Research

Legacy systems carry data and operational stability. Reconfiguring them can open new paths for digital renewal.

Connected products can inform, recommend, or act. Our taxonomy shows how service outcomes, users, and technical capabilities fit together in business-to-business settings.

Keeping components in use requires a shared view of their history. Our study works backward from a circular automotive industry to identify the data, agreements, and investments that would make it possible.

Human and AI capabilities can be combined in different ways. Our framework explains how shared resources and rules shape this collaboration in service ecosystems.

An AI pilot needs people who can take responsibility for it in daily use. We examine how that responsibility stays with technical teams or business functions, or moves between them as a project enters production.

Sharing data connects technical choices with organizational structures and relationships between firms. Our taxonomy helps explain how these choices fit together.

We built a mechanism that ranks data sources and tests what each adds to a prediction. It helps buyers compare data bundles against their budget before acquiring them.

AI coaching should help founders question assumptions and develop their judgment. We translate these needs into design requirements that preserve founders’ control over decisions.