AI is everywhere – where are the profits?

Companies are spending billions on artificial intelligence. But are they making any money from it? IMD's Karl Schmedders on hidden costs, vibe coding and how companies can turn AI into business value.
A new Gartner survey finds that only 13% of technology leaders report significant or transformational value from AI. Meanwhile, employees are building their own AI-powered tools, companies are struggling to turn prototypes into dependable products, and investors are starting to question the economics of the AI boom. So are companies investing in genuine transformation — or expensive experiments? And what happens when AI tools that appear to work turn into costly liabilities?
In this episode of What Matters Most, Tim Quigley speaks with Karl Schmedders, Professor of Finance at IMD, about the economics behind the AI boom. Drawing on new Harvard Business Review research involving 11 companies, Schmedders warns that “initial success can be sort of very attractive, but then really turn into a problem.” He challenges executives to rethink their approach: “you don't want to do AI.” Instead, “start with a real pain, a real issue”. From shadow AI and corporate governance to the mounting financial pressure on tech giants, this conversation explores what leaders can do to turn technological promise into measurable business value.
What Matters Most – the new podcast by IMD
The most important questions facing leaders today deserve more than headlines. Every week, IMD professors Hana Milanov and Tim Quigley invite faculty and voices beyond the campus for a cutting-edge conversation, helping leaders understand what is changing, why it matters and what to do about it.
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Meet this week's guest

Karl Schmedders (imd.org/faculty/professors/karl-schmedders) is Professor of Finance at IMD in Lausanne, where he directs the Strategic Finance program. Trained in operations research at Stanford University, he previously taught at Northwestern University's Kellogg School of Management and the University of Zurich. His research applies economics and finance to decisions under uncertainty, capital allocation, artificial intelligence and climate change. His recent work, published in Harvard Business Review, examines why companies struggle to turn promising AI-built software prototypes into reliable business tools.