The end of AI theatre – why 2026 will be defined by AI impact, not inputs

From concept to reality, AI has been implemented far and wide, with three quarters of UK businesses already using it to power their operations.

Despite this widespread uptake, AI’s true impact is lagging. Two out of three companies are still in the initial adoption phase, and enterprise-wide scaling is yet to take off.

Across industries, businesses are still very much stuck in the onboarding phase, with the prospect of an AI bubble bursting putting the pressure on for tangible results. Calls for clear proof of return on investment are amping up, and, in 2026, organisations must move beyond strategy by putting AI into action with clear, measurable outcomes.

A shift in mindset is required for organisations to fully harness AI. Making this transition requires laying a strong foundation. This includes reforming how AI is perceived and treating it as a collaborative teammate in the workplace. To unlock its true value, organisations must rethink workflows, foster a culture where AI is used meaningfully every day, and establish clear measurement frameworks to track impact.

AI boosts personal productivity but undermines teamwork

Despite the claims of AI grandeur, most companies are yet to realise meaningful organisational gains from AI. Whilst the early adoption signals are positive - AI usage has doubled in the last year and workers report that it is making them 33% more productive - almost all (96%) companies that are making significant investments have not seen dramatic improvements in organisational efficiency, innovation or work quality.  

This is largely because there is an overemphasis on AI-enabled personal productivity instead of team productivity. According to Atlassian research, 76% of executives see increased employee productivity as the number one indicator of whether their AI investment is paying off. But organisations hyper-focused on personal productivity as the main AI outcome are 16% less likely to drive innovation compared to those focused on coordination.  

AI may increase the speed of personal work, but this does not guarantee that the right things are being worked on. If teams are not aligned, they may just be accelerating in the wrong direction.  

Shifting the measure from usage to teamwork

This is why organisations need to look beyond individual usage measures, instead focusing on team impact. Companies focused on AI-enabled coordination are nearly two times as likely to say that AI has significantly transformed organisation-wide efficiency. As scepticism about an AI bubble grows, organisations will increasingly be judged on AI’s impact on collective outcomes, not on how many employees are using it. 

By shifting success metrics toward how effectively AI accelerates teamwork, alignment and decision-making, organisations move closer to the frameworks required for true enterprise transformation, rather than celebrating activity without results. 

Disorganised workflows are AI’s biggest obstacle

The organisations that successfully bridge the gap between individual productivity and company-wide impact are those that build a company-wide knowledge base, establish the right systems and weave AI directly into team workflows. 

The following actions enable AI to become the connective layer across an organisation, bridging silos, driving action on the right context and aligning everyone around shared goals.  

Build a connected company knowledge base 

AI can only action what it can access. Organisations need to break down data silos and ensure their data is accurate, diverse, and up-to-date. The teams that see the greatest AI-enabled impact enable AI to operate where employees are, within existing workflows.

Our research shows that teams with transparent ways of working and connected data see better AI outcomes. To do this, leaders must ensure they are investing in enterprise-ready AI that empowers IT admins to decide exactly what data AI has access to and who can use it. This access can be adjusted for different teams or departments with the appropriate data security clearance.

Aligning work to goals  

At the same time, by establishing connected frameworks, leaders can ensure that AI understands where teams should be headed, keeping them on path and helping them get there faster.

This starts with setting three to five clear goals per team, defining what the team wants to accomplish and how they will know if they have succeeded.  

When AI knows every goal, it can drive teamwork in the right direction, quickly flagging duplicative work and connecting the right people, projects, and knowledge. 

Make AI part of the team  

True AI transformation can only happen when every single team member knows how to weave AI into their workflows. While roughly half of executives and teams work with AI throughout the day, over a third of executives and nearly half of knowledge workers use it only a few times per week or less.

Culture ultimately drives progress. To unlock the full value of AI, teams must have the freedom to experiment with their AI teammate. Our research shows that the companies that empower every team to use AI, even if their strategy isn't set in stone, are twice as likely to make innovation gains than companies that are slower at adopting AI.

At the same time, effective collaboration requires thoughtful human oversight. AI’s speed must be paired with seasoned operators who set direction, monitor outputs and manage risk. Human beings should always remain in the loop, with AI acting only as a collaborator.  

Moving from AI spectacle to impact

AI has the potential to fuel stronger teamwork next year, but only if companies put in the right groundwork. Organisations see real results when AI is treated as a strategic partner, integrated with existing systems, and made available to all employees.

In 2026, the spotlight moves from surface-level adoption to clear results. If AI’s impact on teamwork and decision-making isn’t measured, the investment isn’t working. Success will belong to the companies that assess AI’s impact on collaboration and use those insights to drive tangible outcomes.