Restaurants Can’t Find Workers. AI Says It Can. .. PYMNTS.com ...Middle East

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The restaurant industry solved online ordering, delivery and digital payments. It still hasn’t solved labor.

Staffing shortages, high turnover and retention problems continue straining restaurant economics, pushing operators toward technology platforms built to stabilize hiring pipelines and reduce workforce churn.

Miami-based MAJC, which launched in February, is among the newest entrants in a category attracting growing operator attention. The platform combines artificial intelligence-powered job-matching, training and community tools to run a single workforce engine built for hospitality professionals.

A Structural Problem

The numbers behind the industry’s labor challenge haven’t moved in years.

The National Restaurant Association projected total restaurant employment at 15.9 million workers in 2025, making the sector the nation’s second-largest private employer. Despite that scale, turnover rates remained among the highest in the economy. The average annual restaurant turnover rate topped 75%, with quick-service restaurants regularly exceeding 130%.

The association’s 2026 State of the Restaurant Industry report found that 80% of restaurants said they were short at least one position in 2025. The average operator carried five open roles, up from 3.8 the prior year. Training a single new employee cost an average of $3,037.

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TD Bank found that 54% of surveyed participants cited a shrinking labor pool as their biggest challenge in attracting and retaining talent. Labor efficiency, training and scheduling were the top areas where operators said AI could deliver improvements.

What MAJC Is Building

MAJC, which debuted with a culinary council led by James Beard Award-winning chef Andrew Zimmern and Darden Restaurants Chief People Officer Sarah King, is the world’s largest full-service restaurant company, according to a February press release.

The company’s focus sits at the intersection of hiring infrastructure and retention culture, which are two problems operators have historically addressed through separate tools and instinct rather than integrated platforms.

Small operators, in particular, struggle to fill roles across HR, marketing and accounting while competing with better-resourced chains, the release said. Hourly employees often lack clear career advancement tracks, a gap the platform aims to close.

“Hospitality has always been about people, and MAJC understands that technology should support, not replace, that reality,” King said in the release. “By combining AI with the power of an expert community and learning academy, MAJC is democratizing access to software and systems that help operators attract, develop and retain great talent, improving their bottom line and strengthening the entire industry.”

Labor as a Technology Problem

MAJC’s rollout reflects a broader shift in how the restaurant industry is framing its workforce challenge.

Nation’s Restaurant News reported in December that labor shortages dominated operator concerns heading into 2026, with immigration reform and rising costs compounding the pressure.

“As restaurant operators navigate rising costs and workforce constraints, AI is emerging as a potentially material lever for long-term growth and sustainability,” Mark Wasilefsky, head of TD Bank’s Restaurant Franchise Finance Group, said in a statement.

The National Restaurant Association found that technology and AI are creating measurable gains in hiring speed, workforce efficiency and scheduling. Multilingual AI-powered hiring tools reduced Chipotle’s application-to-start date from 12 days to 4, nearly doubled applicant flow and pushed application completion rates from roughly 50% to nearly 85%.

Southern Rock Restaurants also uses lightweight digital tools, including QR codes and text-to-apply features, to streamline hiring. Those tools strengthen employee referral programs, long considered one of the restaurant industry’s most reliable recruiting methods, by letting candidates quickly submit applications wherever they are.

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