Most CEOs are treating AI as a tool to buy rather than a capability to build. New Vistage research found that while 82% of CEOs and 80% of leadership teams use AI.

Yet our March 2026 survey found that only 22% of CEOs have a comprehensive AI governance policy, and another 21% have an informal or partial one. Even among companies with a comprehensive or partial policy, just 42% of CEOs provide training on AI use or policies.

Without deliberate training, employees are left to figure it out for themselves. That reveals a fundamental misunderstanding of what operationalization really requires.

This is not a minor oversight. It’s important to understand that using AI is not the same as leveraging AI. When knowledge workers simply transition their traditional browser behaviors to AI, they’re just getting a smarter search with results that require less reading. Advanced competency is a must for building prompt skills, importing proprietary data for analysis, or developing business plans.

Most organizations treat AI adoption as a technology purchase when it’s really an execution problem. The gap between tool deployment and actual capability is where competitive risk lives.

From “What Can AI Do?” To “How Do I Operationalize AI?”

In 2025, the question for CEOs and business leaders was: what can AI do to transform business? Now, the question is operational. The shift signals that CEOs have moved past novelty into business reality.

But adoption is outpacing AI competency at large. Individual workers will figure out AI applications in their own workflows long before workgroups redesign processes around AI. Business transformation remains elusive and difficult. The space between how fast AI is being deployed and how well people are actually using it is widening.

Building a Comprehensive AI Training Strategy Requires 4 Components

AI training should not be a one-and-done approach. Rather, it’s a series of activities that must be continually updated, upgraded, and maintained as the organization evolves. Training programs should take on multiple forms, including structured individual training, external or vendor-based training, and self-directed and peer learning.

Here are the 4 interconnected components that must be part of every AI training strategy.

1. Governance and Approved Tools

This is the starting point. Establish governance protocols around security, appropriate use and, most importantly, a common set of tools. If every employee uses a different AI platform, then everyone speaks a different language.

The benefit of having common tools is common language, skills, protocols and approach to utilizing the tools. Training on AI policies, data privacy, security and appropriate use is essential for effective AI use — and for protecting the organization from the downsides of unauthorized use.

2. Skill Development

Moving employees from browser behavior to real AI fluency drives individual productivity — and that scales. The teaching philosophy is simple: teach them how to fish and see what they catch.

Start with workshops, power-user programs, lunch-and-learns, internal academies and vendor-specific instruction. Most employees don’t need to build bots or write code. But they do need to move from treating AI like a search engine to building prompt skills, importing data for custom analysis and designing workflows that solve real work problems.

That’s the fastest path to organizational productivity gains.

3. Collaboration and Peer Learning

People learn by doing, experimenting, and sharing what works. When teams operate in a common toolset, learning accelerates. Employees can replicate successful use cases and individual wins can compound into collective capability.

This also plants the seed for transformation at scale. Those who are skilled and knowledgeable about AI will be the ones who help develop, design, implement, and operate the AI systems the organization builds next.

4. Embed AI Skills in Hiring

AI skills must be a baseline requirement for knowledge workers — equivalent to computer literacy. According to the Q1 2026 Vistage CEO Confidence Index:

• Only 6% of organizations list AI skills as required in job postings, while another 6% prefer and formally evaluate them.

• Only 21% assess AI skills informally.

• About 1 in 3 (34%) are figuring out how to incorporate it into hiring

• Nearly 4 in 10 (39%) don’t consider AI skills at all in hiring decisions.

Organizations cannot afford to hire workers who can’t function in an AI environment. The risk of hiring digitally impaired workers is that they’ll constrain the entire organization’s ability to transform.

Why This Matters for Retention

Digitally engaged workers are the most desired in the labor market. Employees looking to change jobs will seek environments where AI is central to the organization’s work. They want to develop and use their skills. Current employees want to do the same thing. They’ll stay in organizations that invest in their AI development — or they’ll leave for organizations that do. This reframes training spend entirely from an HR cost to a retention tool.

AI is no longer something to be left to individual workers to figure out on their own. It’s a mission-critical business tool for every knowledge worker. Organizations that are building training infrastructure now and operationalizing AI will compound their advantage with every planning cycle. Those treating it as an afterthought will find themselves playing catch-up, if they’re not already.

Employees won’t wait for perfect clarity on AI’s role. The question for CEOs is whether that skill development happens inside or outside the organization.

This first appeared in Inc.