When thinking about S&P’s data estate, I see a hierarchy of AI defensibility. At the top is data that you alone create and wouldn’t exist without you, like a credit rating. Below that is data obtained through private sources, like the loan price data that S&P gets fed to it from dealers or shipping data sourced through bespoke commercial agreements. Further down still are curation activities – like entity matching and de-duplication, and data normalization – which I see as jobs that AI will eventually perform better and cheaper than any human team. I don’t consider those capabilities a moat long-term. What does matter at that layer, however, particularly in compliance or regulatory driven domains, is governance infrastructure and SLAs. Where S&P controls the chokepoint, whether in the form of proprietary or near proprietary data or contractual assurances that clients cannot do without, AI should be a source of leverage rather than fear.