"We spent the early part of the year getting models to understand our data. Now we have to figure out if we can safely let them touch it. The market is moving from generating answers to executing actions, which changes the baseline requirements for databases and catalogs. The goal isn't just building a smarter agent. It's about letting an agent change a record and being able to prove exactly who authorized it, why it happened, and how to reverse it."
In the second half of 2026, the focus for data and AI leaders will shift from generating trusted insights to executing governed actions. We spent the first half of the year building semantic layers to help models understand business context. Now, organizations face a harder problem: letting agents act on that data in a safe, governed, and performant manner.
The transition from generating insights to executing governed actions requires a significant investment in the underlying data estate, breaking down data silos, surfacing critical meaning through metadata, and overcoming architectural barriers that divide operational and analytical engines. However, success is currently constrained less by technology or budget than by a critical shortage of professionals capable of governing autonomous software and managing the technical debt of rapid agentic AI adoption. Amid these shifts, enterprises also face new risks of technical debt and inescapable inertia via vendor lock-in as providers attempt to control both the foundational database layer and the intelligence stored at the agent and ontology level.
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.
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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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