Worth Reading – AI agents are only as good as the data they’re given, and that’s a big issue for businesses
I’ve been rethinking how to approach information governance recently, and the article below relates to my new approach:
There is, however, a disconnect in business — although businesses report using data more, technical leaders have reservations, with nearly two-thirds (63%) agreeing their companies struggle to drive business priorities with data. Data and analytics leaders estimate that 26% of their organizations’ data is “untrustworthy.” And 42% of business leaders said their data strategies don’t fully align with business objectives.
For a long time, I tried to communicate the need to delete old, worthless, and incorrect data due to the costs of storing it and the legal risks of having to review it during litigation. Those are real risks, but can also represent small or theoretical risks, rather than the kind that puts this at the top of a priority list.
In the age of AI, though, this might be the high-priority risk. That old, untrustworthy, and outdated information that no one ever bothered to clean up is actively messing up your AI implementation. Your attempt to be a data-driven business depends on having accurate data. That becomes difficult to do when you’re not actively cleaning up after yourself.
Data governance is in the spotlight because it’s one of the key ingredients for AI technology to succeed. As we move from AI chat to agents, we’re being asked to trust that the agent will carry out tasks correctly, at least most of the time. Hand it incorrect data, and there’s little chance of that happening.
It’s time to get your data in order.
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