Most corporate transformations start with a plan: fixed goals, a timeline, financial targets. Evgeny Kaganer and Christoph Loch of IESE Business School argue in Harvard Business Review that this is where many of them go wrong.

The reason, in their words: "As the environment changes—because of technological disruption, for example, or new customer expectations—those assumptions quickly become obsolete."

Their alternative treats transformation as a learning journey, with strategy that evolves through experiments. They sort the work into four kinds of initiatives: pilots that test new approaches, options that build future capabilities, improvements to the established business, and new ventures. Three leadership practices hold the whole together. The authors contrast the experiences of DBS Bank and GE to show the difference.

The argument lines up well with what research on AI adoption keeps finding. In the Boston Consulting Group experiment by Fabrizio Dell'Acqua and colleagues, published this year in Organization Science, AI raised consultants' output on tasks inside its capabilities and lowered accuracy on a task just outside them. The line between the two was hard to see in advance — it is something a team discovers by testing.

The startup experiment by Hyunjin Kim, Dahyeon Kim and Rembrand Koning points the same way. Firms that searched more widely for uses of AI found more of them and grew faster. Search is a learning activity, and it thrives when every pilot is allowed to teach something, whatever its outcome.

For those of us in learning and development, the framework is familiar territory. Pilots, options and ventures are experiments, and experiments produce learning when someone captures it and feeds it back into the next decision. Maybe a question for all of us: who in our organization writes down what the last pilot taught?

Talent Takeaway

Give every pilot a learning owner and a date. Before it starts, write down what you expect; afterward, write down what happened and what changes. That record is what turns a set of projects into a transformation.

Read the original at Harvard Business Review

Sources

Kaganer, E., & Loch, C. (2026). Transformation should be a learning journey. Harvard Business Review, September–October 2026. https://hbr.org/2026/09/transformation-should-be-a-learning-journey

Dell'Acqua, F., McFowland, E., III, Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2026). Navigating the jagged technological frontier: Field experimental evidence of the effects of artificial intelligence on knowledge worker productivity and quality. Organization Science. https://doi.org/10.1287/orsc.2025.21838

Kim, H., Kim, D., & Koning, R. (2026). Mapping AI into production: A field experiment on firm performance [Working paper]. SSRN. https://doi.org/10.2139/ssrn.6513481