Alex Singla
McKinsey commentary
Senior partner and global coleader of QuantumBlack, AI by McKinsey
We’ve learned a lot about generative AI over the past two years. But perhaps the most important lesson is this: It pays to think big. The organizations that are building a genuine and lasting competitive advantage from their AI efforts are the ones that are thinking in terms of wholesale transformative change that stands to alter their business models, cost structures, and revenue streams—rather than proceeding incrementally.
Our experience helping organizations create and deploy gen AI systems also shows that it pays to be ambitious from the outset—pursuing end-to-end solutions to transform entire domains, rather than taking a piecemeal, use-case-by-use-case approach. Beginning with an overarching, enterprise-level transformative vision opens up possibilities down the line. That’s because a clear picture of where you’re going influences the data you capture and the models you build. You’re thinking about things like access control; security; reusability of code at the front end, not as an afterthought; and creating a foundational infrastructure that is well beyond any individual use case or domain. This allows further functionality to be deployed faster and more cheaply than if you go use case by use case—which, in turn, becomes a competitive advantage that others will have a hard time keeping up with.
Transformative thinking also forces the CEO and top team to be aligned—something that use case thinking does not. This is critical because successful transformations require siloed parts of the enterprise to come together in a single orchestrated effort—and that can typically only happen when the CEO and other top leaders are involved.