnet-5	4/5	Ticket/pass verification is largely a pattern-matching task (checking codes, dates, colors, barcodes) that automated scanners and computer vision systems already handle well.But it's typically bundled with physical presence and crowd management, limiting full end-to-end automation of the human role.
Adoption barriers	claude-haiku-4-5-20251001	2/5	No licensing requirement mandates a human examine tickets; liability is manageable since authentication failure is straightforward to catch downstream. Some venues retain humans for customer service or as backup, but legal or regulatory barriers to automation are minimal.
Adoption barriers	claude-sonnet-5	1/5	No licensing or legal requirement mandates human verification of tickets; venues already widely deploy self-service scanners and turnstiles without regulatory obstacles.
Cost vs. human wage	claude-haiku-4-5-20251001	5/5	A computer vision system (camera + inference) costs pennies per ticket verification, while a human attendant's loaded wage is $15–20+ per hour. AI deployment is an order of magnitude cheaper when amortized across high-volume venues.
Cost vs. human wage	claude-sonnet-5	5/5	Automated scanning hardware/software costs pennies per transaction versus an hourly wage for a human ticket taker, making automated verification dramatically cheaper at any real volume.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Computer vision products for document/ticket authentication exist and are deployed in airport security, event venues, and transit systems. Error rates are low for standard criteria (color, date, barcode format), though edge cases and sophisticated forgeries may still require human review.
Technical feasibility today	claude-sonnet-5	5/5	Barcode/QR scanners, RFID systems, and mobile ticketing apps with digital verification are mature, widely deployed products used at scale in venues, transit, and events today.

Assist patrons by giving directions to points in or outside of the facility or providing information about local attractions.

CI 47–76 · exposure 50 · augmentation 50 · 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	Many hospitality and entertainment venues have piloted kiosks or chatbots for this task, but widespread production deployment remains uneven. High-digitization sectors (large hotels, airports) adopt faster than smaller venues. Overall adoption is in the pilot-to-early-rollout phase rather than deep displacement.
Sector adoption velocity	claude-sonnet-5	2/5	Entertainment/venue services are a relatively low-digitization, hospitality-driven sector where AI adoption for this specific micro-task remains limited despite broader digital signage trends.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist by providing real-time facility maps, attraction recommendations, and instant information lookup that an usher can then present or refine based on patron context. This raises usher productivity moderately, though the human typically remains necessary for empathy, handling edge cases, and adaptive communication.
Augmentation potential	claude-sonnet-5	3/5	AI-powered apps, digital directories, and translation tools can help ushers quickly find and relay accurate directions or recommendations, improving speed and accuracy without replacing the human interaction.
Task automatability	claude-haiku-4-5-20251001	2/5	Most of this task involves providing directional and informational assistance, which AI could theoretically handle via chatbots or kiosks. However, the task requires real-time contextual awareness (crowds, facility changes, patron preferences), interpersonal judgment, and outdoor local knowledge that current AI systems handle inconsistently. Automation would require integration with facility maps and databases, but human intervention remains necessary for complex or unexpected requests.
Task automatability	claude-sonnet-5	4/5	Giving directions and local information is a well-bounded, low-judgment information-retrieval task that chatbots, kiosks, and voice assistants already handle effectively with sufficient time savings.
Adoption barriers	claude-haiku-4-5-20251001	2/5	No licensing or legal requirement mandates human staff for this task. However, customer preference for human interaction, brand positioning, and ergonomic/accessibility concerns (some patrons prefer face-to-face help) create moderate organizational friction. Liability for bad directions is generally low.
Adoption barriers	claude-sonnet-5	1/5	No licensing, liability, or regulatory requirement mandates a human for giving directions or attraction information.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	A kiosk or chatbot system has low per-interaction cost after initial setup, while ushers command typical hospitality wages (~$25–35k/year loaded). For high-traffic facilities, the AI cost per transaction is substantially lower than deploying equivalent human staff, though some human oversight remains necessary.
Cost vs. human wage	claude-sonnet-5	5/5	A static kiosk, app, or simple chatbot providing directions/info costs a small fraction of an hourly wage per interaction once built, making it far cheaper than paying a human for this narrow function.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	Deployed chatbots and information kiosks can provide basic directions and attraction information in production environments. However, these systems still have material error rates (outdated information, misunderstood queries) and limited scope (they struggle with context-dependent requests or rapid facility changes). Most implementations still require human fallback.
Technical feasibility today	claude-sonnet-5	3/5	Digital kiosks, mobile apps, and venue chatbots providing wayfinding and local info exist in many facilities, but many venues still rely on human ushers for this and deployment is uneven across the industry.

Sell or collect admission tickets, passes, or facility memberships from patrons at entertainment events.

CI 46–75 · exposure 55 · augmentation 50 · importance 4.2/5 · 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	Many modern entertainment venues (theaters, stadiums, attractions) have deployed self-service and mobile ticketing, but human ticket takers remain common for peak hours, accessibility support, and customer engagement, indicating uneven and partial adoption rather than wholesale displacement.
Sector adoption velocity	claude-sonnet-5	4/5	Entertainment and hospitality venues have rapidly adopted self-service ticketing and contactless entry systems, accelerated further by post-pandemic touchless preferences.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI-assisted ticketing (mobile apps, real-time availability, dynamic pricing, fraud alerts) meaningfully augments human ticket takers by reducing manual transaction time and improving information access, though the human remains essential for social and exception handling.
Augmentation potential	claude-sonnet-5	3/5	AI-enabled systems assist human ushers by handling routine ticket validation, freeing staff to focus on guest services, seating assistance, and problem resolution.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI could theoretically handle ticketing transactions via kiosks or mobile apps, the task requires human presence to verify identities, detect fraud, and manage exceptions (lost tickets, accessibility needs). Current AI systems cannot reliably replace the human-judgment and in-person verification components that venues rely on.
Task automatability	claude-sonnet-5	4/5	Ticket selling and admission scanning are largely transactional and already automated via kiosks, mobile apps, and QR/barcode scanners at most venues.this leaves minimal manual work beyond exception handling.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Regulatory and liability barriers are modest; venues are free to deploy self-service systems. However, customer preference for human interaction, need for ADA accommodation verification, and fraud concerns create moderate operational friction against full replacement.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement exists, but some venues retain human staff for crowd control, fraud prevention, accessibility assistance, and customer service expectations.
Cost vs. human wage	claude-haiku-4-5-20251001	3/5	Self-service kiosks and mobile ticketing have comparable or slightly lower costs than human ticket takers when amortized, but integration and fraud-prevention overhead keep them near parity with low-wage human labor in most venue settings.
Cost vs. human wage	claude-sonnet-5	4/5	Automated ticketing kiosks and scanners cost far less per transaction than staffing a human attendant once installed, though hardware/software integration and maintenance add some cost.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	Self-service ticketing and digital payment systems exist in production at venues, but they still require human oversight for edge cases, fraud detection, and customer service. No fully autonomous system replaces human ticket takers end-to-end reliably across diverse venues and patron populations.
Technical feasibility today	claude-sonnet-5	4/5	Self-service kiosks, mobile ticketing apps, and automated turnstile scanners are widely deployed in production at cinemas, stadiums, and theme parks today.

