In Episode 3, of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Daragh Kelly, Chief Data Officer at The Economist, where they discuss why most AI initiatives are still failing, why there's not much measurable progress and how insight functions have become toolmakers and decision intelligence partners, which includes;

Why most AI initiatives fail because they as a solution looking for problems.
The importance of aligning AI use cases to strategic goals, KPIs and measurable outcomes.
Why speed rather than velocity leads to very little measurable progress.
Why compelling POCs create false confidence before the real production challenges begin.
The deployment gap: why robust, scalable and commercially viable AI is still hard.
Why disconnected tools and poor workflow integration stall AI value realisation.
The simple test for prioritisation: is this problem big enough to matter?
Why the best AI use cases act as building blocks for future capability.
How AI and UX together are driving true self-service insight generation.
Why insight teams are evolving from answer providers to toolmakers.
The growing importance of data governance, quality and observability in an AI-first world.
How distributed insight creation can weaken corporate memory and knowledge curation.
The skills shift toward UX, enablement, storytelling and decision intelligence.
Practical build vs buy criteria in fast-moving and rapidly commoditising AI markets.
Why operating models matters less than discipline, purpose and capability building.

S7 | Ep 3 | The AI Speed Trap: Why Activity Isn’t Progress with Daragh Kelly, Chief Data Officer at The Economist