By Stephanie Simone
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Video produced by Steve Nathans-Kelly
In this clip from Data Summit 2026, John O’Brien, Radiant Advisors’ principal advisor and industry analyst, quantifies and demonstrates what differentiates organizations succeeding with agentic AI from organizations continuing to struggle with it and what the data tells us.
“A data foundation is not enough for successful AI,” O’Brien said. “Well that goes against everything I’ve heard so far.”
He outlined 3 architectural pillars that differentiate successful organizations from struggling ones:
Data foundation: This includes data security, semantic definitions, data freshness/latency, unstructured data, and a knowledge graph platform.
Trust-oriented: This includes full AI model traceability, automate data trust score, data quality for AI, trust scoring readiness, and metadata/lineage.
AI architecture: This includes real-time for AI, fully autonomous agents, multi-agent systems, and agent orchestration.
“These aren’t really data foundations in terms of what we think of for analytics,” O’Brien said. “All of [these] factors are trust factors. How are we going to build trust in the AI process?”
None of this matters if you don’t have a committed budget with the mind of putting this into production, O’Brien explained.
“We have to shore up what we already have,” he concluded.
The annualData Summitconference 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 theDBTA YouTube channel.
Save the date: Data Summit 2027 is returning to Boston on May 12 -13, with pre-conference workshops on May 11. Register now to attend.