Lemonade: Is its "AI everywhere" strategy a competitive advantage?

Master AI-enabled operations: identify persistent bottlenecks, unite ops/data/IT in one hub, and design human-centered AI systems

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.

The artificial intelligence industry has spent years feathering the accelerator of frontier model development in a fierce contest to dominate the technology. Now, it is considering something that until recently seemed almost unthinkable: slamming ...

Firmenich, the Geneva-founded flavors and fragrances house, built its competitive edge on the tacit, highly specialized craft of its perfumers and flavorists – expertise sitting at the intersection of chemistry and artistry. By 2017 board-level anxiety about digital disruption, and credible signals that technology giants were eyeing the sector, forced the question of how a craft-based industry should respond to AI. Eric Nicolas, chief financial officer (CFO) and head of strategy, and Eric Saracchi, chief digital and information officer (CDIO) were charged with shaping that response. Rather than buy capability or partner externally, they chose to build in-house: d-lab, sited deliberately close to, while being organizationally distinct from EPFL's innovation park in Lausanne. The case follows d-lab from early experimentation to a string of commercial firsts: an AI-generated beef flavor launched in Asia in 2020, and an AI-created laundry fragrance in early 2021. Central to the lab's traction was a deliberate framing choice positioning AI as a creative co-pilot rather than a replacement and designed to win over skeptical, identity-invested experts whose value rested precisely on the knowledge AI now threatened to encode. By November 2021 d-lab had been named digital innovation of the year and had halved time-to-market while cutting formulation costs. The case closes on an unresolved strategic question facing Nicolas and Saracchi: how to move d-lab from proof of concept to durable advantage while deepening its integration with the wider organization, and extending its reach from formulation into molecular discovery. It offers a grounded vehicle for examining innovation-unit design, expert buy-in under AI disruption, and the governance of adjacent-but-separate digital capability.

Generative AI has made building software feel almost free. A product manager describes what she wants, an AI model writes the code, and a working tool appears in an afternoon, impressing everyone who sees it. As a result, companies and teams that ...

AI can default to measuring whatever is easiest to find and simplest for another system to score, regardless of intent. Time for some human oversight, says Robert Vilkelis.

CFOs in the AI era: design data-models and workflows that maximize value, redefine productivity, and establish transparent AI governance.

Deep learning is increasingly presented in economics as a new paradigm for solving dynamic models, superseding the classical projection methods of numerical economics. We argue that this dichotomy rests on a misclassification. The neural-network s...

On June 30, 2026, at 7:00 a.m., a coffee chain opened a store on the lower level of Grand Central Terminal in New York City. The logo on its cups was a small blue deer. A costumed mascot named Lucky was there to work up the communal crowd. First-t...