# Restaurants Turn to AI to Solve Staffing Shortages

> Source: <https://letsdatascience.com/news/restaurants-turn-to-ai-to-solve-staffing-shortages-d0ef18bc>
> Published: 2026-05-26 23:41:33.572890+00:00

# Restaurants Turn to AI to Solve Staffing Shortages

PYMNTS reports that the restaurant industry continues to face acute labor pressure: the sector employed **15.9 million** workers in 2025 and average annual turnover topped **75%**, with quick-service restaurants regularly exceeding **130%**. An industry association's 2026 report, cited by PYMNTS, found **80%** of operators were short at least one position in 2025, the average operator carried **five** open roles (up from **3.8**), and average training cost per hire was **$3,037**. PYMNTS describes a Miami-based entrant called **MAJC** that combines AI-powered job-matching, training and community tools as an integrated workforce platform aimed at hospitality operators.

### What happened

PYMNTS reports that staffing shortages, high turnover and retention problems continue to strain restaurant economics. PYMNTS reports the sector employed **15.9 million** workers in 2025, with average annual turnover at **75%** and quick-service turnover regularly exceeding **130%**. An industry association's 2026 report, cited by PYMNTS, found **80%** of operators had at least one open position in 2025, an average of **five** open roles per operator (up from **3.8**), and average training cost per hire of **$3,037**.

### What was announced

PYMNTS describes a Miami-based company called **MAJC** that, according to PYMNTS, combines AI-powered job-matching, training and community features into a single workforce platform for hospitality professionals. PYMNTS reports MAJC launched with a culinary council led by a James Beard Award-winning chef and a Chief People Officer, and cites a February source describing MAJC as the world's largest full-service restaurant company.

### Editorial analysis - technical context

Companies building hiring and retention platforms for high-turnover sectors typically pair algorithmic matching with onboarding automation, training modules and scheduling optimization to reduce time-to-fill and improve early retention. Industry deployments often hinge on data quality from applicant tracking systems, POS logs and scheduling tools, and on integration with payroll and shift-management systems.

### Industry context

Observed patterns in comparable transitions show operators prioritize reliability and measurable labor-efficiency gains over headline AI features. Vendors that deliver measurable reductions in time-to-hire, training hours or no-shows tend to gain traction first, while broader cultural shifts (career ladders, benefits) remain outside purely technical fixes.

### What to watch

For observers, relevant indicators will include measured changes in time-to-fill and first-90-day retention reported by operators, integration breadth with existing HR and POS systems, and any third-party validation studies of matching accuracy and training efficacy. PYMNTS did not quote MAJC executives on rationale in the scraped article, and MAJC's public statements should be checked for methodology and performance claims.

## Scoring Rationale

The story highlights important applied-AI work in a large, high-turnover sector where operational gains can be material for practitioners and vendors. It is notable but not frontier-level model or infrastructure news.

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