Agentic AI in corporate planning: from promise to practice

Drawing on 312 responses across Europe and North America, BARC maps where agentic AI stands in planning today, what’s holding it back, and what separates the teams pulling ahead from those still waiting.

98% see the promise of AI in planning—yet only 10% feel its impact today. That gap is the real story. Most teams are investing to work faster, and the use cases they reach for first make clear that they want AI to spot what’s off and test what’s next, not to run the plan on its own.

Most feel solid on technology, far fewer on the processes and organization around it. The obstacles aren’t exotic—they’re the data foundation itself: silos, quality gaps, integration, and security. So teams stay pragmatic, fixing the foundation before layering AI on top, and keeping a human in the loop when AI does run. Strategic decisions, final approvals, and full autonomy stay firmly with people.

This edition adds an exclusive look at interoperability—the baseline 85% now call essential, where leaders and laggards agree almost exactly. The principle Finance teams keep returning to is simple: control before action, and write access only once trust is earned.

AI is moving fast in corporate planning, and Finance teams face real pressure to adopt it, yet little clarity on what works and what doesn’t. That’s where grounded evidence earns its place—a clear view of what peers are prioritizing, where they’re meeting resistance, and what’s delivering results. As an independent analyst, BARC reflects the state of the field rather than any single vendor’s perspective.

Download the study to see the full picture.

“AI adoption in planning depends on connected, reliable data and clear governance; software alone will not close those gaps.”
— Dr. Christian Fuchs, Senior Analyst, BARC