AI Is Only as Good as the Data Behind It

Everyone wants to talk about what AI can do. Fewer people want to talk about where it gets its data, who maintains that data or whether anyone can find the latest version of it. Fair enough. Data management is not the flashy part. It is, however, the part that keeps the flashy part from confidently getting things wrong. This interesting topic came to us from Gov Insider in their article, “Why AI governance starts with data management.”

Data management covers the everyday work of collecting, organizing, storing and making data usable. When that work is done well, artificial intelligence (AI) has a better chance of finding relevant information and producing useful results. When it is done poorly, an AI system may pull from outdated records, duplicate information or missing context. A polished answer can still be a wrong one.

That is where data governance comes in. Governance sets the expectations: Who owns the data? Who can access it? How should it be used? How do we know it is accurate? Data management puts those expectations into practice through processes people actually follow.

The two need each other. A governance policy that nobody carries out is just a document. A well-organized collection of data without clear rules can create its own problems, especially when AI makes that data easier to search, combine and share.

Before an organization asks what AI tool it should buy, it is worth asking a less exciting question: Can we trust the data we are about to give it? The answer may save a lot of cleanup later.

The future of AI depends on how content is prepared today. Access Innovations partners with organizations to turn metadata, semantics and structure into AI-ready infrastructure that protects meaning and enables confident innovation.

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Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, uniquely positioned to help you in your AI journey.