If no one at your company is complaining about AI, you're probably using it the wrong way

A surprisingly effective indicator of the success of an AI adoption strategy? The level of resistance it generates. If the introduction of AI in a company doesn’t raise any doubts or cause any friction, it’s possible that it isn’t really changing the way people work.

‍

This idea emerges clearly from the insights of Tyler Cowen, a professor of economics at George Mason University, and other experts in AI and work organization interviewed on Microsoft’s WorkLab podcast. Their starting point is clear: becoming an organization capable of using AI as a widespread and structural resource requires profound changes—not just technological ones.

‍

Reskilling: Not Just New Skills, but a New Professional Identity

Asking people to rethink their work in light of AI effectively means asking them to redefine their roles. That is why reskilling cannot be limited to just a few online courses.  

According to Raffaella Sadun of Harvard Business School, transformation must begin with a clear explanation of the “why”: why the company is investing in AI, what business goals it aims to achieve, and what kind of future it envisions for its people. Without this framework, uncertainty risks stalling change.
Many organizations focus on the tools but overlook the fundamental question: what is AI really for?

Dan Diasio, Global AI Consulting Leader at EY, emphasizes that an effective transformation requires three elements: mindset, skills, and tools. AI is comparable to training for a marathon: it’s necessary, but it’s not the goal. The key is to understand where value is created and what concrete results you want to achieve.

‍

Relationships remain a key competitive advantage

As AI capabilities continue to grow, skills such as persuasion, critical thinking, and emotional intelligence become even more crucial.  

As Cowen notes, building and maintaining a network of strong relationships becomes essential. Pascal Bornet, author and AI expert, emphasizes that authentic creativity, critical thinking, and trust are distinctly human qualities and also determine how effectively a person can work with AI agents and advanced systems.

In short, then, change inevitably causes discomfort. The more profound a transformation is, the more it reduces predictability, calling long-established habits into question.

Leaders, therefore, must learn to view discomfort as an indicator of progress. In this sense, complaints are not a failure of AI adoption but rather proof that the process is working.

‍