Gambling and Sports Book Writers and Runners
39-3012.00Median wage $34,980/yr8,950 employed (US)Rank #161 of 923 scored · top 17% by substitution
Post information enabling patrons to wager on various races and sporting events. Assist in the operation of games such as keno and bingo. May operate random number-generating equipment and announce the numbers for patrons. Receive, verify, and record patrons' wagers. Scan and process winning tickets presented by patrons and pay out winnings for those wagers.
Sub-scores
0–100 · band = confidence interval from rater disagreement
Substitution41
Exposure40
Augmentation38
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
18 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
17%
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%41
panel mean rating 2.6/5 → substitution pressure 41/100
Technical feasibility todayw 20%39
panel mean rating 2.6/5 → substitution pressure 39/100
Cost vs. human wagew 15%47
panel mean rating 2.9/5 → substitution pressure 47/100
Adoption barriersw 20%inverted — strong barriers lower the score42
panel mean rating 3.3/5 (barrier strength) → substitution pressure 42/100
Sector adoption velocityw 10%33
panel mean rating 2.3/5 → substitution pressure 33/100
Task breakdown (18 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.
Compare the house hand with players' hands to determine the winner.
92CI 90–95 · exposure 100 · augmentation 63 · importance 4.7/5 · click for rater detail
Compare the house hand with players' hands to determine the winner.
92| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 5/5 | Online gambling platforms and digital casinos already universally use automated hand comparison; even physical casinos are steadily shifting to electronic table management systems, indicating deep and rapid sector adoption. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Casinos have adopted electronic and hybrid tables at meaningful but uneven rates; many venues still emphasize live dealers for customer experience, so adoption is moderate rather than fast and universal. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can augment human runners by instantly validating their judgment calls and highlighting ambiguous hand rankings for human review, materially speeding dispute resolution and reducing error. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI/automated systems can assist human dealers by verifying hand outcomes and flagging discrepancies, improving speed and accuracy while the dealer remains customer-facing. |
| Task automatability | claude-haiku-4-5-20251001 | 5/5 | Determining a winner by comparing hands in games like poker or blackjack is entirely rule-based and algorithmic; current AI can instantly evaluate all possible hand rankings and declare winners with 100% accuracy, far exceeding the 50% time-saving threshold. |
| Task automatability | claude-sonnet-5 | 5/5 | Comparing card hands to determine a winner is a deterministic rules-based computation that automated systems (e.g., electronic table games, RFID card readers) already handle perfectly and instantly. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | While most jurisdictions permit algorithmic hand determination in online gambling, some casinos and jurisdictions may have legacy regulatory frameworks or customer-trust preferences favoring human presence; however, no binding legal requirement universally mandates a human runner for this judgment. |
| Adoption barriers | claude-sonnet-5 | 2/5 | Gaming regulations govern licensing of equipment and dealers in live settings, but electronic and automated table games are already legally approved in many jurisdictions, so barriers are moderate rather than strict human-only mandates. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 5/5 | The inference cost of comparing hands is near-zero (microseconds per comparison), while human runners require hourly wages; full-stack deployment cost is negligible relative to labor costs. |
| Cost vs. human wage | claude-sonnet-5 | 5/5 | Automated hand comparison via software/RFID sensors costs fractions of a cent per hand versus a human dealer's wage, an order-of-magnitude or greater saving. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 5/5 | Hand-comparison logic is already deployed at scale in online gambling platforms and casino management systems; rule engines and computer vision solutions reliably determine winners in production environments worldwide. |
| Technical feasibility today | claude-sonnet-5 | 5/5 | Electronic gaming tables, video poker, and online casino platforms already perform this exact comparison at scale in production with essentially zero error rate. |
Record the number of tickets cashed and the amount paid out after each race or event.
84CI 74–95 · exposure 87 · augmentation 50 · importance 4.1/5 · click for rater detail
Record the number of tickets cashed and the amount paid out after each race or event.
84| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 5/5 | Sportsbooks and casinos are high-digitization environments with strong financial incentives; automated ticketing and transaction systems are industry standard, indicating deep and rapid adoption of automation in this domain. |
| Sector adoption velocity | claude-sonnet-5 | 4/5 | Gaming and sports betting is a fast-digitizing sector with widespread adoption of automated wagering and reconciliation systems, especially with the rise of online and mobile sportsbooks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can assist by flagging anomalies, reconciling discrepancies, or organizing summary reports, but the core recording task leaves limited room for meaningful human–AI collaboration once automated. |
| Augmentation potential | claude-sonnet-5 | 3/5 | Where manual recording still occurs (e.g., at small physical counters), AI/automated systems can assist with tallying and error-checking, though the task is largely already automated rather than augmented. |
| Task automatability | claude-haiku-4-5-20251001 | 4/5 | Recording ticket counts and payout amounts is straightforward data entry and arithmetic that can be largely automated by integrating with betting systems or OCR of tickets. Current AI could handle 70–80% of this workflow, though some edge cases (damaged tickets, manual payouts) may require human intervention. |
| Task automatability | claude-sonnet-5 | 5/5 | Recording ticket counts and payout amounts is a simple structured data-entry/reconciliation task that automated ticketing and point-of-sale systems already handle natively without human intervention. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Gaming and sports betting are regulated industries requiring audit trails and compliance reporting; while this creates some oversight requirements, the recording task itself is not legally prohibited from automation and is already largely automated in modern sportsbooks. |
| Adoption barriers | claude-sonnet-5 | 2/5 | There may be some regulatory record-keeping requirements for gaming operations, but the recording itself is not legally required to be performed by a licensed human and is already commonly automated in many jurisdictions. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 5/5 | Automated logging and data entry via existing betting management software costs orders of magnitude less than hiring staff to manually record tickets and payouts after each event. |
| Cost vs. human wage | claude-sonnet-5 | 5/5 | Automated ticketing/POS systems record this data as a byproduct of the transaction at near-zero marginal cost compared to a human writer manually tallying and logging figures. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 4/5 | Sports betting and gaming platforms already use automated systems to log transactions, ticket counts, and payouts at scale. Sportsbooks and casinos deploy real-time transaction recording systems in production that capture this data reliably. |
| Technical feasibility today | claude-sonnet-5 | 5/5 | Modern sportsbook and casino wagering systems (both physical kiosks and online platforms) already log ticket cashing and payouts automatically as part of standard transaction processing in production. |
Answer questions about game rules or casino policies.
