Who would have guessed that the foundation for the generative AI explosion of 2023-24 would have been laid all the way back in 2018? At the time, there were already common themes among leaders in AI augmentation for data and analytics. At that time, there were clusters of successful AI enablement in business intelligence, analytics, data engineering, and metadata services. AI was already empowering dozens of different kinds of recommendations and automations, as well as, natural language queries and explanations.
In 2023-24, after sitting through dozens of briefings and demos on the use of generative AI in data and analytics platforms, I noticed a trend. Most of the demos focused on the AI enablement that had already been in the market for the previous five years or more. Most of the vendors simply tacked generative AI onto their existing platform; and the result was underwhelming for anyone who understood what was already being done with AI.
I noticed a second trend. The vendors with the most impressive use of generative AI were the same vendors that I identified as leaders and innovators in the use of AI and ML all the way back in 2019. As I dug deeper into the most impactful use of generative AI in data and analytics platforms, I discovered five foundational software design priorities that made the difference in impact: active metadata, business semantics, technical feedback, human feedback, and a central AI engine.
If you are making decisions on how to enable the use of generative AI in your data and analytics organizations, especially if you are making new purchases, read the Ferraro Consulting POV paper by John Santaferraro and Amit Soni, Senior Product Manager at Google, Unleashing the Power of Generative AI for Data and Analytics. Discover how a simple checklist can guide you to the best of the best in the use of generative AI for your data, analytics, and AI organization. The impact on your business will be transformative.