TeamViewer’s Chief Product and Technology Officer, Mei Dent, has launched a new LinkedIn newsletter, “Mei’s Innovation Log” sharing her perspective on how enterprises can design human-centered, AI-powered systems at scale. In the series, Mei will draw on her experience leading global product and engineering organizations and reflect on how emerging technologies are reshaping enterprises and the way we work.
The first edition, The shift from AI ambition to AI infrastructure, focuses on a growing inflection point for enterprise AI. After several years of pilots, proofs of concept, and standalone AI tools, organizations are now under pressure to operationalize AI in ways that deliver durable, measurable impact. According to Mei, success in 2026 will depend less on experimentation and more on the foundations that allow AI to scale responsibly.
Key insights from the first edition include:
- 2026 marks a shift from AI ambition to operationalization. Many organizations have invested heavily in pilots and AI-powered assistants, building familiarity and delivering modest productivity gains. The next phase requires moving beyond experimentation to integrated, productive usage at scale.
- Fragmentation is becoming a limiting factor. Layering AI tools onto cluttered systems increases complexity, slows productivity gains, and raises governance, security, and compliance risks—especially as AI pulls data across departments.
- AI should be treated as infrastructure, not a feature. Enterprises that embed AI into core platforms and operating models gain a competitive edge over those deploying disconnected tools.
- Governance enables scale rather than slowing it down. Strong governance, transparency, and data lineage may seem like barriers to speed, but they become enablers of trust and expansion as AI systems grow more autonomous.
- The digital workplace is already reflecting this shift. Organizations are asking for embedded intelligence within secure, connected ecosystems—supporting proactive and predictive IT operations rather than isolated AI features.
In future editions, Mei will explore topics such as AI governance, leadership, and human–AI collaboration, drawing on her observations, research, and conversations with IT and business leaders navigating the next phase of enterprise technology.
Subscribe to Mei’s Innovation Log on LinkedIn to follow the series and join the conversation on how AI is shaping the future of work.