71CI 65–76 · exposure 70 · augmentation 75 · importance 4.1/5 · click for rater detail
Answer questions about game rules or casino policies.
71| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | The gaming and hospitality sector is moderately digitized and beginning chatbot rollouts, but adoption remains mixed—some properties use AI FAQs while others maintain human call centers; this reflects middling adoption with pilots more common than deep integration. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Gaming/casino floor operations are a physically-oriented, less digitized sector with slower AI adoption compared to information or finance sectors. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can significantly assist humans by instantly surfacing rules, policies, and precedents during a conversation, reducing lookup time and improving answer consistency while the employee manages relationship and judgment aspects of customer interaction. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI tools (chat assistants, quick-reference apps) can help staff quickly look up rules or policies to answer patron questions faster and more accurately. |
| Task automatability | claude-haiku-4-5-20251001 | 4/5 | LLMs and retrieval-augmented systems can reliably answer factual questions about standardized game rules and published casino policies with high accuracy; this is largely information lookup and explanation requiring minimal judgment, easily achieving 50% time savings in most cases. |
| Task automatability | claude-sonnet-5 | 4/5 | Answering factual questions about rules and policies is well-suited to LLM-based chatbots and can be handled with high time savings, though edge cases involving disputes still need human judgment. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | Gaming is regulated but rule-explanation itself is not legally gated; casinos may prefer human agents for liability or customer experience reasons, but no license or legal requirement prevents AI from handling this task, creating moderate but surmountable friction. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement to answer rule questions, though casinos may prefer human staff for customer service ambiance and to manage disputes or regulatory compliance nuances. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 5/5 | The inference cost for an LLM answering a rules question is cents per query, while a human employee answering the same question costs $15–30+ in loaded wages; the cost ratio heavily favors AI automation. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | An AI system answering routine rules questions costs a fraction of a cent per query versus paying a staffed employee, making it dramatically cheaper for high-volume simple queries. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 4/5 | Deployed chatbots and knowledge-base systems already perform rule-explanation tasks in production across gaming and hospitality sectors; systems reliably handle FAQs about game rules and standard policies, though edge cases and novel policy disputes may still require human verification. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | Casino chatbots and kiosks exist for basic rule/policy Q&A, but most floor-level interactions still rely on human runners/writers rather than deployed conversational AI at scale. |
Start gaming equipment that randomly selects numbered balls and announce winning numbers and colors.
67CI 57–76 · exposure 70 · augmentation 25 · importance 4.5/5 · click for rater detail
Start gaming equipment that randomly selects numbered balls and announce winning numbers and colors.
67| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Many casinos and gaming venues have automated number-drawing and announcement systems, but adoption varies widely by jurisdiction and gambling type; regulatory constraints and operator preference for human oversight prevent rapid universal adoption. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Gaming/casino industry adopts automation for draws and displays steadily, though many venues retain human runners/writers for customer service and floor presence, slowing full displacement. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | Augmentation potential is limited because the task is mechanical and rule-bound; AI could log results or provide analytics, but adds little value to the operator announcing winning numbers in real time. |
| Augmentation potential | claude-sonnet-5 | 2/5 | For the narrow act of starting equipment and announcing numbers, AI/automation mostly replaces rather than augments the human, offering little added productivity boost to a person still performing this specific task. |
| Task automatability | claude-haiku-4-5-20251001 | 4/5 | The core mechanical process of starting gaming equipment and announcing results is highly automatable—triggering random number generation and broadcasting outcomes requires minimal human intervention. However, some tasks like physical verification of equipment or regulatory compliance checks may require human oversight, preventing a perfect 5. |
| Task automatability | claude-sonnet-5 | 4/5 | Starting equipment and announcing pre-generated random results is a simple mechanical/verbal task easily automated by automated draw machines and voice announcement systems already used in many venues.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Gaming and lottery operations are heavily regulated; jurisdictions typically mandate human presence, witness requirements, or certified equipment operation for regulatory transparency and anti-fraud purposes, creating legal barriers to full automation. |
| Adoption barriers | claude-sonnet-5 | 2/5 | Gaming regulations require certified equipment and audit trails but do not typically require a licensed human to operate the draw mechanism or announce results, so barriers are modest. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | Automated systems for ball-drawing and number announcement have minimal per-cycle operating costs once deployed (electricity, maintenance), substantially cheaper than paying wages to human operators to perform the same repetitive function. |
| Cost vs. human wage | claude-sonnet-5 | 5/5 | Automated ball-draw and announcement systems are a one-time hardware/software cost versus ongoing wages, making automation dramatically cheaper per game run. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | Automated lottery and gaming equipment systems exist and are deployed in some jurisdictions, but they typically require human operators for security, regulatory observation, and equipment verification. Full end-to-end automation faces acceptance and compliance barriers in practice. |
| Technical feasibility today | claude-sonnet-5 | 4/5 | Automated bingo/keno machines and electronic announcement systems are already deployed widely in casinos and gaming halls, though some venues retain human callers for atmosphere and compliance. |
Prepare collection reports for submission to supervisors.
