CIOs and CDOs everywhere are busy chasing after AI, but many are getting ahead of themselves. They’ve lost sight of a very important prerequisite—data strategy. Successful AI requires not just lots of data but lots of high-quality data built on a well-executed data strategy.
Executives and boards are frantically looking for fast AI outcomes without considering strategy. As an example, one of our customers went to their board saying they needed some budget to build a data platform. The board said that although they didn't have money for data projects, they had unlimited funds for AI innovation. So the customer changed the proposal title, went back to the board and said,"I need to build an AI platform.
AI and ML are synergistic results of a well-executed data strategy where governance, lineage, access and data integration all work in harmony. They’re not independent strategies that come together at a later date. If you have two different data stacks, you’re going to be building governance twice. Using this complicated approach, you’ll probably work twice as hard to make it work. Worse, you’ll likely need to rebuild it all before you can jump ahead to AI.