Most senior leaders will tell you their organisations are actively embracing AI. And they genuinely believe it. New research from AI upskilling platform Multiverse, published in March 2026, surveyed 810 technology leaders and 1,190 employees across the UK and the United States, and the picture that emerges is one of real ambition, real momentum, and a practical gap between the two that, once understood, is well within reach of being closed.
Some 59% of leaders believe their teams collaborate with AI on a daily basis, and that confidence is not unfounded, because adoption is genuinely growing across all levels of the workforce. Where the research adds nuance is in showing that employees report a somewhat lower rate of daily use, at 42%, which means the strategies and investments being shaped at the top can now be refined with a clearer picture of where people actually are.
A closer look at where AI is taking hold
When the data is broken down by specific use cases, it becomes clear that AI is already being put to work across a wide range of tasks. Leaders report strong belief in adoption across automation, data analysis, and process optimisation, all areas where AI can deliver measurable efficiency gains. The research usefully highlights where perception and frontline experience diverge, giving organisations a precise starting point for closing the distance.
On task delegation, for instance, 23% of CEOs believe their employees are already handing entire tasks over to AI autonomously, while 8% of employees report doing so. This highlights to a clear and near-term opportunity, that the infrastructure of expectation is already in place, and building the skills to meet it is a question of structured investment rather than cultural change from scratch.
The untapped potential in junior teams
One of the most forward-looking findings in the research concerns the variation in AI adoption across seniority levels. Mid-level workers are already engaged, with 52% reporting daily AI collaboration, and 48% of middle managers similarly active. The area with the most room to grow is among junior employees and individual contributors, where daily usage sits at 21% and 20% respectively.
A 30 percentage point gap between the most and least senior employees is, looked at another way, a significant pool of untapped potential. Junior employees make up the majority of most organisations, and equipping them with the same AI capability that their more senior colleagues are already using is one of the most direct routes to scaling the productivity gains that leaders are expecting. The ceiling here is high, and the foundations are already in place at the levels above.
Why structured training changes everything
The single factor that connects most of the gaps in the data is the absence of structured training, and it is also the most straightforward to address. More than half of senior leaders (55%) have received fewer than five hours of formal AI training from their organisations, and 58% have been supplementing that with informal experimentation using tools like ChatGPT. The appetite to learn is clearly there. What is needed now is a framework that channels it more effectively.
Around half of both leaders and employees point to mindset and resistance to change as barriers to wider adoption. This is encouraging context rather than a cause for concern, because mindset shifts most reliably when people are given clear, relevant, and well-supported learning experiences. Organisations that have invested in structured AI training report considerably stronger engagement, and the evidence from Multiverse’s own learner base bears that out.
“AI is not a monolithic tool, and its application varies wildly between a junior developer, a middle manager, and a CEO. The 30% gap in adoption we see between seniority levels is a clear signal that the one-size-fits-all approach to AI is failing. To bridge this divide, businesses must move beyond generic training and implement custom AI upskilling paths tailored to the unique daily workflows of every individual.”
Gary Eimerman, Chief Learning Officer, Multiverse
A workforce ready to move
Perhaps the most compelling finding in the entire study is the degree of alignment between leaders and employees on what comes next. Some 85% of leaders and 78% of employees agree that more frequent training is essential to keep pace with the current rate of AI development. Across seniority levels, across functions, the workforce is pointing in the same direction. That kind of shared readiness is a strong foundation to build from.
Multiverse has partnered with more than 1,500 companies to build applied learning programmes in AI, data, and technology skills. Its learners have collectively generated more than two billion dollars in measured return on investment for their employers, demonstrating what becomes possible when structured, role-specific development is given the priority it deserves.
How to build on this
The most effective starting point is a clear-eyed audit of how AI is currently being used across the organisation, gathered from the ground up rather than inferred from leadership assumptions. Anonymous surveys or structured conversations with line managers can quickly reveal where adoption is strongest, where confidence is lower, and which teams are ready to move faster with the right support. That picture is the foundation everything else is built on.
From there, the priority is replacing broad AI awareness programmes with training paths designed around specific roles and workflows. A junior analyst and a chief operating officer have different daily realities, and the AI skills most relevant to each of them look quite different. Role-specific learning is what takes adoption from a leadership-level activity and distributes it across the full organisation, which is where the compound returns begin to accumulate.