Why Most Enterprise AI Deployments Fail Before the Technology is Even the Problem
Christine Pierce, former Nielsen executive and advisor, explains why most enterprise AI deployments fail before technology is the problem.
Explore DatAInnovators & Builders, Nexla’s flagship data and AI podcast, plus conversations featuring our team across leading data integration, AI, and enterprise technology podcasts, covering real-world AI adoption and agent-ready intelligence.
Christine Pierce, former Nielsen executive and advisor, explains why most enterprise AI deployments fail before technology is the problem.
Francois Lopitaux, SVP of Product Management at ThoughtSpot, explains why context, not models, is the key to trusted, scalable AI and analytics.
Yorck F. Einhaus, former Global CDO at Liberty Mutual and Farmers Insurance, explains why enterprise AI fails without strong data foundations.
Michael Domanic, VP at UserTesting, explains how enterprises run AI teams of three to drive transformation and measurable ROI.
Rowan Trollope, CEO of Redis, explains how teams hit 95% cache and cut LLM costs 70% using agent memory, semantic layers, and production-grade AI infrastructure.
Fred Gertz of Collide Technologies explains how swarm intelligence solves NP-hard routing and scheduling problems in seconds, without training data or LLMs.
GrowthX founder Marcel Santilli explains the delegation test for AI and why poor context, not weak models, is the real reason AI initiatives fail to scale.
Ortecha’s Stephen Gatchell explains the data governance gap blocking AI production, why unstructured data breaks legacy models, and how data product frameworks enable scale.
No vendor pitches. No polished panels that skip the hard parts. DatAInnovators & Builders features CDOs, CTOs, and data architects sharing real architecture decisions and hard-won lessons — honest conversations from leaders who’ve actually shipped AI and data solutions at enterprise scale.
Real enterprise challenges: moving AI from pilot to production, managing data variety across 1,000+ systems, simplifying bloated data stacks, and building effective teams without endless hiring. Topics include RAG vs. fine-tuning for production agents and the process-level reasons most AI adoption stalls before it scales.
Season one features Robin Sutara of Databricks, Ashish Thusoo of CurieTech AI, Alexander Page of BigPanda, and Stephen Gatchell of BigID — CDOs, CTOs, and AI leaders sharing firsthand experience tackling enterprise data and AI challenges at scale.
Guests share the specific decisions, integration strategies, and structural changes that moved their AI initiatives from proof-of-concept to production. Each episode breaks down why projects stall — usually at the process level — and exactly what leaders did to break through.
New episodes drop every two weeks on Apple Podcasts, Spotify, and YouTube. Full video episodes are available on the Nexla YouTube channel. Data leaders with real-world lessons to share can also reach out to be considered as a guest.
DatAInnovators & Builders is produced by Nexla, an enterprise, AI-powered data integration platform that unlocks data from any source and transforms it into production-ready data products for AI and agents — supporting 550+ connectors, ELT, ETL, streaming, APIs, and agentic RAG. Host Saket Saurabh, Nexla’s Co-founder and CEO, brings firsthand experience solving the challenges discussed on the show.