65CI 60–70 · exposure 70 · augmentation 75 · importance 4.0/5 · click for rater detail
Prepare collection reports for submission to supervisors.
65| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 4/5 | Gambling and sports book operations are digitized, high-transaction environments with strong financial reporting discipline. These sectors show relatively fast adoption of automation tools for compliance and operational reporting. Existing pressure to scale reporting with volume and regulatory deadlines drives velocity above average. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | The gambling/casino floor operations sector is not a fast digital adopter compared to finance or professional services, though back-office reporting functions are gradually modernizing. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can draft complete reports, highlight anomalies, and surface key metrics, allowing supervisors to focus on interpretation, oversight, and decision-making rather than manual compilation. This significantly raises productivity and data-driven insight without removing human judgment from the review loop. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI-driven reporting tools can significantly speed up drafting, formatting, and flagging anomalies in collection reports, helping human workers focus on verification and exceptions. |
| Task automatability | claude-haiku-4-5-20251001 | 4/5 | This task involves compiling structured data (collections, figures, statistics) into reports—a process well-suited to current AI systems. AI can extract numerical data, format tables, generate summary statistics, and compose standard report sections with minimal human intervention, achieving substantial time savings. Some domain context and approval workflow may require human oversight, but the bulk of report preparation can be automated. |
| Task automatability | claude-sonnet-5 | 4/5 | Preparing collection reports is largely a data compilation and summarization task—totaling wagers, payouts, and cash flows—which current AI paired with existing point-of-sale/gaming systems can automate at high time savings once inputs are digitized.atability. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Gambling and sports books operate under regulatory oversight; reports may need to be certified or signed by a supervisor before submission, creating a human sign-off requirement. However, the automation itself faces no licensing restriction, and supervisors can review and approve AI-generated reports efficiently, making barriers moderate rather than hard. |
| Adoption barriers | claude-sonnet-5 | 3/5 | Gaming industry has regulatory and audit requirements around cash handling and reporting accuracy, often requiring human sign-off or oversight, creating moderate compliance friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | AI-driven report generation costs a fraction of a full-time report writer's loaded wage. Inference and integration overhead are minimal for tabular and text summarization tasks. The cost advantage is substantial, particularly when amortized across repeated monthly or weekly submissions. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | Automated report generation from transactional data is very cheap compared to paying a human writer/runner to compile and submit reports manually, though initial system integration adds some cost. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 4/5 | Production-ready systems (RPA, document automation tools, large language models with data integration) are deployed today to generate financial and operational reports at scale. Gaming and sports book operations already use automated reporting pipelines for regulatory and internal compliance. Minor customization may be needed, but mature platforms reliably handle collection report generation. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | Casino management and financial reporting software already automate much of this reporting, but many gambling operations still rely on manual reconciliation and human-verified logs, so full deployment varies by casino sophistication. |
Pay off or move bets as established by game rules and procedures.
59CI 37–81 · exposure 55 · augmentation 63 · importance 4.5/5 · click for rater detail
Pay off or move bets as established by game rules and procedures.
59| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 5/5 | Large-scale sportsbooks and online betting platforms have already deployed automation for routine settlement at scale, with major operators in high-digitization sectors (DraftKings, FanDuel, etc.) using automated systems as standard practice. This represents production-level adoption across the sector. |
| Sector adoption velocity | claude-sonnet-5 | 4/5 | Online and mobile sports betting has rapidly automated bet placement and payout processes industry-wide over the past several years, especially since legalization expansion in the US. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI systems augment human operators by auto-settling routine bets, flagging exceptions, and providing settlement recommendations, allowing operators to focus on complex disputes and customer issues. This materially raises operator throughput while keeping humans in control of edge cases. |
| Augmentation potential | claude-sonnet-5 | 3/5 | In physical sportsbook settings, AI/software tools assist human writers with calculating payouts and moving bets faster, though human oversight remains common for in-person transactions. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Core bet settlement requires discrete rule application and transaction logging, which AI could partially automate. However, the task includes judgment calls on disputed outcomes, customer disputes, and edge-case rule interpretations that require human oversight, limiting end-to-end automation to simple, standardized wagers. |
| Task automatability | claude-sonnet-5 | 4/5 | Paying off or moving bets follows deterministic rule-based logic (odds, payout tables) that is highly structured and already automated in electronic sportsbooks and betting platforms.: |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Sportsbook operations are heavily regulated by state and federal authorities, and payoff procedures are subject to gaming licensing requirements and audit trails. Many jurisdictions mandate human operators or licensed personnel sign off on settlements, particularly for disputed or high-value bets, creating hard legal barriers. |
| Adoption barriers | claude-sonnet-5 | 2/5 | Gaming regulations require licensing and auditability of wagering operations, but automated settlement is already standard and accepted in regulated online and kiosk-based betting, so barriers are modest. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | Automated bet settlement systems have minimal per-transaction inference costs and integration is well-established in modern sportsbooks, making them substantially cheaper than human settlement on volume. However, dispute handling and oversight still require some human involvement, preventing the deepest cost advantage. |
| Cost vs. human wage | claude-sonnet-5 | 5/5 | Automated bet settlement software costs a fraction of a cent per transaction compared to a human writer's wage for the same repetitive task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | Sportsbooks have deployed systems that automatically settle straightforward bets against official results, but many real-world scenarios involve judgment (late-game rule changes, voided bets, customer claims) that require human adjudication. Production systems handle routine payouts but fall short of fully autonomous operation. |
| Technical feasibility today | claude-sonnet-5 | 4/5 | Mature deployed systems (online sportsbooks, kiosk terminals, automated cashiers) already calculate and settle bets automatically at scale in real production environments. |
Compute and verify amounts won or lost, paying out winnings or referring patrons to workers, such as gaming cashiers, so that winnings can be collected.