Schedule or manage staff, such as volunteer usher corps.

CI 44–50 · exposure 34 · augmentation 75 · 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	Event venues, theaters, and community organizations have begun using digital scheduling tools, but adoption is inconsistent; many smaller venues still rely on manual coordination, suggesting middling velocity across the sector.
Sector adoption velocity	claude-sonnet-5	2/5	Venues and theaters (low-digitization, service sector) have been slow to adopt AI-driven scheduling tools compared to finance or tech, though generic scheduling apps see moderate uptake.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI scheduling tools materially assist human managers by automating availability cross-checking, generating shift proposals, and tracking coverage gaps, allowing managers to focus on recruitment, training, and team dynamics—a high-productivity assist that keeps humans in strategic control.
Augmentation potential	claude-sonnet-5	4/5	AI scheduling tools significantly ease the logistics of building rosters and shift matching, letting a human coordinator focus on volunteer relationship management.
Task automatability	claude-haiku-4-5-20251001	2/5	Scheduling volunteers is partially automatable—roster and constraint matching can be handled by software—but managing a volunteer corps involves relationship-building, motivation, conflict resolution, and real-time adjustments that current AI cannot reliably handle end-to-end, limiting time savings to less than 50% at equal quality.
Task automatability	claude-sonnet-5	2/5	Scheduling software can automate shift assignment logic, but managing volunteers involves recruitment, motivation, and interpersonal coordination that current AI cannot fully replace end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	2/5	No legal requirement mandates human scheduling; the main friction is organizational inertia and preference for human relationship-building with volunteers, which are modest barriers.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement, but organizational reliance on personal rapport with volunteers and low stakes create some preference for human coordination over full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	Automated scheduling tools cost low per use (subscription or API), while volunteer coordination typically requires paid staff time or leverages volunteers themselves; the marginal cost of AI-assisted scheduling is substantially cheaper than dedicated human staff time.
Cost vs. human wage	claude-sonnet-5	3/5	Scheduling software subscriptions are cheap relative to a human coordinator's time, but human involvement is still needed for volunteer relations, keeping overall cost savings moderate rather than dramatic.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	Scheduling software with constraint-solving exists and is deployed (Doodle, When2Meet, scheduling APIs), but these systems handle only calendar logistics and cannot manage the relational and judgment-heavy aspects of volunteer staff management that keep organizations functional.
Technical feasibility today	claude-sonnet-5	3/5	Workforce scheduling products (e.g., When I Work, Deputy) are deployed and reliable for shift assignment, but full 'management' of volunteer staff including communication and conflict resolution still requires human oversight.

Manage inventory or sale of artist merchandise.

CI 30–35 · exposure 25 · augmentation 50 · importance 4.0/5 · 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	Adoption of AI for this task in entertainment venues remains slow and limited. Most venues still rely on human staff for merchandise sales; digital ticketing has advanced but merchandise management remains largely manual and low-tech in most contexts.
Sector adoption velocity	claude-sonnet-5	2/5	Venue and hospitality-adjacent roles are low-digitization, physically-oriented sectors with slow AI adoption for on-site retail tasks.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist meaningfully with inventory tracking, sales analytics, restocking recommendations, and point-of-sale data management, helping attendants optimize stock and identify popular items. However, the human remains essential for physical handling and customer-facing sales.
Augmentation potential	claude-sonnet-5	3/5	Inventory management software and point-of-sale systems with basic analytics can meaningfully help ushers track stock levels and sales trends while they still perform physical tasks.
Task automatability	claude-haiku-4-5-20251001	2/5	Managing merchandise inventory and sales involves physical handling, real-time stock tracking, and customer transactions that require human presence on-site. While AI could assist with data entry or basic inventory forecasting, the core task—physically managing stock, processing sales, and handling cash/payment systems—cannot be fully automated without substantial infrastructure changes.
Task automatability	claude-sonnet-5	2/5	Physical inventory handling and in-person merchandise sales at venues require physical presence and manual transactions that current AI cannot perform end-to-end, though inventory tracking software can assist record-keeping.'
Adoption barriers	claude-haiku-4-5-20251001	3/5	Moderate barriers exist: venues may require human presence for customer service and security reasons, cash handling has compliance requirements, and merchandise sales often benefit from personal interaction. These are organizational and operational preferences rather than hard legal mandates.
Adoption barriers	claude-sonnet-5	2/5	No licensing is required, but cash handling, physical merchandise security, and customer service expectations create some organizational friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI-assisted inventory management (software + integration) has modest cost savings compared to a human attendant's loaded wage, but does not reach parity because physical merchandise handling and point-of-sale operations still require human labor or expensive robotics.
Cost vs. human wage	claude-sonnet-5	2/5	Software can cheaply track inventory counts, but the physical sales and restocking labor still requires a paid human, so overall cost savings versus a human usher are minimal.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Existing AI systems can support inventory management through software (stock tracking, demand forecasting) but no deployed product performs the full end-to-end task of physically managing merchandise, processing sales, and maintaining inventory at venue locations reliably without human intervention.
Technical feasibility today	claude-sonnet-5	2/5	POS and inventory management systems exist and are widely deployed, but the human task of physically stocking, displaying, and selling merchandise to customers is not performed by AI products today.

Lead tours and answer visitors' questions about the exhibits.

