TeamViewer chief predicts AI’s practical turn by 2026

TeamViewer Chief Executive Officer Oliver Steil has set out five predictions for how artificial intelligence will shape workplace technology in 2026, with a focus on return on investment, workflow design, trust, autonomy and regulation.

The company framed the outlook around practical outcomes in daily work, rather than research progress or model performance. Steil described a shift towards more targeted deployment of AI inside organisations.

Monday Morning ROI

Steil said business leaders will scrutinise AI projects through day-to-day results. He used the phrase "Monday Morning ROI" to describe a more immediate test of value.

"After years of conceptual talk about AI's promise, 2026 will be the year that business leaders shift their attention to a far more practical question: what actual value does AI deliver on a Monday morning?," said Oliver Steil, Chief Executive Officer, TeamViewer.

Steil linked that change to "agentic AI". He described it as the use of specialised agents trained on company data for narrower tasks. He gave examples such as running engineering simulations overnight and summarising insights from customer service interactions. He argued that businesses will judge these tools on productivity, quality and output experienced by teams.

Adaptive workflows

Steil said workplace systems will begin to adapt to staff, rather than the other way around. He described longstanding business processes as layered with manual steps and built around outdated structures. He said AI-driven optimisation will change how work moves through organisations.

He said tasks will re-route based on availability, context and urgency. He also said administrative work will compress in the background and that systems will coordinate with less direct human intervention. He positioned the change as a way for staff to spend more time on judgement, creativity and empathy.

Steil said organisations that recognise this transition early will redesign work around individual strengths rather than fixed processes. He described the change as a move towards a more "human-centric" era of productivity, with less time spent on the mechanics of work.

Trust focus

Steil said trust will become a differentiator in business technology as AI systems take on more autonomy. He argued that the market will place less emphasis on model speed or scale, and more on accountability and control.

"In the race to build the smartest AI, the next big competitive edge won't come from more data, faster models, or more advanced algorithms - it will come from trust," said Steil.

He said questions about control will shape adoption decisions. He pointed to design choices around data, transparency and user agency. He said some organisations will build mechanisms that give users more control over how AI gets used. He also said participation should be a deliberate choice rather than a default setting.

Steil said transparency and consent will influence whether tools become embedded in daily routines. He also said regulation will play a role as policy frameworks mature.

Towards autonomy

Steil also described an evolution in IT and business operations from reactive support to proactive prevention and, later, autonomous action. He said technology has historically helped organisations respond faster once problems appear. He said analytics, machine learning and connected intelligence will shift that model.

"For years, the technology story has been one of response. Systems existed to help humans react faster - fixing issues, closing gaps, solving problems once they appeared. But that reactive model is already being rewritten," said Steil.

He said organisations will increasingly predict and prevent issues before they occur. He also said systems will identify patterns, flag early warning signs and suggest fixes in real time. He said this approach will reduce disruptions and free time for work he described as innovation rather than maintenance.

Steil said the rise of agentic AI points to more autonomy, where systems resolve problems independently within boundaries set by humans. He said people will remain in control through goals and limits, while self-directed agents handle more day-to-day problem-solving.

Regulatory pace

Steil said AI regulation will accelerate, and he described a debate between tight restrictions and lighter oversight. He said AI remained in an experimental phase and that governance should follow practical lessons from real deployments.

"The global conversation around AI regulation is at a critical crossroads. Some argue for tight restrictions to contain risk; others advocate a lighter touch to allow innovation to flourish. The truth is, both are necessary," said Steil.

He said countries and companies that balance innovation with responsibility will set standards for the next stage of adoption. He presented this balance as a factor in whether AI becomes a sustained economic driver or another cycle of overinvestment.

"Striking that balance will determine whether AI becomes a sustained economic driver or another overhyped cycle," said Steil.