The AI Training Trap: Upskill Your Best People, Then Watch Them Leave
Your Best AI-Trained Employees Are 55% More Likely to Quit
New EY research reveals a striking paradox: the employees who receive the most AI training become your highest flight risks. Employees who receive extensive AI training gain more than 14 hours of productive time each week—nearly double the 8-hour median gain. But those same highly trained employees are 55% more likely to leave your organisation.
This is the AI Training Trap—and it's costing companies far more than they realise.
Why it matters: Companies are missing up to 40% of potential AI productivity gains—not because the technology isn't working, but because talent strategy hasn't kept pace with it.
The Data Behind the Paradox
The findings come from the EY 2025 Work Reimagined Survey, conducted in November–December 2025 across 29 countries with 15,000 employees and 1,500 employers. It is one of the most comprehensive looks at how AI is reshaping the workforce to date.
The training gap is stark. Only 12% of employees say they receive sufficient AI training. The overwhelming majority of workers are being asked to operate alongside AI without meaningful preparation. Meanwhile, the minority who do receive deep training become measurably more productive—and measurably more attractive to competitors.
HR and people investment are the bottleneck, not the tools.
Why Training Alone Isn't Enough
There's a straightforward logic behind the paradox. Employees who develop strong AI skills become more valuable in the labour market. If your organisation upskills them but doesn't adjust compensation, offer meaningful advancement, or give them visible AI-linked career paths, they have every incentive to take those skills elsewhere.
The EY data does not establish direct causation—the relationship is associative. But the pattern is consistent: more AI training is associated with higher attrition risk. Organisations that invest in developing talent without investing in keeping that talent are essentially subsidising their competitors' talent pipelines.
Why it matters: This isn't unique to AI—the same dynamic has played out with data science skills, cloud certifications, and agile expertise over the past decade. AI is accelerating the cycle and raising the stakes.
What HR Leaders Should Do Now
The answer is not to slow down AI training. Pulling back on upskilling would surrender the productivity gains and leave your workforce even further behind. The answer is to change what surrounds the training.
1) Pair upskilling with total rewards reviews
Employees who complete meaningful AI training milestones should see that reflected in compensation and benefits. If your pay bands haven't been reviewed in the context of AI skill premiums, they are probably already out of date.
2) Build internal mobility pathways
AI-proficient employees want to work on AI-enabled projects. If your organisation can't offer those opportunities internally, attrition becomes inevitable. Create visible routes for trained employees to move into roles where they apply what they've learned.
3) Create AI-linked career pathing
Document what AI capability looks like at each career level. Make it clear that investing in AI skills is not just a short-term productivity play—it's a pathway to advancement. Employees who can see a future inside your organisation are far less likely to build one elsewhere.
4) Measure retention as an upskilling KPI
Most organisations track completion rates and productivity outcomes from training programs. Few track whether trained employees stay. Add retention to your program metrics. If your highest-trained cohort is churning at elevated rates, that's a signal your retention strategy needs to catch up.
The Real Opportunity
The companies that will win this decade are not those that train the most aggressively or retain the most stubbornly. They are the ones that do both—treating AI upskilling and talent retention as a single integrated strategy rather than separate HR workstreams.
The EY research is a warning, but it is also a roadmap. Forty percent of AI productivity gains are still sitting on the table. The organisations that close that gap will be the ones that figure out how to invest in their people's AI capabilities without inadvertently making them someone else's best hire.
Final Takeaway
Train smarter. Retain harder. The trap has an exit—but only if HR leads the way out.
Sources
What is the "AI Training Trap"?
The AI Training Trap is the paradox where employees who receive the most advanced AI training become significantly more productive, but also significantly more likely to leave the organisation if compensation, career paths, and internal opportunities do not keep pace with their new market value.
Why does more AI training increase attrition risk?
Deep AI training makes employees more valuable in the external labour market. If organisations upskill people without adjusting pay, advancement opportunities, or AI-linked career paths, those employees have strong incentives to take their new skills to competitors who will reward them appropriately.
How big is the AI productivity gap identified by EY?
According to the EY 2025 Work Reimagined Survey, companies are missing up to 40% of potential AI productivity gains—not because the technology is ineffective, but because talent strategy, training coverage, and retention have not kept up with AI deployment.
What should HR leaders change about AI upskilling programs?
HR leaders should pair AI upskilling with updated total rewards, visible internal mobility into AI-enabled roles, and clear AI-linked career pathing. They should also treat retention of trained employees as a core KPI for training programs, not just track completion rates or short-term productivity gains.
Is pulling back on AI training a good way to reduce attrition?
No. Slowing AI training would sacrifice productivity gains and leave the workforce less prepared. The article argues that the solution is not less AI training, but smarter training combined with robust retention strategies so that organisations benefit from the capabilities they help create.