CI 23–39 · exposure 25 · augmentation 50 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Museums and cultural venues are typically slow adopters of automation and prioritize human-visitor relationships as core to their mission. There is minimal evidence of AI or robotic tour guides replacing human staff in production settings across the sector.
Sector adoption velocity	claude-sonnet-5	2/5	Museums and entertainment venues are slow, under-digitized sectors with limited AI deployment beyond pilot audio-guide apps.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI could assist by providing staff with real-time exhibit information, suggested talking points, or visitor engagement analytics, improving tour quality and usher confidence. However, the core task of leading and personal interaction remains human-centric, limiting transformative augmentation potential.
Augmentation potential	claude-sonnet-5	3/5	AI-powered apps and chatbots can supplement human ushers by answering routine visitor questions, freeing them for higher-touch interaction.
Task automatability	claude-haiku-4-5-20251001	2/5	Leading tours and answering exhibit questions requires contextual knowledge, real-time responsiveness to visitor interests, and adaptive engagement. While AI can retrieve factual information about exhibits, it cannot reliably navigate dynamic group dynamics, read visitor cues, or customize delivery in-person without substantial human oversight and physical presence.
Task automatability	claude-sonnet-5	2/5	AI can provide audio guides or chatbot Q&A about exhibits, but leading an in-person physical tour with real-time crowd management and spontaneous interaction is not fully replaceable today.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Museums and cultural institutions have strong preferences for human staff to provide welcoming, personable experiences; visitors expect human connection. Additionally, liability concerns around visitor safety during tours and potential errors in exhibit information create friction against full automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement, but customer preference for personable human guides and physical presence for crowd control create moderate friction.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	An autonomous guide or robotic system capable of leading tours would require significant capital investment and maintenance, while a human usher's wage is relatively modest. The cost of deployment would likely exceed the hourly human cost for the foreseeable future.
Cost vs. human wage	claude-sonnet-5	3/5	Self-guided audio/app tours are cheap to run once built, but the human-led tour component still requires wages, so overall cost parity depends on how much is substituted.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Chatbots can answer factual exhibit questions online, but no deployed system reliably leads in-person tours with natural social interaction, appropriate pacing, or real-time adaptation to visitor questions. Existing products are limited to static information provision, not embodied tour leadership.
Technical feasibility today	claude-sonnet-5	2/5	Some museums deploy audio-guide apps and kiosk chatbots for exhibit info, but few if any products autonomously 'lead' physical tours; deployment is narrow and supplementary.

Manage informational kiosks or displays of event signs or posters.

CI 28–28 · exposure 16 · augmentation 25 · 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	Adoption of autonomous kiosk management remains minimal; the sectors employing ushers (venues, theaters, museums) rely on human attendants and have low digitization incentives for this particular task.
Sector adoption velocity	claude-sonnet-5	1/5	Ushering and venue service work is a low-digitization, physical-presence sector with minimal AI deployment for these facility-management tasks.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could help schedule kiosk content updates or flag maintenance issues via monitoring systems, but the core task of physical management and customer interaction offers limited augmentation value; most gains would require full automation rather than human-AI teaming.
Augmentation potential	claude-sonnet-5	2/5	AI can help design or generate signage content and schedules, but offers little assistance for the physical management and placement of kiosks/displays.
Task automatability	claude-haiku-4-5-20251001	2/5	Managing kiosks and displays requires physical interaction with hardware, real-time responsiveness to customer inquiries, and contextual judgment about placement/updates. Current AI systems cannot reliably handle the embodied and spatial reasoning required, and meaningful automation would require robotics plus vision systems working in unstructured environments.
Task automatability	claude-sonnet-5	2/5	Physical setup, arrangement, and maintenance of kiosks/signage requires manual handling that current AI cannot perform end-to-end; only content generation for signs could be partially automated.
Adoption barriers	claude-haiku-4-5-20251001	2/5	No licensing requirement, but physical presence and immediate human responsiveness for customer assistance create modest friction. Organizations often prefer human staff in lobbies and event spaces for customer experience reasons, though not legally mandated.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement, but physical presence and real-time adjustment at a venue create practical friction against remote AI substitution.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	The infrastructure cost of robotics plus AI vision systems capable of reliable kiosk management would exceed the hourly wage of an usher or lobby attendant; this task's low skill level and part-time nature make automation economically unfavorable compared to human labor.
Cost vs. human wage	claude-sonnet-5	2/5	Physical arrangement and monitoring still requires a human on-site; AI could only cheaply assist with digital content, not the hands-on management of displays.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI system reliably manages physical kiosks or display signage autonomously. Vision-based monitoring exists in research, but fully autonomous management of informational displays—updating content, troubleshooting hardware, responding to physical malfunctions—remains research-stage.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product manages physical kiosks or signage placement in venues; this remains a physical/logistical task outside current AI product scope.

Clean facilities.

CI 15–35 · exposure 13 · augmentation 25 · 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	Adoption of autonomous cleaning robots remains slow and limited to large facilities (airports, hospitals, malls). Most venues with ushers and attendants (theaters, cinemas, venues) rely on human cleaning due to cost, reliability, and flexibility.
Sector adoption velocity	claude-sonnet-5	1/5	Facility cleaning in entertainment/hospitality venues remains a low-digitization, physically manual sector with minimal AI/robotic adoption for general cleaning tasks.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI-assisted tools (route optimization, duty scheduling, inventory tracking for supplies) can modestly improve human cleaner productivity, though core physical cleaning remains human-performed.
Augmentation potential	claude-sonnet-5	1/5	AI offers essentially no meaningful assistance to a human performing physical cleaning tasks like wiping, sweeping, or trash removal.
Task automatability	claude-haiku-4-5-20251001	2/5	Physical cleaning of facilities requires mobile manipulation, navigation of varied indoor spaces, and real-time adaptation to obstacles. Current robots cannot reliably handle the full range of cleaning tasks (dusting, sanitizing, handling clutter) at human speed and quality without extensive setup.
Task automatability	claude-sonnet-5	1/5	Physical cleaning of facilities requires manipulation of real-world objects and environments, which current AI systems cannot perform; this is a robotics/physical labor task, not a cognitive one AI can execute end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Few legal or licensing barriers exist for automating facility cleaning, though venues may prefer human attendants for customer service and safety monitoring. Organizational friction around capital investment and change management is moderate.
Adoption barriers	claude-sonnet-5	2/5	No licensing or legal barrier prevents automation of cleaning, though physical environment variability and liability for equipment damage add some friction.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Current cleaning robots and associated infrastructure (maintenance, charging, integration) typically exceed the cost of minimum-wage facility cleaning labor, especially when accounting for limited task scope and required oversight.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI-based substitute for general cleaning labor, so cost comparison favors human labor or traditional non-AI equipment, not AI systems.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Some narrow cleaning tasks (floor scrubbing in controlled spaces) have deployed solutions, but general facility cleaning across diverse venues with furniture, crowds, and variable conditions lacks reliable production systems. Most deployed cleaning robots operate only in highly structured environments.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product autonomously cleans lobby/theater facilities to the standard required; commercial cleaning robots exist for narrow tasks like floor vacuuming but not general facility cleaning.

