AI Impact vs. Hype in Finance 2026: Why confidence rises when AI is embedded in the ERP

AI already runs in 56% of finance teams’ workflows. Finance has moved past the curiosity stage and are using AI in their day-to-day work, based on 565 survey responses. The question is where finance teams are seeing measurable value, what is still overhyped and why some teams trust AI more than others.

Our AI Impact vs. Hype in Finance 2026 report shows a clear pattern: stronger outcomes come from structured workflows, defined ownership and AI embedded directly in the ERP. That is where confidence rises, ROI becomes easier to prove and pilots start producing results finance can actually act on.

Key highlights

• 87% of broad adopters report high confidence in ERP-native AI, compared with 39% of teams still in pilot mode.
• 53% say reporting and analysis is where AI has delivered the most tangible benefit, followed by forecasting and planning at 39% and approvals and workflows at 37%.
• Teams using AI in specific workflows report 49% positive ROI, versus 27% for teams still experimenting in pilots.
• Teams investing 21+ hours a week in AI experimentation say AI beat expectations at 74%, versus 40% among teams spending five hours or less.

Why confidence rises when AI is embedded in the ERP

One of the clearest findings in the report is that finance confidence rises sharply when AI gets closer to the system finance already trusts. When AI is embedded in the ERP, teams can evaluate outputs against live data, existing controls and workflows they already understand. That makes results easier to review and easier to act on.

Finance teams are judging AI on whether it can hold up inside real processes with real accountability attached. The closer AI stays to the finance system of record, the more usable it becomes.

Where finance is seeing the clearest early wins

The report also shows that value is not appearing everywhere at once. The strongest gains are showing up in workflows finance teams already understand well – work with defined inputs, recognizable outputs and tighter review loops. That is why reporting, forecasting and approvals are pulling ahead while other high-visibility use cases still struggle to deliver consistent value.

The report also maps what separates teams still testing AI from teams getting measurable return: adoption depth, ownership, time investment and workflow choice. What emerges is less a verdict on AI and more a picture of the conditions that make it work in finance.

Download the report to see where finance teams are getting real value from AI, what is still outpacing reality and why ERP-native AI is emerging as one of the clearest paths from experimentation to trust.

‍