54CI 25–84 · exposure 55 · augmentation 50 · importance 4.3/5 · click for rater detail
Compute and verify amounts won or lost, paying out winnings or referring patrons to workers, such as gaming cashiers, so that winnings can be collected.
54| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Gaming establishments use existing point-of-sale and gaming management software, but actual payout authorization remains human-controlled due to regulatory mandates and risk management; adoption of autonomous payout AI is minimal in production. |
| Sector adoption velocity | claude-sonnet-5 | 4/5 | Sportsbooks and casinos have rapidly adopted electronic wagering, kiosks, and automated cashiering systems, especially with the growth of mobile and online betting platforms. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI could usefully assist by pre-calculating amounts, flagging anomalies, and managing simple referrals to cashiers, thereby reducing manual verification time, but the human runner must remain in the loop for approval and dispute resolution. |
| Augmentation potential | claude-sonnet-5 | 3/5 | Where human writers/runners still operate, AI/software assists by instantly calculating payouts, reducing errors and speeding verification, though physical handling and patron interaction remain human tasks. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While basic calculation of winnings/losses can be automated, the task requires judging patron disputes, confirming identity compliance, and routing decisions that demand human discretion. Current AI systems could automate roughly 30-40% of routine payout calculations, but not the full end-to-end task at 50% time savings. |
| Task automatability | claude-sonnet-5 | 4/5 | Computing amounts won or lost from odds/payout tables is a deterministic calculation task well within current software capability; only the physical payout and patron interaction resist full automation., but the compute/verify portion is highly automatable |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Gambling payouts are heavily regulated by gaming commissions and state law; a licensed gaming employee must legally authorize and verify payouts in most jurisdictions, creating a hard barrier to full automation regardless of technical capability. |
| Adoption barriers | claude-sonnet-5 | 2/5 | Gaming is regulated and requires licensed operators and audited systems, but automated payout calculation itself is standard and widely permitted; no requirement for a human to manually compute payouts. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Integration with gaming floor systems, compliance auditing, and required human oversight make AI implementation costs comparable to or exceeding the hourly wage of a sports book runner, especially accounting for liability and error correction. |
| Cost vs. human wage | claude-sonnet-5 | 5/5 | Software-based payout calculation is essentially free per transaction compared to a human writer/runner's wage, especially at scale in electronic sportsbooks. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed products reliably perform the full task autonomously in production gambling environments. Gaming systems can track balances, but regulatory and liability requirements mandate human verification and decision-making on actual payouts, leaving only narrow automation in payment routing. |
| Technical feasibility today | claude-sonnet-5 | 5/5 | Automated betting systems, kiosks, and cashiering software already compute payouts reliably in production at casinos and sportsbooks worldwide. |
Exchange paper currency for playing chips or coins.
49CI 25–72 · exposure 50 · augmentation 25 · importance 4.7/5 · click for rater detail
Exchange paper currency for playing chips or coins.
49| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Gaming and casino sectors show slow adoption of full automation in customer-facing, cash-handling roles due to regulatory constraints, customer preference for human interaction, and compliance requirements. Mechanical chip dispensers exist but have not displaced workers at scale. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Casinos have adopted TITO and self-service cash machines steadily but many properties still rely heavily on human cage staff and runners, making adoption moderate rather than fast. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could modestly assist by verifying currency and player eligibility before a worker completes the exchange, but the core task—physical exchange and immediate customer interaction—offers limited augmentation opportunity; the human remains essential. |
| Augmentation potential | claude-sonnet-5 | 2/5 | The task itself is a discrete physical/transactional act with limited room for AI to augment a human performing it, beyond kiosks replacing rather than assisting the worker. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While currency-to-chip exchange involves clear procedures, end-to-end automation requires physical manipulation (accepting bills, dispensing chips) and real-time verification of currency authenticity and player accounts. Current AI cannot reliably handle the full physical workflow, though parts (verification, accounting) could be partially automated with significant setup. |
| Task automatability | claude-sonnet-5 | 4/5 | This is a simple, repetitive cash-handling transaction that automated kiosks and cash-to-chip machines can already perform end-to-end with high reliability, meeting the time-savings threshold. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Gaming establishments operate under strict regulatory oversight; cash handling and chip issuance are tightly licensed activities requiring human accountability and compliance documentation. Most jurisdictions legally require a licensed gaming employee to perform or directly authorize chip exchanges. |
| Adoption barriers | claude-sonnet-5 | 2/5 | Gaming regulations require currency transaction reporting and anti-money-laundering controls, but these can be built into automated kiosks; no licensing requires a human specifically to hand over chips. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | The infrastructure and oversight costs for even partial automation (cash-handling machines, integration with gaming systems) remain comparable to or exceed the marginal labor cost of a skilled casino worker handling exchanges, especially given low transaction complexity per exchange. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | Kiosk hardware plus minimal maintenance oversight is substantially cheaper per transaction than a staffed cashier over high transaction volumes, though upfront capital costs and cash servicing reduce the ratio somewhat. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed AI system reliably performs this task end-to-end in production. Chip dispensing machines exist but require human oversight for cash authentication and player verification; they solve a narrow subset rather than the full exchange transaction as described. |
| Technical feasibility today | claude-sonnet-5 | 4/5 | Cash redemption machines, TITO kiosks, and automated chip dispensers are already deployed in many casinos, though full replacement of human cage/pit staff for chip exchange is not universal. |
Check to ensure that all players have placed their bets before play begins.
46CI 39–54 · exposure 42 · augmentation 63 · importance 4.5/5 · click for rater detail
Check to ensure that all players have placed their bets before play begins.
46| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Casinos and sportsbooks are digitizing operations and deploying betting system integrations, but adoption of fully automated pre-play verification is mixed; many still employ runners in hybrid roles. The gaming industry modernizes faster than some sectors but slower than purely digital finance. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Casino/gambling floor operations are a physical, moderately regulated sector with slower digitization outside of online sportsbooks; live table automation adoption is gradual. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI dashboards flagging missing or suspicious bets in real-time could substantially increase a runner's speed and accuracy in verifying all players are ready, enabling them to catch errors before play and reducing manual checking labor while keeping the human accountable for final sign-off. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI-enabled sensors and electronic systems can assist by flagging late bets or discrepancies, helping the worker but not fully replacing the oversight role in live settings. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Verification that all players have placed bets requires monitoring multiple concurrent human actions and state changes in real-time. While AI could theoretically scan betting systems to confirm entries exist, the task involves dynamic real-world coordination that is partially automatable but faces integration challenges with diverse betting platforms and the need for fallback human judgment when discrepancies arise. |
| Task automatability | claude-sonnet-5 | 3/5 | This is a simple verification/monitoring task that could be automated via sensors, electronic betting systems, or camera-based detection, but requires physical/environmental integration beyond pure software.electronically-tracked tables already do this automatically.true |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Gaming operations face regulatory compliance requirements that may require human attestation or liability for missed bets, and many venues prefer human runners for customer-facing trust and discretionary judgment. Organizational inertia and union agreements in some jurisdictions also create moderate friction against full automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | Gaming regulations often require licensed personnel to oversee bet integrity and fraud prevention, creating moderate regulatory and trust-based barriers to full automation, especially in live casino settings. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | A simple automated check against a betting database costs minimal compute and integration overhead compared to the hourly wage of a human runner performing this verification task repeatedly throughout a gaming session. |
| Cost vs. human wage | claude-sonnet-5 | 3/5 | Automated systems (RFID chips, electronic terminals) have upfront hardware costs but low marginal cost per game; for legacy live tables, replacing a low-wage worker with new infrastructure may not yet be dramatically cheaper. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | Betting management software and point-of-sale systems exist that log bet placement, and some automated alerts can flag missing bets. However, deployed systems typically still require manual runner review for edge cases (verbal bets, system errors, player disputes), so reliable end-to-end automation without human oversight remains incomplete in production. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | Electronic gaming tables and digital sportsbook platforms already enforce bet placement deadlines automatically, but many live table games still rely on human dealers/writers for this check, so deployment is uneven across venues. |
Collect cards or tickets from players.
36CI 5–67 · exposure 33 · augmentation 13 · importance 4.3/5 · click for rater detail
Collect cards or tickets from players.
36| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Gaming venues and sports books operate in regulated, often physical environments where worker presence is mandated; digital transformation of this specific task is minimal. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Casinos and gaming venues have adopted self-service kiosks and electronic terminals at a moderate pace, but many traditional table-game and sportsbook settings still rely heavily on human staff. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | AI cannot meaningfully assist a human in the act of collecting physical cards or tickets; the task is straightforward physical collection with no analytical or cognitive component to enhance. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI offers limited direct augmentation for the physical act of collecting cards or tickets, though supporting systems like scanners can speed up processing when a human is still involved. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Collecting physical cards or tickets from players requires physical manipulation and presence in a gaming environment; current AI systems lack embodied robotics or in-person presence to perform this task end-to-end. |
| Task automatability | claude-sonnet-5 | 4/5 | Physical collection of cards/tickets is largely mechanical and could be replaced by kiosks, self-service terminals, or automated ticket scanners in most gambling contexts, though some physical handling remains. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Gaming establishments have regulatory requirements around verification of age, identity, and authorization; human workers handling cash and cards are often required by gaming commissions and state law. |
| Adoption barriers | claude-sonnet-5 | 2/5 | Gaming regulations require oversight and controls on money/ticket handling but the specific act of collecting tickets is not itself subject to strict licensing requiring a human, so barriers are moderate rather than high. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Human workers currently perform this task at low cost in labor-intensive gaming environments; any robotic solution would be prohibitively expensive compared to direct human labor. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | Kiosks and automated systems have low marginal operating cost compared to paying a human runner an hourly wage for a simple collection task, though upfront hardware investment is required. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product can physically collect cards or tickets from players; this is fundamentally a physical, in-person task requiring human agents on-site. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | Automated ticket redemption kiosks and electronic betting terminals already exist and are deployed in many casinos and sportsbooks, but many venues still rely on human runners for table games and in-person collection. |
Collect bets in the form of cash or chips, verifying and recording amounts.
34CI 0–67 · exposure 38 · augmentation 38 · importance 4.5/5 · click for rater detail
Collect bets in the form of cash or chips, verifying and recording amounts.
34| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Gambling operations have not adopted AI for on-floor cash collection; the sector remains highly regulated and risk-averse around financial handling. Physical casinos and betting parlors rely on trusted human staff for this security-critical function. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Casinos and sportsbooks have adopted self-service kiosks and mobile betting meaningfully, but many venues still rely heavily on human writers for cash/chip transactions, especially in traditional table-adjacent settings. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist with recording and verification (flagging irregular patterns post-hoc), but the core act of collecting, securing, and handling cash in real-time remains human-dependent. Assistance is marginal and limited to back-end analytics. |
| Augmentation potential | claude-sonnet-5 | 3/5 | Point-of-sale and verification software assists human writers with recording and validating bets, reducing errors, though the physical cash/chip handling still requires human involvement in many settings. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Collecting physical cash or chips requires real-world manipulation, trust verification, and secure handling that current AI cannot perform end-to-end. The task involves sensory judgment (verifying denominations, detecting counterfeits) and physical presence that autonomous systems lack today. |
| Task automatability | claude-sonnet-5 | 4/5 | Automated betting kiosks, electronic terminals, and self-service wagering systems already handle bet collection, verification, and recording in most modern casinos and sportsbooks, meeting the time-saving threshold for standard transactions. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Gambling and sports betting are heavily regulated; licensed, bonded humans are often legally required to handle customer funds and record wagers. Liability, licensing, and anti-money-laundering rules create hard barriers to automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | Gaming regulations, cash-handling/AML rules, and licensing requirements for gaming establishments create moderate friction, though electronic wagering is already widely permitted with proper certification. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The wage for a bet collector is modest, but the capital cost of robotics capable of secure currency handling, plus compliance overhead, far exceeds the human labor cost. Integration would require specialized hardware unavailable at favorable economics. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | Automated kiosks and terminals cost far less per transaction than a human writer's wage once deployed, though initial hardware and compliance integration add some cost. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product collects and verifies physical currency or gaming chips in a production casino or betting environment. This task fundamentally requires robotic hardware combined with fraud detection, neither of which operates reliably in this regulated, high-stakes context. |
| Technical feasibility today | claude-sonnet-5 | 4/5 | Deployed self-service betting terminals, mobile sportsbook apps, and cash-recycling kiosks reliably perform bet collection and recording at scale across many jurisdictions today. |
Open or close cash floats or game tables.
17CI 9–25 · exposure 20 · augmentation 38 · importance 4.6/5 · click for rater detail
Open or close cash floats or game tables.
17| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Gaming establishments rely on strict compliance and human accountability for cash management; adoption of automation in this specific function is minimal because regulatory frameworks require licensed personnel to take responsibility for float accuracy. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Casino floor operations are a low-digitization, physically-anchored sector where AI adoption for cash-handling procedures remains slow and mostly limited to counting machines rather than full task automation. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist with automated logging, variance alerts, or reconciliation reports, but the human remains responsible for the physical act and verification of opening/closing tables and cash counts. |
| Augmentation potential | claude-sonnet-5 | 3/5 | Automated coin/cash counters and inventory tracking software can speed up reconciliation, providing moderate productivity assistance while the human remains responsible for the physical opening/closing process. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Opening/closing cash floats requires physical handling of currency, secure storage, and real-time verification of amounts—tasks that demand human presence and tactile manipulation. AI could assist with documentation and reconciliation, but the core operational requirements remain manual. |
| Task automatability | claude-sonnet-5 | 2/5 | Involves physical handling of cash, chips, and equipment plus verification steps that require presence at a table, limiting end-to-end AI automation, though counting/reconciliation could be assisted by automated cash-counting devices.: |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Gaming and sports betting are heavily regulated industries where cash handling is subject to licensing requirements, auditing, and often legal requirements that a named, accountable human must perform or certify. Liability for cash shortages falls on designated personnel. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Gaming regulations typically require licensed personnel to handle and verify cash floats and table inventories, with strict chain-of-custody and surveillance requirements that resist automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The cost of deploying AI-assisted systems (cameras, sensors, software integration) plus human oversight would exceed the cost of a staff member performing the task directly, especially given compliance and accountability needs. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | Specialized cash-counting hardware and security systems have upfront and maintenance costs comparable to or exceeding the low wage of a casino floor worker for this narrow task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI system can autonomously handle physical cash management, including counting, securing, and physically opening/closing gaming tables. This task fundamentally requires human physical presence and responsibility. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Automated cash-counting and chip-tray reconciliation systems exist in some casinos, but full open/close procedures still require a human physically present and accountable at the table. |
Conduct gambling tables or games, such as dice, roulette, cards, or keno, and ensure that game rules are followed.
14CI 5–23 · exposure 13 · augmentation 25 · importance 4.8/5 · click for rater detail
Conduct gambling tables or games, such as dice, roulette, cards, or keno, and ensure that game rules are followed.
14| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Physical gambling venues (casinos, card rooms) remain highly dependent on human dealers and are subject to strict licensing rules that have changed little; adoption of automation in game conduct itself is minimal, with only ancillary monitoring tools seeing slow uptake. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Casino floor operations are a low-digitization, physically-intensive sector with minimal AI/agent adoption for actual game dealing; electronic gaming machines are a separate, slow-moving trend. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI can assist with rule-violation detection and data logging, but has limited upside in raising a human dealer's core productivity because the task fundamentally requires licensed human judgment, physical conduct, and regulatory authority that AI cannot meaningfully augment. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could assist with surveillance, fraud detection, or rule-compliance monitoring in the background, but offers little direct augmentation to the physical act of running the table. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI could monitor game rules and detect violations via computer vision or sensor input, the core task requires active human conduct of physical games (dealing cards, spinning roulette) and real-time judgment calls that depend on in-person presence and authority. Current AI systems cannot reliably manage the full end-to-end operation with 50% time savings at equal quality. |
| Task automatability | claude-sonnet-5 | 1/5 | This requires physical presence at a table, manual card/dice handling, chip management, and real-time in-person interaction with players, none of which current AI can perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Gaming commissions and regulators require licensed, bonded human dealers and floor supervisors to physically conduct and oversee games; gaming licenses, liability insurance, and gaming law typically mandate human sign-off on game conduct. These legal and regulatory barriers are substantial. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Gaming operations require licensed personnel, strict regulatory oversight, anti-cheating controls, and casinos value human interaction and trust, creating strong barriers to automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI surveillance or rule-monitoring tools exist at moderate cost, but they augment rather than replace dealers and floor managers. The all-in cost of a full automation solution (hardware, integration, oversight) would still exceed the cost of human staff given the need for physical presence and legal accountability. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI substitute performing this physical, socially interactive job, so no meaningful cost comparison favors AI; casinos would need robotics plus AI, which is far costlier than a human dealer today. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed product reliably conducts physical gambling tables autonomously. Computer vision systems can detect some rule violations, but no production system independently runs tables at scale; human dealers and floor staff remain essential in all deployed gambling venues. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed AI product operates live table games as a dealer; electronic table games exist but replace the format entirely rather than automate the human dealer role. |
Inspect cards or equipment to be used in games to ensure they are in proper condition.