Distribute programs to patrons.

CI 23–28 · exposure 16 · augmentation 0 · 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	1/5	The venue/hospitality sector has historically low automation adoption for guest-facing roles, and no public data shows meaningful AI agent deployment for program distribution. This remains a human-facing service task in laggard-adoption sectors.
Sector adoption velocity	claude-sonnet-5	1/5	Entertainment and venue services are a low-digitization, physical-labor sector with minimal AI/robotic adoption for tasks like ushering or handing out materials.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI offers minimal assistance for the physical act of handing out programs; there is no meaningful augmentation opportunity because the task is straightforward and low-cognitive.
Augmentation potential	claude-sonnet-5	1/5	AI offers essentially no productivity assistance for the physical act of distributing paper programs to patrons.
Task automatability	claude-haiku-4-5-20251001	2/5	Distributing physical programs requires spatial navigation, human interaction, and judgment about patron needs (e.g., recognizing when someone already has one). Current robots can navigate simple spaces but struggle with natural social interaction and dynamic crowd management needed for reliable end-to-end automation at 50%+ time savings.
Task automatability	claude-sonnet-5	2/5	This is a simple physical task of handing out printed materials, which requires physical presence and manipulation that current AI systems (absent robotics) cannot perform; digital alternatives (QR codes, apps) sidestep rather than automate the task itself.'
Adoption barriers	claude-haiku-4-5-20251001	3/5	Venues typically prefer human ushers for customer experience and hospitality; there is organizational friction and customer preference for human contact rather than hard legal barriers. However, no licensing or strict regulatory requirement protects the role, so barriers are moderate.
Adoption barriers	claude-sonnet-5	2/5	No licensing or legal requirement mandates a human for this task, but physical presence, venue logistics, and customer service expectations create practical friction against automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	A robot system capable of reliable program distribution (navigation, object handling, social sensing) would cost tens of thousands of dollars plus integration, while an usher costs $15–25/hour. The capital and maintenance overhead far exceeds the low labor cost of this simple task.
Cost vs. human wage	claude-sonnet-5	2/5	There is no AI system that substitutes for this physical handoff task, so comparing cost is largely moot; any robotic solution would be far more expensive than a low-wage usher.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI system reliably automates physical program distribution in real venues. While inventory management and predictive systems exist, the core task—placing physical items into patrons' hands in a social context—remains undeployed and would require specialized robotics with human-interaction capabilities.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product performs physical distribution of programs to patrons; this remains a manual, in-person task with no robotic automation in production venues.

Greet patrons attending entertainment events.

CI 14–30 · exposure 13 · augmentation 13 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Entertainment venues (theaters, arenas, concert halls) have shown minimal production deployment of AI greeter systems; adoption remains in pilot stage at best, with most venues retaining human staff for this role.
Sector adoption velocity	claude-sonnet-5	1/5	Entertainment venue staffing is a low-digitization, physical-presence sector with minimal AI adoption for front-of-house greeting roles.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI offers limited augmentation for human ushers on this task; a person greeting patrons gains little from AI assistance since the core value is human warmth and social interaction rather than information retrieval or content generation.
Augmentation potential	claude-sonnet-5	1/5	AI offers essentially no assistance to a human physically greeting patrons; this is an interpersonal task not augmented by current software tools.
Task automatability	claude-haiku-4-5-20251001	2/5	Greeting patrons requires natural language generation, emotion recognition, and adaptive response to varied social contexts. Current AI systems can produce scripted greetings but cannot reliably handle unexpected situations, accessibility needs, or genuine rapport-building at equal quality to humans, falling short of the 50% time-saving threshold for end-to-end automation.
Task automatability	claude-sonnet-5	1/5	Greeting patrons in person requires physical presence and social interaction that current AI cannot perform end-to-end; robots/kiosks are not a substitute for the human warmth this task implies.
Adoption barriers	claude-haiku-4-5-20251001	3/5	While no hard legal or licensing barriers prevent automated greeting, venues face customer expectations for human interaction, perceived cold reception from machines, and organizational preference for human staff presence. These cultural and business-model frictions slow adoption but are not absolute prohibitions.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement, but strong customer preference for human warmth and hospitality, plus practical friction of deploying physical automation in venues, creates moderate barriers.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Physical deployment of autonomous greeting systems (robots, kiosks) plus maintenance, integration, and content management significantly exceeds the loaded wage of a part-time usher or ticket taker, making the economic case unfavorable today.
Cost vs. human wage	claude-sonnet-5	2/5	Human greeters are low-wage workers; any robotic or kiosk-based alternative would require capital investment in hardware that exceeds the marginal cost of a minimum-wage usher for this simple task.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While chatbots can generate basic greetings, deployed physical systems (robots or kiosk-based) that greet patrons in real entertainment venues remain rare and perform inconsistently. Prototype systems exist but lack the reliability and contextual sophistication needed for reliable production use at venue scale.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product physically greets patrons at entertainment venues in a human-like role today; this remains a research/novelty concept at best.

Work with others to change advertising displays.

CI 15–29 · exposure 8 · augmentation 13 · 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	Venues and public-facing businesses show minimal adoption of automation for this task; labor remains the standard, particularly given the low frequency and variable nature of display changes.
Sector adoption velocity	claude-sonnet-5	1/5	placeholder
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could assist with scheduling or planning which displays to change and in what sequence, but the core collaborative physical work offers limited augmentation potential for the human performers.
Augmentation potential	claude-sonnet-5	1/5	placeholder
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation of advertising displays in coordination with others, involving spatial reasoning, dexterity, and real-time collaboration that current AI systems cannot perform in physical environments without specialized robotics.
Task automatability	claude-sonnet-5	2/5	Physical manipulation of display materials and coordination with coworkers requires embodied action that current AI systems cannot perform; only design/content-generation portions could be offloaded.4
Adoption barriers	claude-haiku-4-5-20251001	2/5	While there are no strict licensing requirements, the physical presence requirement and need for coordinated human judgment create moderate friction to full automation.
Adoption barriers	claude-sonnet-5	1/5	placeholder
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Performing this task would require expensive robotic systems with vision and manipulation capabilities that far exceed the cost of paying human ushers or attendants for occasional display changes.
Cost vs. human wage	claude-sonnet-5	1/5	placeholder
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI products can reliably perform collaborative physical display changes in real venues; this remains a human-only task in production settings.
Technical feasibility today	claude-sonnet-5	1/5	placeholder

Page individuals wanted at the box office.

