“We’re seeing a critical pivot from experimenting with AI to industrializing it, and this has exposed a massive gap in data readiness. The winning strategy in 2025 won’t be about building or integrating the best AI models but creating the best data to feed those models at scale and without risk.”
By the end of 2025, the primary bottleneck for scaling enterprise AI will shift from model development to data readiness. In response, most enterprises will focus on deploying an “AI-Powered Data Control Plane” to automate data discovery, preparation, and governance, making it the most critical investment for unlocking value from AI workloads.
Emerging enterprise concerns over data quality and the maturation of data engineering platform capabilities drive this trend.
Brad Shimmin is Vice President Practice Lead, Data Intelligence, Analytics, & Infrastructure at Futurum, where he provides strategic direction and market analysis to help organizations maximize their investments in data and analytics. Currently, Brad is focused on helping companies establish an AI-first data strategy.
The vision behind everything in Futurum’s Custom Research practice is this: research should show you what is happening, what comes next, and what to do about it. It should be personal to each audience, easy for people to grasp, and structured so LLMs can reason over it accurately. And it should be fast and turnkey; you want answers now, not another project to carry for quarters.
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If any of this is useful, I would love to talk.
VP, Custom Research · The Futurum Group
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