14CI 5–23 · exposure 13 · augmentation 38 · importance 4.3/5 · click for rater detail
Inspect cards or equipment to be used in games to ensure they are in proper condition.
14| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Gambling operations are heavily regulated, risk-averse, and depend on trusted human inspectors; adoption of AI for this task is negligible because regulatory bodies mandate human accountability and operators fear reputational or compliance damage from automation. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Casino floor operations are a low-digitization, physical-labor-heavy sector with minimal AI agent deployment for equipment handling tasks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI could assist by flagging potentially problematic equipment for human re-inspection, reducing false negatives and speeding up routine scanning; however, the task's straightforward nature and low complexity limit augmentation gains compared to tasks requiring judgment. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI-based computer vision could theoretically flag anomalies in cards or dice via camera systems, but this is not standard practice for hands-on inspection by writers/runners and offers limited current assistance. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Visual inspection of cards and gaming equipment could be partially automated with computer vision, but ensuring proper condition requires detecting subtle defects, wear, markings, and irregularities that demand fine-grained judgment and domain expertise; current AI systems struggle with comprehensive end-to-end replacement at equal quality. |
| Task automatability | claude-sonnet-5 | 1/5 | This requires physical handling and visual/tactile inspection of cards, dice, and equipment for damage, marking, or tampering, which current AI cannot perform without robotic embodiment. Off-the-shelf AI has no way to physically inspect gaming equipment on a casino floor. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Gaming equipment inspection is heavily regulated; casino and gaming commissions typically require certified human personnel to verify equipment integrity, and liability for missed defects creates a hard barrier to full automation without licensed oversight. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Gaming regulatory bodies require licensed personnel to inspect and certify equipment integrity for fairness and anti-cheating compliance, creating strong regulatory and liability barriers. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | High-resolution imaging systems, specialized computer vision models, and human oversight to validate AI decisions would likely be comparable to or exceed the cost of a worker performing spot checks, especially given the liability of false negatives in gaming. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI substitute performing this physical inspection task, so cost comparison favors the human by default. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | While computer vision systems can identify gross defects or damage, no widely deployed product reliably inspects gaming equipment for the full range of condition issues (bent cards, faded markings, mechanical wear) at production scale in gambling venues. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs physical inspection of gambling equipment; this remains a manual, hands-on task performed by casino staff. |
Deliver tickets, cards, and money to bingo callers.
13CI 10–15 · exposure 0 · augmentation 0 · importance 3.9/5 · click for rater detail
Deliver tickets, cards, and money to bingo callers.
13| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Gambling and bingo operations are physically-located, traditionbound, and have low digitization and automation investment velocity compared to information or finance sectors. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Gambling venues and bingo halls are low-digitization, physical-labor environments with minimal AI/robotics adoption for such menial physical tasks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | AI offers no meaningful assistance to a human performing direct physical delivery and handoff of items. The task requires bodily presence and does not benefit from ML or decision support. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers essentially no assistance for the physical act of walking materials and cash to a caller; this is not a cognitive or information task AI can support. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task is fundamentally physical: delivering tangible items (tickets, cards, money) to a specific person in a physical location. Current AI systems have no robotic embodiment in deployed, general-purpose form capable of reliable material handling and navigation in variable environments. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical delivery task requiring walking through a venue and handling materials and cash, which off-the-shelf AI systems cannot perform end-to-end.olejo Robotics could theoretically do this but no general AI system performs this today. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | Physical tasks that require human presence and trust (handling cash, tickets, face-to-face handoff) create some organizational friction and audit/control preferences, though no strict legal barrier prevents automation in principle. |
| Adoption barriers | claude-sonnet-5 | 3/5 | Handling cash and gambling-related materials often involves venue security, trust, and sometimes gaming-license or background-check requirements, creating moderate organizational and regulatory friction against automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | A mobile robot capable of reliable delivery in a bingo hall would cost tens of thousands of dollars plus maintenance, vastly exceeding the hourly wage of a runner performing occasional delivery tasks. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI system that performs this physical handling and delivery task, so any hypothetical automation (e.g., robotics) would be far more expensive than a low-wage human runner today. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product performs this task. It would require mobile robotics with manipulation, navigation, and object handling capabilities operating reliably in real-world venues—still largely research-stage outside narrow, controlled settings. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed AI product delivers physical tickets, cards, and cash to bingo callers in production; this remains purely a human physical task. |
Operate games in which players bet that a ball will come to rest in a particular slot on a rotating wheel, performing actions such as spinning the wheel and releasing the ball.
8CI 0–16 · exposure 0 · augmentation 0 · importance 4.8/5 · click for rater detail
Operate games in which players bet that a ball will come to rest in a particular slot on a rotating wheel, performing actions such as spinning the wheel and releasing the ball.
8| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Casinos operate in highly regulated, brick-and-mortar environments with strong incumbent labor practices and licensing barriers. Adoption of physical automation in this sector is minimal and proceeds at a laggard pace. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | The casino/gaming sector adopts electronic and automated table games slowly and selectively, with live dealers still dominant in premium and high-touch gaming segments. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | This task offers no meaningful opportunity for AI assistance, as it is purely physical wheel-spinning and ball-release with no analytical, predictive, or information-processing component. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers essentially no assistance to a human physically spinning a wheel and releasing a ball; this is a manual dexterity task with no cognitive augmentation opportunity. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task is fundamentally physical—spinning a wheel and releasing a ball—and requires real-time interaction with mechanical equipment in a physical space. Current AI systems have no capability to manipulate physical objects or operate casino equipment. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical task requiring manual dexterity to spin a wheel and release a ball in a live casino setting; no AI system performs the physical operation of a roulette wheel today. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Gambling operations are heavily regulated at state and federal levels; casino operators must comply with licensing requirements and gaming control board oversight. Most jurisdictions require licensed human dealers or operators to manage actual gaming equipment, creating hard legal barriers to automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | Gaming regulations require licensed, background-checked personnel and surveillance for integrity of wagering, and casinos value human dealers for customer experience, creating moderate regulatory and preference-based friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Even if a robotic system were available, the capital and maintenance cost would far exceed the loaded wage of a roulette operator, making automation economically infeasible. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | Automated electronic roulette machines exist and can be cheaper long-term, but they represent capital equipment investment, not an AI cost-per-task substitution scenario, and human dealers remain preferred in many venues for experience value. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product can physically operate roulette wheels or casino gaming equipment. This task requires embodied robotics in a regulated gambling environment, which does not exist in production systems today. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product operates physical roulette wheels; automated roulette exists only as fully mechanized electronic wheel systems, which are a hardware substitute rather than an AI performing the task. |
Sell food, beverages, or tobacco to players.
3CI 0–5 · exposure 0 · augmentation 25 · importance 3.9/5 · click for rater detail
Sell food, beverages, or tobacco to players.
3| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Gambling and sports book operations are physically constrained venues with low digital transformation and no evidence of AI replacing point-of-sale staff. Adoption velocity is minimal in this sector. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Casino floor service and hospitality retail are low-digitization, physical-presence-dependent sectors with minimal AI/robotics adoption for this kind of task. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist with inventory management or payment processing recommendations, but the core task of selling and age verification requires human judgment and legal accountability, limiting meaningful augmentation. |
| Augmentation potential | claude-sonnet-5 | 2/5 | POS systems and inventory/ordering software provide minor efficiency gains, but AI offers little meaningful assistance to the core physical selling and serving task. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Selling food, beverages, or tobacco requires direct interpersonal interaction, handling cash or payment systems, reading customer needs, and regulatory compliance around age-restricted items like tobacco. Current AI cannot autonomously perform these in-person transactional and compliance-heavy tasks. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical in-person retail/hospitality task requiring handling of goods, cash/card transactions, and often ID checks for tobacco/alcohol; no AI system performs this end-to-end.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Selling tobacco requires age verification and state/local licensing compliance; selling in a gambling venue involves venue-specific permissions; and direct customer service expects human interaction. Legal and regulatory requirements create hard barriers to full automation. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Alcohol and tobacco sales require age verification and often licensed/trained staff under state gaming and liquor regulations, creating legal barriers to full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Deploying a robotic or AI system to replicate a human food/beverage server in a venue, including payment handling and compliance oversight, would be more expensive than the loaded wage of a minimum-wage server. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI substitute performing this physical sales function, so AI cost cannot be compared favorably; human labor remains the only viable option. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI system reliably operates independently as a cashier or point-of-sale agent handling physical goods, payments, and age verification in gambling venues. Vending automation exists but does not cover the full scope of salesmanship and judgment required. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed AI product sells physical food, beverages, or tobacco to customers on a casino floor; this remains entirely a human/physical retail function. |
Supervise staff and games and mediate disputes.
3CI 0–5 · exposure 0 · augmentation 25 · importance 3.8/5 · click for rater detail
Supervise staff and games and mediate disputes.
3| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | The gambling industry is heavily regulated and risk-averse; supervisory and dispute-mediation tasks remain firmly gatekept by licensing requirements and human accountability standards, with minimal AI substitution in production. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | The gambling/casino floor operations sector is low-digitization and physically grounded, with minimal AI agent deployment in supervisory roles. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist by flagging suspicious patterns or organizing dispute data, but the core tasks of staff supervision and mediation require human judgment and authority; assistance is narrow and peripheral rather than transformative. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could assist with logging incidents, tracking game data, or flagging anomalies, but offers limited direct help with the core supervisory and mediation activities. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Supervising staff, mediating disputes, and making judgment calls on game rulings require human judgment, interpersonal negotiation, and contextual understanding of complex social situations. Current AI cannot reliably handle the nuanced decision-making and conflict resolution inherent in dispute mediation. |
| Task automatability | claude-sonnet-5 | 1/5 | Supervising staff and games and mediating interpersonal disputes on a casino floor requires real-time physical presence, judgment, and authority that current AI cannot replicate end-to-end.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Gaming commissions and gambling regulations explicitly require licensed, human supervisors to oversee operations and resolve disputes; many jurisdictions legally mandate that a responsible human must perform or sign off on these functions for regulatory compliance and liability purposes. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Gaming supervisors typically require gaming licenses and regulatory oversight, and dispute mediation involves authority and liability that must rest with an authorized human employee. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The cost of deploying AI systems to monitor disputes, combined with required human oversight and liability concerns, exceeds the wage cost of a single supervisor, especially in time-sensitive gambling contexts where errors are costly. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI substitute performing this supervisory/mediation role, so cost comparison favors the human by default. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product reliably mediates disputes or supervises human staff in real-time operational settings. While AI can flag anomalies or draft recommendations, final mediation and supervisory authority remain human functions in all production gambling environments. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed AI product supervises gaming staff or mediates in-person disputes; this remains a human management function with no production analog. |
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.