2026 Predictions from TeamViewer CEO Oliver Steil

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? The next phase of AI maturity will be measured not by research breakthroughs, but by daily relevance - the tangible impact on productivity, quality, and output that teams experience at work.

Agentic AI is making this shift possible. Instead of generic, open-ended models prone to hallucinations, organizations are deploying specialized agents trained on company-specific data to perform focused, high-value tasks. Whether it’s an agent running hundreds of engineering simulations overnight or summarizing insights from customer service interactions, AI’s new utility is grounded in specificity. The broad ambition of the past few years is giving way to targeted efficiency, and 2026 will be the moment ROI shows up not in theory, but in the real world.

 

For decades, people have had to adapt themselves to the way work is structured, navigating outdated processes and systems, and layers of manual steps that slow everything down. In 2026, that relationship flips. With the rise of agentic AI and continuous optimization, workflows will begin adapting to people in real time. Tasks will re-route automatically based on availability, context, and urgency; administrative work will compress silently in the background and systems will coordinate themselves so humans can focus on the parts of work that actually require judgment, creativity, and empathy.

The most successful organizations will be those that recognize this shift early: work becomes something that shapes itself around people’s strengths rather than forcing everyone into the same process. Instead of humans working for the workflow, the workflow finally starts working for them. It marks the beginning of a more frictionless, human-centric era of productivity – one where employees feel less drained by the mechanics of work and more energized by the meaning of it.

In the race to build the smartest AI, the next competitive edge won’t come from more data, faster models, or advanced algorithms — it will come from trust. As technology becomes more autonomous and integrated into daily business, a key question arises: who’s really in control?

This question is prompting the tech industry to pause and reflect. After years of prioritizing speed and scale, the focus is shifting to responsibility — how systems are designed, the data they rely on, and transparency. Forward-thinking organizations understand that adoption must be earned, not assumed. They are creating mechanisms that give users real control over AI, making participation a conscious choice, not a default.

Trust now underpins technology itself, influencing data collection, system explanations, and user control. As AI moves into daily work, transparency and consent will determine which tools last and which fade away.

When hype diminishes and regulation advances, one thing remains clear: trust takes time to build, but once earned, it becomes the most lasting asset in technology.

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. We are still in the trial phase of AI: experimenting, learning, and understanding how it behaves in real-world contexts. The control phase must follow, informed by those lessons rather than shaped by fear.

Striking that balance will determine whether AI becomes a sustained economic driver or another overhyped cycle. The nations and companies that figure out how to balance innovation with responsibility will set the standard for responsible progress in the years ahead.