A new global CEO study has found that artificial intelligence is forcing companies to rethink not only their technology plans, but also the structure of leadership teams and the skills employees need to stay effective at work.
Released on May 4, 2026, the annual study surveyed 2,000 CEOs across 33 countries and found that business leaders expect a major wave of workforce transformation between 2026 and 2028. The findings suggest that AI adoption is moving from experimentation into a deeper phase where job roles, leadership responsibilities, and employee training plans are being redesigned at the same time.
The headline finding is the scale of the skills shift. CEOs expect 53% of employees to need upskilling to perform their current roles more effectively, while another 29% will need reskilling for different roles. Together, that means roughly eight in ten workers could face some form of skills change within a two-year window.
The study reveals a major gap between CEO confidence and actual workplace behavior. While most CEOs believe their employees have the ability to collaborate with AI, only about 25% of the workforce is currently using AI regularly as part of their job.
That is the real readiness problem. Companies may have access to AI tools, and employees may understand them in theory, but regular use inside daily workflows remains limited. For CEOs, the challenge is no longer just buying or deploying AI systems. It is getting people to adopt them properly.
A large majority of CEOs also believe human adoption is the main factor that will determine whether AI projects succeed. That shifts the focus from technology availability to workplace habits, training, trust, and confidence.
In other words, the AI bottleneck is not only the model. It is the employee sitting in front of the tool.
The study also shows that the next wave of AI skills is not limited to coding. Most workers will meet AI inside tools they already use, including productivity software, customer service systems, sales platforms, analytics dashboards, HR tools, finance software, and development environments.
That means the most urgent skill is practical AI literacy. Employees need to know how to write better prompts, give useful context, check whether an AI answer is reliable, and decide when a human should step in.
These are everyday workplace skills, not just technical specialist skills. A marketer may use AI to draft campaign ideas. A sales team may use it to summarize customer conversations. A manager may use it to review team reports. A finance worker may use it to analyze numbers and prepare summaries.
In each case, the value depends on whether the employee can guide the system and judge the result. AI access alone does not create productivity. Skill does.
The study also points to a major shift inside the C-suite. A growing number of companies now report having a Chief AI Officer, a role that has become far more common as AI moves into core business operations.
The rise of this role shows that companies are treating AI as a strategic function, not only a technology project. AI now affects product planning, customer support, risk, compliance, marketing, operations, HR, and finance.
Human resources leaders are also becoming more important. If more than half of employees need upskilling and nearly a third need reskilling, workforce development becomes a central business issue. CEOs increasingly expect HR leaders to help redesign roles, build training systems, and prepare employees for new AI-supported workflows.
At the same time, technology and talent leadership are beginning to merge. Functional leaders are expected to understand how AI changes their own departments. A finance chief, sales head, operations leader, or marketing director may not need to become an engineer, but they do need to understand how AI changes decision-making and execution in their domain.
The pressure is expected to grow by 2030. CEOs predict that AI will make a much larger share of operational decisions within the next few years, rising from a supporting role today to a more autonomous role in business workflows.
That could affect pricing, supply chains, customer service, hiring processes, compliance checks, reporting, and marketing operations. As AI takes on more decision-making, companies will need stronger oversight, clearer accountability, and employees who understand how to work with automated systems.
For workers, the message is direct: AI literacy is becoming a core career skill. Employees who learn how to use AI tools confidently, verify outputs, and apply them to real business tasks will be better prepared than those who wait for change to happen around them.
For companies, the lesson is equally clear. AI transformation will not succeed through tools alone. It needs training, leadership alignment, and a workforce that knows how to turn AI from a feature into daily value.
The study shows that the next phase of AI at work will be defined less by who owns the best technology and more by who can help people use it well.
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