Analysis · Business
AI Service Growth Depends on What Can Be Reused—and What Must Change
By AWEI · AI-compiled · Published · Analysis prepared · 1 source · doi.org
A system for managing underground mine traffic may also help map the mine. In a 2021 study, the manufacturer given the pseudonym Rockcorp described this additional capability of its AI application. The paper does not establish that the mapping service was deployed. But the example raises a useful growth question: how much of the next offering is already built?
David Sjödin, Vinit Parida, Maximilian Palmié and Joakim Wincent explored six large, globally active Swedish industrial manufacturers and their partners. They compared interview themes with company reports, agreements and project documents, developing a framework for expanding AI services. This was an exploratory case study, with no experimental test of whether reuse improved profits.
The interviews revealed a tension between customization and expansion. Customers needed services suited to their particular operations; providers wanted components that could serve multiple customers. Interviewees described modular design as a way to address both: separate functions could be adapted and combined into different offerings. Customer-specific development could therefore supply ingredients for a wider portfolio.
That possibility remained distinct from demonstrated expansion. Solutioncorp described transferring applications across industries and customer segments as a goal, while acknowledging that adaptations would be required. Designing toward that goal encouraged flexibility from the outset. Elsewhere, interviewees emphasized the operational knowledge needed to define models and the staff needed to check their predictions against real events.
The authors proposed that customer use, technical refinement and new service combinations could reinforce one another. These links are interpretations of case evidence, not established causal effects. The firms were deliberately selected for existing AI capabilities and successful customer collaborations. Their experience cannot establish typical returns or show that smaller firms and consumer businesses would follow the same path.
For industrial service expansion, the practical distinction is between a reusable capability and a deliverable offer. A promising second use still leaves questions about data access, adaptation, operational validation and delivery responsibility. The study makes those questions visible; it does not show that adding another service necessarily adds profit.
Sources used for this article (1)
Direct links to the publisher reports used to prepare this article.
- Source 1
- How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops David Sjödin, Vinit Parida, Maximilian Palmié …
