Video produced by Steve Nathans-Kelly
In this clip from Data Summit 2026, John O’Brien, Radiant Advisors’ principal advisor and industry analyst, reports some surprising indicators regarding self-assessed AI readiness and successful outcomes in AI initiatives involving data quality, lineage, and governance after analyzing the data from the 2026 AI Market Study conducted by DBTA and Radiant Advisors.
“When it comes to AI-readiness here is what I can say: AI-readiness does not predict AI success,” O’Brien said. “Which is different from what the industry is telling us.”
Of the people who self-assessed their readiness, half of them are successful less than 50% of the time, he explained. Data is becoming the underlying issue.
“Spending two days with you guys and talking, asking, why is this? Where is this false confidence coming from,” O’Brien said. “Data quality is the number one issue as to why AI is failing.”
The disciplines are not new, what companies are being asked to support has changed, O’Brien noted. A data quality framework built for monthly reporting is not the same as one supporting real-time inference. A governance framework for audit trails is not the same as one supporting model explainability. A semantic layer created BI consumption is not the same as the one feeding context to agents.
The annual Data Summit conference returned to Boston, May 6-7, 2026, with pre-conference workshops on May 5.
Videos and clips of presentations from Data Summit 2026 are now available for on-demand viewing on the DBTA YouTube channel.
More information about Data Summit 2027 is coming soon.