Gambling managers
SOC Code: 11-9071
Gambling managers carries a 45% AI exposure score (High automation risk), with a median annual wage of $85,580 and +1.2% projected employment growth from 2024 to 2034 (BLS), affecting approximately 5,100 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 45% AI exposure, Gambling managers sits 8 points above the 37.2% average across 832 U.S. occupations - more exposed than 79% of them. Most of its core tasks still require human judgment.
Career outlook score
48/100
Gambling managers, weighted across 3 of 3 tracked dimensions
A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.
- Median wage A- $85,580
Annual median wage, percentile rank vs all tracked occupations
- Projected growth F +1.2%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) F 45% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure
Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).
Automation-risk inventory
Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Gambling managers in the High band.
Credential × growth standing
Open entry with non-declining BLS pace
Gambling managers keeps an HS / some college bar (333 of 832) and sits in Slow growth (245 of 832). Lower formal gates with a non-shrinking employment line - skill and AI desks matter more than credentials here.
Where Gambling managers sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Gambling managers sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
45% Higher than most higher than 79% of 832 occupations
Occupations, banded by AI-exposure score
Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.
Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Gambling managers vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Gambling managers is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Gambling managers's High automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score in the 40–70% range indicates meaningful automation pressure on specific task categories, but the role as a whole still requires human judgment for coordination, exception handling, or client interaction.
The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 11-9071) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Gambling managers be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Gambling managers. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Resolve customer complaints regarding problems, such as payout errors.
- 2. Remove suspected cheaters, such as card counters or other players who may have systems that shift the odds of winning to their favor.
- 3. Circulate among gaming tables to ensure that operations are conducted properly, that dealers follow house rules, or that players are not cheating.
- 4. Track supplies of money to tables and perform any required paperwork.
- 5. Set and maintain a bank and table limit for each game.
- 6. Explain and interpret house rules, such as game rules or betting limits.
- 7. Prepare work schedules and station arrangements and keep attendance records.
- 8. Monitor staffing levels to ensure that games and tables are adequately staffed for each shift, arranging for staff rotations and breaks and locating substitute employees as necessary.
- 9. Direct the compilation of summary sheets that show wager amounts and payoffs for races or events.
- 10. Maintain familiarity with all games used at a facility, as well as strategies or tricks employed in those games.
Key Skills Required
- Critical Thinking
- Management of Personnel Resources
- Speaking
- Monitoring
- Active Listening
- Social Perceptiveness
- Coordination
- Service Orientation
- Complex Problem Solving
- Judgment and Decision Making
Knowledge Areas
- Customer and Personal Service
- English Language
- Administration and Management
- Mathematics
- Personnel and Human Resources
- Administrative
- Computers and Electronics
- Economics and Accounting
- Education and Training
- Public Safety and Security
Frequently Asked Questions
Will AI replace Gambling managers?
Gambling managers has an AI exposure score of 45%, indicating a high level of automation risk. Some tasks in this role can be augmented or partially automated by AI, but core responsibilities require human judgment.
What is the job outlook for Gambling managers?
According to BLS Employment Projections 2024-2034, Gambling managers is projected to grow by 1.2% over the decade. Current employment stands at approximately 5,100 workers.
What skills are needed for Gambling managers?
Key skills for Gambling managers include Critical Thinking, Management of Personnel Resources, Speaking, and others. Typical entry-level education is High school diploma or equivalent.
How much do Gambling managers earn?
The median annual wage for Gambling managers is $85,580, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Gambling managers?
The typical entry-level education for Gambling managers is High school diploma or equivalent. Employers generally expect Less than 5 years of related work experience. On-the-job training typically involves None. Requirements can vary by employer and specialization.
Which companies employ Gambling managers?
Gambling managers roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
High automation risk based on 10 analyzed tasks. A moderate share of tasks may be augmented by AI tools.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Gambling managers: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (45% here).
- Advertising sales agents · AI exposure 45%
- Broadcast announcers and radio disc jockeys · AI exposure 45%
- Electrical and electronics repairers, commercial and industrial equipment · AI exposure 45%
- First-line supervisors of mechanics, installers, and repairers · AI exposure 45%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (+1.2% here).
- Air traffic controllers · growth +1.2%
- Biological scientists, all other · growth +1.2%
- Camera operators, television, video, and film · growth +1.2%
- Economists · growth +1.2%
Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.
Related Occupations
Showing 6 of 14 occupations with a comparable automation-risk profile.
What to do with this
Use Gambling managers' numbers above to compare, not just read in isolation.
- Compare Gambling managers side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.
Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).