TeamViewer CEO shares insights on AI’s impact for Washington Post report

A new report published by The Washington Post, in partnership with Investment Reports, examines one of the biggest questions facing businesses today: How can organizations turn rapid AI adoption into measurable business value?

Beyond the Breakthrough: AI’s Real Impact draws on more than interviews with business and technology leaders, including TeamViewer CEO Oliver Steil, to explore what separates successful AI implementations from those struggling to deliver returns. It finds AI value depends less on having the latest technology and more on building the right foundations around it, from data and governance to workflows, skills and trust.

Below is a look at Oliver’s contributions to the report, as well as his full interview with Investment Reports, in which he shares how TeamViewer is using AI to reduce digital friction and help organizations move toward more autonomous IT operations.

At a glance: What does it take to turn AI into business value?

Oliver’s perspective centers on a few key principles:

• Start with the business outcome, not the AI technology. Organizations should first identify the process they want to improve, define what success looks like and set ambitious performance targets. Only then should they determine how AI can help achieve them.
• AI is already moving beyond experimentation. Across industries, businesses are finding concrete applications for AI — from software development and engineering to sales, marketing and frontline operations — that improve productivity, quality and speed.
• Operational data can create a continuous learning loop. At TeamViewer, AI can learn from how IT issues are identified and resolved, turning those insights into repeatable automations that help predict, prevent and resolve future incidents.
• Agentic AI changes what organizations can delegate. Instead of prompting AI through every individual step, employees will increasingly be able to assign AI agents broader responsibilities and focus on the outcomes, while people oversee and guide their work.
• Trust is essential to greater autonomy. Enterprise adoption will happen gradually as organizations address data, security and process complexity. As businesses gain confidence in proven automations, they can become more comfortable delegating larger parts of their operations to AI. TeamViewer explored this topic in greater detail in our research report, Path to the Autonomous Workplace.

How is TeamViewer putting AI into practice?

As Oliver explained in his full interview with Investment Reports, TeamViewer’s evolution from remote connectivity to digital workplace management has created a foundation for AI-powered automation.

Today, tens of thousands of TeamViewer customers are actively using AI capabilities to analyze remote sessions, identify patterns and generate operational insights. Those insights can help organizations automate repetitive processes, reduce resolution times and prevent support issues from recurring.

Most organizations already have the answers to many of their recurring IT issues. The challenge is that those answers are often buried in tickets, support sessions, and individual experience. TeamViewer's focus is on helping companies turn that day-to-day problem-solving into something they can reuse, whether that's recommending the next best action, automating a routine fix, or preventing the same issue from affecting other employees.

The longer-term opportunity is autonomous endpoint management: creating an automation library based on an organization’s own trusted operational data and allowing AI agents to take responsibility for more IT tasks over time.

As Oliver told Investment Reports, AI agents can ultimately operate more like digital members of a team — owning defined responsibilities while people continue to coordinate, supervise and manage exceptions.

What should business leaders prioritize with AI?

For Oliver, the answer comes back to outcomes.

Rather than asking where an organization can deploy AI, leaders should ask what meaningful improvement they want to achieve. Whether the goal is faster IT resolution, better sales conversations or more efficient engineering, clearly defining the desired result gives employees a reason to embrace AI and provides the organization with a concrete way to measure its impact.

That shift, from adopting AI to redesigning work around what AI can help accomplish, is also at the heart of Beyond the Breakthrough. The next phase of enterprise AI will not be defined by who experiments the most, but by who can translate the technology into trusted, repeatable and measurable outcomes.