In Episode 12 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Justin Borgman, Co-Founder and CEO of Starburst, where they discuss why the biggest barrier to AI success is no longer about models.

The conversation explores why traditional approaches to data architecture are struggling in the AI era, how enterprises can overcome fragmented data estates, the importance of context and semantics, why many organisations remain stuck in pilot mode, rising AI costs, build versus buy decisions, agentic AI, and what the next three to five years of enterprise AI adoption are likely to look like, which includes;

Why the vision of centralising all enterprise data into a single platform has never truly reflected reality.
Why the AI industry's obsession with model selection is increasingly distracting organisations from the real challenges.
How advances in foundation models are rapidly commoditising model performance and shifting attention elsewhere.
What the true bottlenecks to AI adoption actually are.
Where the clearest examples of AI delivering measurable value are today.
Why many organisations remain trapped in POCs despite significant investment and executive attention.
How the lack of context and semantic understanding continues to limit the effectiveness of AI in enterprise environments.
Why trust, meaning and business context matter as much as access to data itself.
Why AI success depends on; data foundations, analytics performance, enterprise context and trusted agentic interfaces.
Why rising AI costs are becoming one of the biggest concerns for enterprise leaders and CFOs.
Why data products are emerging as a practical solution for creating AI-ready context across the enterprise.
Why separating context from physical data location creates more flexible and scalable architectures.
Why executives are increasingly expecting answers rather than reports and dashboards.
Why organisations should be building differentiated business capabilities rather than core platform infrastructure.
How businesses that feel behind are often closer to the market than they realise.
What the next three to five years could look like as AI becomes embedded into every major business function.

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