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The "wait and see" phase is over. AI is moving fast, but most organizations are not ready.
AI adoption is accelerating, but results are falling short, according to new DBTA research. Fewer than half of AI initiatives succeed, and most pilots never reach production. What's more, AI failures are expensive, with 36% costing more than $500K and 16% exceeding $1M.
The root cause is clear: data. Gaps in quality, access, trust, and lineage continue to limit outcomes and prevent AI from scaling. And this is not a new problem; it is an unsolved one.
At the same time, organizations are moving quickly into agentic AI, with 37% already in production, even as security, governance, data quality, and trust remain unresolved barriers. Many are managing risk through copilots and human- in-the-loop workflows, but a clear gap remains: while most believe their data is AI-ready, 77% of failures are tied to data, and only one in three can fully trace model outputs back to source data.
Join DBTA, Radiant Advisors, and Quest Software for a data-driven discussion on what's really happening inside enterprise AI initiatives and why data readiness is the #1 factor in AI success or failure.
What You'll Learn:
- The real, measurable cost of AI-unready data
- Where the gap between AI ambition and data readiness is breaking down across organizations
- What it takes to improve data quality, governance, and trust to support AI at scale
- How leading teams are building data foundations that support AI success
Reserve your seat today!
Don't miss this live event on Tuesday, April 28th, 11 AM PT / 2 PM ET.
Register Now to attend the webinar AI Readiness Reality Check: Why Most AI Initiatives Still Fail and How to Fix It.
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MODERATOR |
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John O'Brien
Principal Advisor and Industry Analyst
Radiant Advisors |
Ryan Crochet
Director of Product Marketing
Quest |
Bharath Vasudevan
Vice President of Product and GTM
Quest |
Stephen Faig
Research Director
Unisphere Research and DBTA |
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