Data Governance - The AI Prerequisite

I’ve talked to a lot of people recently about their desire to implement AI to help with automation and decision making.  Their problem?  They still can’t do the basics like counting customers (i.e. consumer, patient, provider, student, etc.) or widgets (i.e. product, sale, opportunity, etc.).  The reasons are plentiful but can usually be traced back to key terms not being consistently defined, data that is not trusted, or data that lives in so many places it is hard to pull together in a desktop tool like Excel.  In other words, basic components of data management. 

So, how can you trust an AI model if you don’t understand, trust, or have access to the data that feeds the model?  You can’t.  That’s why data governance is important - it introduces oversight, discipline, and communication into data management processes that that make data governance a key enabler for any AI undertaking.