There is a divide over who should be responsible for AI training
AI is changing everything, how we work, how we decide, how we compete. And yet, in many large companies, there’s confusion about something basic: who’s responsible for making sure employees know how to use AI. The answer isn’t consistent. A new global survey from Emergn covered 751 large companies. Here’s what they found: 81% of employees think employers should lead AI training. But 83% of CEOs believe it’s the employee’s job to get up to speed. That gap isn’t just a difference of opinion, it’s a friction point that’s already slowing AI adoption in organizations where alignment should be a given.
Leadership isn’t even consistent internally. Only 59% of CTOs and 64% of COOs back the CEO view that AI upskilling should be self-driven. That tells us the disconnect isn’t just between leadership and the broader workforce, it’s also happening at the executive level. That kind of fragmentation undermines progress. Because when no one owns the mission, it stalls. You can’t move fast on AI, and you should be moving fast, when your teams can’t agree who should learn what, or who should pay for it.
Executives need to treat AI training as base infrastructure. That means top-down investment, coordinated planning, and leadership alignment. Otherwise, adoption becomes patchy, transformation slows, and talent doesn’t stick around.
As Alex Adamopoulos, CEO at Emergn, put it: “Employees say ‘train us.’ Employers say ‘train yourselves.’ That paradox is becoming one of the biggest barriers to AI adoption.” He’s not exaggerating. The longer the deadlock continues, the further behind your people, and by extension, your business, fall.
Employees have strong expectations for employer-led AI upskilling initiatives
Employees aren’t sitting around waiting for AI to pass them by. They know it’s the future, and they want to be ready for it. The same Emergn survey showed that 77% of employees expect their companies to provide structured AI training. Two-thirds said they’d reconsider working for a company that doesn’t offer it. That’s not a mild suggestion, it’s a strong demand.
This isn’t just about technical skills. Employees understand that AI will reshape many roles, not just in engineering or data science, but across departments. Sales, operations, finance, every function is impacted. Workers want to stay relevant. They want clarity. If organizations don’t step up and offer that through training and guidance, productivity isn’t the only thing at risk. Retaining skilled people becomes harder. Attracting new ones? Even more difficult.
CEOs and boards tend to prioritize hard ROI. That’s fine, this qualifies. Structured AI training isn’t just a talent perk. It’s a competitive lever. In hiring, in innovation, and in long-term strategy. When your workforce knows how to use the tools of the future, that compounds across every project, every team, and every decision.
Alex Adamopoulos, CEO of Emergn, made it clear: “The data is clear: employees crave guidance and education to keep up with the constant pace of change… AI training… is not a nice-to-have; it’s a necessity for organizations that want to remain competitive in the war for high-performing talent.” That’s not about being nice. That’s about survival in a fast-moving business environment.
Inadequate AI training leads to significant business performance challenges
Neglecting AI training isn’t just a missed opportunity, it’s already costing companies time, people, and progress. According to Emergn’s global survey, 31% of respondents reported that digital transformation initiatives were delayed by more than six months due to a lack of proper training. That’s not theoretical. That’s real time lost on projects that should already be delivering results.
It doesn’t stop there. Failing to prepare your employees for AI is also affecting team stability and output. Twenty-eight percent of respondents saw higher employee turnover tied to insufficient training. Twenty-seven percent reported lower productivity compared to competitors and noted negative impacts on team wellbeing. Another 26% said that lack of training slowed down career advancement. In short: disinvestment in upskilling compresses forward motion across the organization.
This is more than internal inefficiency, it becomes visible on the balance sheet. When projects stall and productivity drops, it’s not just about delays. It’s about being outpaced. And it gets harder to keep your best people when they feel like they’re falling behind or being left unsupported. Executive teams focused on sustainable growth need to take these indicators seriously.
Alex Adamopoulos, CEO of Emergn, underscored this point: “People need to be positioned at the forefront of any change management initiative if you want to succeed. There is a distinct ripple effect that impacts nearly every aspect of an organization’s ability to meet goals and expectations when the well-being of its people is not central to those efforts.” He’s right. If leaders sideline training, they slow down transformation. It’s that simple.
Key executive takeaways
- Misaligned training expectations stall AI adoption: Leaders should align internally and with employees on who owns AI upskilling, as conflicting views between CEOs and staff are already delaying transformation efforts.
- Upskilling drives talent acquisition and retention: Organizations should invest in AI training programs to attract high-performing talent, as 77% of employees expect employer-led AI education and two-thirds may avoid employers that don’t offer it.
- Training gaps directly impact performance and retention: Decision-makers must treat AI upskilling as critical infrastructure, with 31% of businesses experiencing project delays and 28% facing higher turnover due to lack of training.