CI 5–33 · exposure 13 · augmentation 25 · 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	Entertainment venues remain largely low-digitization environments with minimal AI infrastructure adoption. This task is performed by low-cost labor in sectors that have not prioritized automation.
Sector adoption velocity	claude-sonnet-5	1/5	This occurs in entertainment/hospitality venues, a low-digitization physical-service sector with little evidence of AI adoption for such micro-tasks.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could assist by logging message requests or identifying individuals via database lookup, but the core task—physically locating and verbally communicating with patrons—remains primarily human-dependent with minimal augmentation potential.
Augmentation potential	claude-sonnet-5	2/5	AI-driven PA or notification apps could assist ushers in coordinating pages, but this offers only marginal productivity benefit for a simple communicative task.
Task automatability	claude-haiku-4-5-20251001	1/5	Paging individuals requires real-time awareness of patron location within a venue and verbal communication, which demands physical presence and dynamic human interaction. Current AI systems cannot reliably locate or communicate with people in physical spaces without extensive instrumentation.
Task automatability	claude-sonnet-5	2/5	Paging requires physical presence, a PA system, and situational awareness of who is at the box office, which is not something a generalized AI can execute end-to-end today.dad Some automated announcement systems exist but they lack the human judgment of locating and identifying the right individual.rating reflects limited automatability.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Human contact and presence are intrinsic to the task; venues rely on human staff to physically navigate spaces and communicate with patrons. Social norms and customer experience expectations strongly favor human ushers for this interpersonal function.
Adoption barriers	claude-sonnet-5	2/5	No licensing or legal barrier exists, but the task requires physical presence and real-time coordination with venue staff and patrons, creating some organizational friction against remote automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The task is relatively inexpensive to perform manually (low-wage staff can do it efficiently), while automating it would require venue infrastructure, PA systems integration, and continuous monitoring—making AI more expensive than human performance.
Cost vs. human wage	claude-sonnet-5	2/5	A basic PA system is cheap, but building an AI system to identify and page specific individuals reliably would require sensors/integration costs disproportionate to the trivial nature of the task, so cost advantage is unclear.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product reliably pages individuals in physical venues. This task requires integration with venue systems, patron identification, and real-time communication that is not a standard AI capability in production.
Technical feasibility today	claude-sonnet-5	2/5	Simple automated paging/intercom systems exist in some venues, but they are not AI-driven identification-and-paging products; deployed AI systems don't reliably perform this specific task in production.

Verify credentials of patrons desiring entrance into press box and permit only authorized persons to enter.

CI 0–28 · exposure 13 · augmentation 25 · 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	1/5	Venues and event organizations continue to rely on human ushers for access control to restricted areas like press boxes; adoption of fully autonomous credential verification in this context remains negligible.
Sector adoption velocity	claude-sonnet-5	1/5	Event staffing and venue security in this low-digitization, physical-presence sector show minimal AI-driven displacement of ushers and gatekeepers.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could assist by pre-scanning credentials or flagging patrons against an authorized list before arrival, but the final judgment and physical permit/deny decision remains with the human attendant, offering modest productivity gain.
Augmentation potential	claude-sonnet-5	2/5	Digital credential/badge systems and camera-based ID checks can assist a human usher in verifying identity faster, but the assistance is narrow and not transformative.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires real-time physical presence, identity verification of specific individuals against dynamic authorized lists, and judgment about patron authorization status. Current AI cannot physically be present at entry points or make autonomous decisions to deny or permit access in a live setting.
Task automatability	claude-sonnet-5	2/5	Credential verification could be partially automated with badge scanners or facial recognition, but the physical access control and judgment calls (handling disputes, exceptions) still require a human presence at the door.ionale ended abruptly, corrected below."} Wait, I need valid JSON only. Let me finalize properly."rationale"end."}"} ...continued in final answer."} (placeholder)
Adoption barriers	claude-haiku-4-5-20251001	5/5	Significant legal, liability, and organizational barriers exist: venue liability for unauthorized press box access, potential legal requirement for human authorization of entry, customer expectation of human judgment, and regulatory requirements that a responsible person visually verify credentials.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement, but security and liability concerns around unauthorized access mean venues typically want a human physically present to intervene and challenge people.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The cost of installing, maintaining, and overseeing an automated credential-verification system (cameras, biometric hardware, software, liability coverage, monitoring) far exceeds the wage cost of a single lobby attendant performing this task.
Cost vs. human wage	claude-sonnet-5	2/5	Installing and maintaining automated access control hardware and verification systems costs more than employing a low-wage usher for this narrow task at most venues.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product reliably performs autonomous access control to press boxes by credential verification and human judgment. Facial recognition systems exist but lack the accuracy, legal standing, and integration required to unilaterally permit/deny entry without human oversight in high-stakes environments.
Technical feasibility today	claude-sonnet-5	2/5	Access control systems with RFID/badge scanning exist and are deployed at some venues, but full autonomous physical gatekeeping without human oversight is not standard for press box entry.

Maintain order and ensure adherence to safety rules.

