Key Takeaways
- 56% of workers say they would be comfortable using AI at work if it were explained to them
- 65% of U.S. employers report training is needed for workers to manage new technology
- 86% of employees believe they would stay longer at a company that invests in their learning and development
- 4.6 million people in the U.S. quit or switched jobs in the leisure and hospitality sector during the first quarter of 2024
- In the U.S., there were 4.6 million leisure and hospitality separations in the first quarter of 2024 (churn tied to reskilling needs)
- U.S. food services and drinking places employed 12.4 million people in 2023
- Food and beverage service workers spend an average of 40% of their work time on tasks that require customer service skills (training relevance)
- The U.S. O*NET skills taxonomy lists ‘Food Preparation’ as a core skill for Cooks
- The hospitality industry worldwide faces a projected 8.0% gap in skills demand vs. supply by 2030
- 63% of organizations that use learning experience platforms (LXPs) report improved learning outcomes
- Using spaced learning can improve retention by up to 200% compared with massed practice (meta-analytic finding relevant to reskilling)
- Simulation-based training is associated with higher learning effectiveness than traditional instruction (meta-analysis result: medium effect size)
- In the U.S., 73% of employers use electronic monitoring/scheduling tools for workforce management (often tied to training workflows)
- In retail and hospitality, 78% of frontline workers are smartphone users (enabling microlearning and reskilling)
- The global e-learning market is projected to reach $420.3 billion by 2026 (training delivery trend)
With high turnover and rising skill demands, targeted AI enabled training can help culinary workers stay and grow.
Related reading
- Upskilling And Reskilling In IndustryUpskilling And Reskilling In The Food Service Industry Statistics
- Upskilling And Reskilling In IndustryUpskilling And Reskilling In The Material Handling Industry Statistics
- Upskilling And Reskilling In IndustryUpskilling And Reskilling In The Video Game Industry Statistics
- Upskilling And Reskilling In IndustryUpskilling And Reskilling In The Promotional Products Industry Statistics
01 · Category
Workforce Readiness4 stats
Workforce Readiness Interpretation
02 · Category
Labor Market Demand5 stats
Labor Market Demand Interpretation
03 · Category
Skill Supply & Gaps3 stats
Skill Supply & Gaps Interpretation
04 · Category
Training Methods3 stats
Training Methods Interpretation
05 · Category
Technology Enablement2 stats
Technology Enablement Interpretation
06 · Category
Industry Trends2 stats
Industry Trends Interpretation
More related reading
07 · Category
Performance Metrics4 stats
Performance Metrics Interpretation
08 · Category
Credentialing & Compliance3 stats
Credentialing & Compliance Interpretation
09 · Category
Labor Participation4 stats
Labor Participation Interpretation
10 · Category
Training Adoption1 stats
Training Adoption Interpretation
11 · Category
Culinary Job Pipeline6 stats
Culinary Job Pipeline Interpretation
Upskilling is becoming essential in foodservice and hospitality
A growing mix of workforce demand signals and employer/employee readiness indicators points to the need for ongoing upskilling and reskilling in culinary roles.
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Min-ji Park. (2026, February 13). Upskilling And Reskilling In The Culinary Industry Statistics. Gitnux. https://gitnux.org/upskilling-and-reskilling-in-the-culinary-industry-statistics
Min-ji Park. "Upskilling And Reskilling In The Culinary Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/upskilling-and-reskilling-in-the-culinary-industry-statistics.
Min-ji Park. 2026. "Upskilling And Reskilling In The Culinary Industry Statistics." Gitnux. https://gitnux.org/upskilling-and-reskilling-in-the-culinary-industry-statistics.
Sources & references
37 datasets cited across this report · attribution is report-level
+19 additional datasets cited (not shown individually)
