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Where enterprise AI breaks down in practice
Real examples of where AI + data look right but aren’t - and what actually goes wrong once these systems hit real business environments.
Why most teams still don’t agree on their own data
How shifting definitions, inconsistent metrics, and lack of shared context create confusion - even before AI is involved.
What it actually takes for AI to understand a business
A candid discussion on whether approaches like semantic models or structured layers are necessary - and what’s overhyped vs. real.
The reality of data teams today
Why data teams are often seen as bottlenecks, the pressure of being “on the hook” for accuracy, and how organizations can move from caution to enablement.
SVP of Data, SurveyMonkey
Meenal Iyer is a data and analytics leader at SurveyMonkey focused on turning complex data into trusted insights for product and business teams. She brings an operator’s perspective on maintaining clear definitions, alignment, and trust in data across growing organizations.
Founder & CEO, Delivery Layer
Solomon Kahn is a data and AI builder focused on helping organizations apply modern data systems to real-world business problems. He works closely with companies navigating the challenge of turning fragmented data environments into reliable analytics and scalable AI capabilities.
CEO & Co-Founder, Solid
Yoni Leitersdorf is the CEO and co-founder of Solid, where he is building infrastructure that helps AI understand and operate on data. Previously, he founded Indeni, a network automation company acquired by BlueCat, and has spent his career building systems for complex technology.