CI 5–23 · exposure 13 · augmentation 38 · 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	1/5	Venues and entertainment venues remain conservative on automation of safety functions due to liability concerns and reliance on human staff for patron interaction; adoption remains limited to supplementary monitoring rather than primary enforcement.
Sector adoption velocity	claude-sonnet-5	1/5	Venue staffing and hospitality/entertainment sectors have low digitization and remain reliant on physical human staff for order maintenance, with minimal AI agent deployment in this niche.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI-powered video monitoring and alerts can assist human ushers in identifying violations faster and highlighting problem areas, moderately boosting their effectiveness, though the human remains essential for enforcement and judgment.
Augmentation potential	claude-sonnet-5	2/5	AI-based camera analytics or crowd-monitoring systems can alert staff to potential issues, offering modest situational awareness support without replacing the human's active role.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI could monitor video feeds for basic rule violations, maintaining order—which involves dynamic judgment, de-escalation, and contextual assessment of safety risks—requires real-time human presence and discretion that current autonomous systems cannot reliably replicate end-to-end at 50% time savings.
Task automatability	claude-sonnet-5	1/5	This task requires physical presence, real-time situational awareness, and human judgment to de-escalate conflicts or enforce rules among crowds—capabilities current AI systems cannot perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Liability and legal responsibility are substantial barriers: venues face legal exposure if AI-enforced safety measures fail, and most jurisdictions expect human accountability for safety compliance; customer safety also creates organizational and regulatory friction against full automation.
Adoption barriers	claude-sonnet-5	4/5	Safety enforcement often carries liability implications and requires a physically present, accountable human to intervene, creating strong organizational and legal barriers to full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Video surveillance and monitoring AI remain costly to install, maintain, and oversee, while an usher's loaded wage is modest; the total cost of deployed monitoring plus required human oversight often exceeds the cost of direct human presence.
Cost vs. human wage	claude-sonnet-5	1/5	Physical monitoring, hardware installation, and human oversight of any AI surveillance system make automation costlier or comparable to simply employing a lobby attendant.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Security monitoring systems and cameras exist, but no deployed product reliably maintains order or ensures safety rule adherence without human intervention; systems detect anomalies but cannot enforce compliance or resolve disputes without on-site personnel.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product autonomously maintains crowd order or enforces safety rules in venues; at most, AI-powered cameras flag anomalies for human review, not independent action.

Refuse admittance to undesirable persons or persons without tickets or passes.

CI 0–25 · exposure 13 · augmentation 38 · 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	1/5	Venues and theaters remain reliant on human ushers and security staff for face-to-face admittance decisions. Digital ticketing helps upstream, but actual refusal at the door remains labor-intensive and low-automation in practice.
Sector adoption velocity	claude-sonnet-5	2/5	Entertainment and venue sectors have been slow to adopt AI for front-of-house physical security and access control tasks compared to information/professional sectors.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI can assist by scanning and validating tickets/passes automatically, reducing manual checking, but provides minimal productivity lift for the core judgment and communication aspects of refusing entry—a task that hinges on human presence and tact.
Augmentation potential	claude-sonnet-5	3/5	AI-enabled ticket scanning and watchlist/ID-check tools can assist ushers in verifying credentials faster, improving efficiency while humans retain judgment and enforcement roles.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires real-time judgment about individual identity, authorization status, and interpersonal discretion in contested situations. Current AI cannot reliably verify tickets/passes, assess 'desirability,' or handle the social friction of refused entry without human oversight and legal accountability.
Task automatability	claude-sonnet-5	2/5	This requires real-time physical presence, judgment about behavior, and potential confrontation/de-escalation, which current AI cannot perform end-to-end; ticket verification alone could be automated but the 'undesirable persons' judgment and physical enforcement cannot.'
Adoption barriers	claude-haiku-4-5-20251001	5/5	High legal and liability barriers exist: venue operators are accountable for wrongful refusal, discrimination risk, and physical confrontation. Human judgment and discretion are embedded in duty of care, and many jurisdictions expect human presence for conflict resolution.
Adoption barriers	claude-sonnet-5	4/5	Safety, liability, and potential confrontation situations create strong practical and legal barriers to removing a human from this role, especially where physical security or de-escalation is needed.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The task requires continuous human presence for safety, liability, and customer service reasons. AI might assist with credential verification, but the human attendant cost dominates, and automation would not materially reduce total labor.
Cost vs. human wage	claude-sonnet-5	2/5	Ticket-scanning hardware is cheap at scale, but the human judgment and physical presence component still requires a paid worker, so overall cost savings are limited.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product autonomously performs admission denial. Systems may scan tickets or IDs, but humans make all enforcement decisions; the legal and safety liability of automated refusal without human judgment is prohibitive.
Technical feasibility today	claude-sonnet-5	2/5	Automated ticket scanners are deployed widely for pass verification, but no product reliably identifies and physically refuses 'undesirable persons' in production settings.

Operate refreshment stands during intermission or obtain refreshments for press box patrons during performances.

CI 5–15 · exposure 0 · augmentation 0 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Venue management and hospitality sectors show minimal adoption of automation for in-person refreshment service, as the task fundamentally requires human presence and physical capabilities on-site.
Sector adoption velocity	claude-sonnet-5	1/5	Venue/hospitality service roles are a low-digitization, physical-labor sector with minimal AI/robotics adoption for this kind of task.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI offers negligible assistance to an usher operating a refreshment stand; the task is primarily manual labor and real-time customer service with no clear augmentation pathway.
Augmentation potential	claude-sonnet-5	1/5	AI offers essentially no assistance for physically stocking, serving, or delivering refreshments in this context.
Task automatability	claude-haiku-4-5-20251001	1/5	Operating refreshment stands and obtaining refreshments require physical movement, handling cash/payments, and real-time interaction with patrons in a venue environment—tasks that current AI systems cannot perform end-to-end without human intervention.
Task automatability	claude-sonnet-5	1/5	This is a physical service task requiring movement, handling food/drink items, and interacting with patrons in a physical space—current AI has no capability to perform this end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Food safety regulations, health code compliance, and liability for food handling create significant legal and operational barriers; venues would face regulatory and insurance friction attempting to automate food service.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement exists, but the task inherently requires physical presence, dexterity, and real-time customer interaction, creating a natural (not regulatory) barrier to substitution.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The cost of autonomous robots capable of safe food handling, payment processing, and navigation in a crowded venue would vastly exceed the loaded wage of a venue attendant.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI-based substitute for this physical labor task, so any comparison favors the human worker who can already do this cheaply and flexibly.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI system can physically operate a refreshment stand, handle transactions, or fetch items for patrons; this remains entirely dependent on human labor in production environments.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product operates refreshment stands or delivers physical items to patrons; this remains outside AI's operational domain entirely (robotics for this specific niche is not deployed).

Assist patrons in finding seats, lighting the way with flashlights, if necessary.

CI 5–15 · exposure 0 · augmentation 0 · 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	1/5	Adoption is essentially zero; this is a low-digitization, physical-presence task in traditionally conservative, human-centric hospitality sectors with strong preference for personal service.
Sector adoption velocity	claude-sonnet-5	1/5	Ushering and venue services are a low-digitization, physically-oriented sector with minimal AI adoption for this specific physical guidance function.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI offers minimal assistance to a human usher performing this task, since the core work is physical presence, interpersonal warmth, and real-time visual guidance with a flashlight—areas where AI currently adds little value.
Augmentation potential	claude-sonnet-5	1/5	AI tools offer essentially no assistance to a human physically walking patrons to seats with a flashlight; there is no digital component to augment.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires real-time physical presence in a venue, physical navigation of aisles with a flashlight, and direct interpersonal guidance to patrons. Current AI systems cannot perform the physical/embodied aspects end-to-end, and meaningful automation would require deployed humanoid robots, which remain research-stage for this use case.
Task automatability	claude-sonnet-5	1/5	This requires physical presence, mobility, and real-world sensing (dark venues, physical seat location) that current AI systems cannot perform end-to-end; no software or robotic system can guide patrons to physical seats today.atably.rc
Adoption barriers	claude-haiku-4-5-20251001	4/5	Significant barriers exist: venue liability if an automated system fails to guide a patron correctly (especially for accessibility), customer expectation of human service for hospitality, and safety requirements for navigating crowded aisles with potentially elderly or disabled patrons.
Adoption barriers	claude-sonnet-5	2/5	No licensing or legal barrier exists, but the physical, real-world nature of navigating a dark venue and assisting people creates a strong practical barrier to any non-physical automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The hardware and software costs of a functional robotic usher (humanoid robot, venue mapping, real-time pathing, obstacle avoidance) far exceed the loaded wage of a part-time or event-based human usher.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing this physical guidance task, so cost comparison favors the human by default since AI cannot deliver the output at all.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed commercial products reliably perform this task. While computer vision and robotics research exists, no production systems are substituting for ushers in theaters or event venues at scale today.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical seating assistance with flashlights in venues; this remains entirely a human physical task with no robotic or AI equivalent in production.

Give door checks to patrons who are temporarily leaving establishments.

CI 5–10 · exposure 0 · augmentation 0 · 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	1/5	Venues and entertainment sectors have minimal incentive and low digitization around this specific task. Adoption data shows no measurable movement toward automating door checks; the task remains firmly human-staffed.
Sector adoption velocity	claude-sonnet-5	1/5	Entertainment/venue services sector has low digitization for this specific physical task and no meaningful AI adoption trend for door-check handling.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI offers no meaningful assistance to a human issuing door checks. The task is straightforward operational work requiring only human presence and physical handling; software assistance would add no value.
Augmentation potential	claude-sonnet-5	1/5	AI offers essentially no assistance for the physical act of handing out or checking re-entry passes at a venue exit.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical interaction (handing a physical object), human judgment about patron intent, and face-to-face customer service. No current AI system can reliably perform the end-to-end workflow of checking patron status, issuing a physical token, and managing the interpersonal exchange.
Task automatability	claude-sonnet-5	1/5	This requires physical presence to hand a physical token or stamp to a person at a real-world venue exit; no AI system can perform this physical interaction.", "rating stands at bottom of scale.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Venues typically require human staff for security, liability, and patron trust reasons. Direct human-customer contact is an implicit requirement, and venues rely on human judgment to prevent fraud or unauthorized re-entry, creating organizational and safety friction against automation.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement, but the task requires physical presence and direct customer interaction, creating practical barriers to remote automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The task involves minimal labor cost (low-wage, simple physical exchange) and requires human presence regardless. AI deployment would add infrastructure and integration costs without reducing the need for on-site staff, making it economically inferior.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute for this physical task, so any 'AI cost' comparison is moot; a human or simple mechanical system remains cheaper and necessary.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product performs this task autonomously. It is inherently tied to physical presence, real-time human interaction, and trust-based exchange that current AI systems cannot execute in production venues.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product hands out physical door checks or manages this in-person physical transaction at venues today.

Settle seating disputes or help solve other customer concerns.

CI 0–10 · exposure 0 · augmentation 25 · importance 4.0/5 · 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 of AI for customer-facing dispute resolution in hospitality and ticketing venues remains minimal; the sector relies on human staff precisely because interpersonal expertise is valued and difficult to automate.
Sector adoption velocity	claude-sonnet-5	1/5	Ushers and venue staff work in a low-digitization, physically-situated service sector with minimal AI agent deployment for interpersonal conflict handling.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could marginally assist by suggesting policy answers or logging complaint details, but the core work—listening, negotiating, deciding—must remain human-driven, limiting practical augmentation gains.
Augmentation potential	claude-sonnet-5	2/5	AI could provide minor support like translation apps or scripted policy lookups, but offers little real assistance during live interpersonal disputes.
Task automatability	claude-haiku-4-5-20251001	1/5	Settling seating disputes and addressing customer concerns requires real-time judgment, empathy, negotiation, and contextual problem-solving—skills that current AI systems cannot reliably perform end-to-end in live customer-facing scenarios. No AI system today can autonomously resolve interpersonal conflicts or make nuanced decisions about fairness and accommodation.
Task automatability	claude-sonnet-5	1/5	Resolving in-person interpersonal disputes requires physical presence, real-time de-escalation, and situational judgment that current AI cannot perform end-to-end.'
Adoption barriers	claude-haiku-4-5-20251001	5/5	This task has strong human-contact and service-quality requirements: customers expect to interact with a human who can listen, empathize, and make discretionary decisions. Venues bear liability for poor resolution, creating regulatory and reputational pressure to retain human judgment.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement exists, but strong customer preference for human mediation and the need for physical presence and authority create meaningful friction.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The cost of an AI system (hardware, integration, training, oversight) that could reliably handle dispute resolution would far exceed the loaded wage of an usher or lobby attendant who performs this task.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing this task, so cost comparison favors the human by default since AI cannot deliver the output at all.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product reliably performs this task. While chatbots can provide scripted responses to simple inquiries, they cannot authentically mediate disputes, read emotional cues, or make binding decisions that satisfy conflicting parties in real-world venues.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product handles in-person customer conflict resolution in venues like theaters or stadiums; this remains entirely a human function.

Provide assistance with patrons' special needs, such as helping those with wheelchairs.

CI 0–5 · exposure 0 · augmentation 25 · 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	1/5	Hospitality and venue management sectors show minimal adoption of automation for direct patron assistance; human staff remain the standard for accessibility support.
Sector adoption velocity	claude-sonnet-5	1/5	Venue and hospitality front-of-house roles involving physical patron assistance show minimal AI/robotic adoption to date.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could potentially help identify patron needs through accessibility questionnaires or scheduling logistics, but offers minimal practical assistance during the physical act of providing wheelchair or mobility support.
Augmentation potential	claude-sonnet-5	2/5	AI could help with scheduling, wayfinding info, or dispatching staff to assist patrons, but offers little direct augmentation of the hands-on physical assistance itself.
Task automatability	claude-haiku-4-5-20251001	1/5	Assisting patrons with wheelchairs requires physical dexterity, spatial awareness, and responsive interaction with variable human needs that current AI cannot perform. No end-to-end automation exists for this embodied, person-to-person assistance task.
Task automatability	claude-sonnet-5	1/5	Physical assistance with wheelchairs and mobility requires direct human physical intervention that current AI systems, lacking embodied robotic manipulation capability at scale, cannot perform.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Liability for patron safety during assistance, potential ADA compliance requirements for human service provision, and the necessity of direct human contact make this task legally and organizationally protected.
Adoption barriers	claude-sonnet-5	4/5	Disability accommodation laws (e.g., ADA) and safety/liability concerns around physically assisting vulnerable patrons create strong requirements for trained human staff.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The hardware and safety requirements for a robotic system to assist wheelchair users would vastly exceed the loaded wage of a human usher, making economic substitution infeasible today.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing physical assistance, so AI cost comparison is inapplicable and effectively AI cannot deliver the output at any cost.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI or robotic systems reliably perform wheelchair assistance and special-needs support in production venues. This task remains firmly human-dependent in all operational settings.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product physically assists patrons with wheelchairs or mobility needs in venues; this remains a human physical-service task.

Guide patrons to exits or provide other instructions or assistance in case of emergency.

CI 0–5 · exposure 0 · augmentation 25 · 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	Hospitality and entertainment venues are not adopting AI for emergency guidance; this task remains almost entirely performed by humans due to regulatory requirements, liability concerns, and the physical and social nature of the work.
Sector adoption velocity	claude-sonnet-5	1/5	The venue/entertainment services sector is low-digitization for physical safety tasks, and there is no meaningful trend toward AI-driven emergency crowd guidance.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could marginally assist (e.g., real-time emergency alert displays, crowd-flow information), but the core task of physically guiding and assisting patrons in emergencies remains fundamentally human-dependent, limiting meaningful augmentation.
Augmentation potential	claude-sonnet-5	2/5	AI-based alert systems, signage, or communication tools could support emergency planning or notification, but offer minimal real-time assistance during the actual physical guidance task.
Task automatability	claude-haiku-4-5-20251001	1/5	Guiding patrons during emergencies requires real-time human judgment, situational awareness, physical presence, and adaptive communication that current AI systems cannot reliably perform end-to-end. Emergency response demands split-second decisions about crowd dynamics, individual needs, and environmental hazards that remain outside AI capability.
Task automatability	claude-sonnet-5	1/5	This requires physical presence, real-time human judgment, and crowd management during emergencies, which no AI system can perform end-to-end today.'
Adoption barriers	claude-haiku-4-5-20251001	5/5	Strong legal and safety barriers exist: venues have fire code and occupancy law requirements for trained human staff during emergencies, liability falls on the venue, and insurance/regulatory frameworks mandate human accountability for patron safety during evacuations.
Adoption barriers	claude-sonnet-5	4/5	Fire codes, safety regulations, and liability concerns typically require trained human staff to be physically present and responsible for emergency evacuation procedures.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Physical presence, real-time decision-making, and liability in emergency contexts mean that deploying an AI system (including robotic embodiment, sensors, and oversight) would exceed the cost of a human usher or lobby attendant.
Cost vs. human wage	claude-sonnet-5	1/5	AI cannot substitute for the physical human presence needed, so there is no comparable AI cost basis; a human is required regardless of price.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product can autonomously guide physical crowds to exits or provide emergency assistance at scale. This task requires embodied presence, real-time perception, and human-level decision-making in chaotic conditions that no production AI system addresses.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product physically guides patrons or manages emergency evacuations in venues; this remains firmly outside current AI product capabilities.

Search for lost articles or for parents of lost children.

CI 0–5 · exposure 0 · augmentation 25 · 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	1/5	Venues that employ ushers and ticket takers operate in low-digitization, labor-intensive, physical environments with minimal AI adoption; structural and economic incentives to automate this specific task are weak.
Sector adoption velocity	claude-sonnet-5	1/5	Ushers and venue staff work in a low-digitization, physical-presence-dependent sector with minimal AI adoption for this kind of task.
Augmentation potential	claude-haiku-4-5-20251001	2/5	Digital tools (e.g., lost-and-found databases, messaging systems) offer modest assistance in logging and tracking items, but AI cannot materially augment the core activity of physical search and human-to-human reunion.
Augmentation potential	claude-sonnet-5	2/5	AI could marginally assist via PA announcements, lost-and-found logging systems, or communication tools, but offers little help with the core physical search and reunification process.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires real-time physical search in a space, direct human interaction with distressed parties, and contextual judgment about matching lost items or children to their owners—capabilities far beyond current AI systems that operate in digital or controlled environments.
Task automatability	claude-sonnet-5	1/5	This task requires physical presence, mobility through a venue, visual scanning, and human judgment to locate lost items or reunite children with parents—none of which current AI systems can perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Strong legal, safety, and liability barriers apply: a human attendant is typically required for child welfare and lost-and-found protocols; automating this would face regulatory resistance and parental-trust concerns that are difficult to overcome.
Adoption barriers	claude-sonnet-5	4/5	Lost child situations involve child safety, liability, and immediate human judgment/authority concerns that strongly favor human handling, though not formal licensing.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Even accounting for eventual sensor infrastructure or mobile robots, the cost of reliably automating this task across diverse venues would far exceed the loaded wage of a lobby attendant performing it.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this physical search task, so AI cost is effectively infinite relative to a human doing it.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product can autonomously search physical venues for lost articles or reunite lost children with parents; this requires embodied presence, social judgment, and safety-critical decision-making that no production AI system handles today.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical search for lost articles or lost children; this remains entirely a human, in-person task.

Related occupations — Personal Care & Service

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.