A new report reveals a critical 'maturity gap' in finance: while 88% of enterprises are ready for AI, over half remain stuck in partial automation. We explore why 2026 is the year CFOs must move from experimentation to hard returns—or risk falling behind on fraud prevention.
If 2024 was the year of “playing with AI” and testing the waters, 2026 is shaping up to be the year the bill comes due.
For finance leaders, the experimental phase is officially ending. The mandate from the board is no longer “What can this cool tech do?” but rather “Show me the money.” Yet, despite the pressure to perform, a significant portion of the finance function is stuck in a dangerous middle ground—automated enough to feel modern, but manual enough to be vulnerable.
A new report from Intelligent Document Processing (IDP) leader Rossum, Document Automation Trends 2026, has flagged a critical “maturity gap” that should make any CFO pause.
The headline statistic is a stark reality check: 54.2% of finance leaders say their processes are only “partially automated.”
In the old days, partial automation was progress. Today, in an AI-powered world, it’s a liability. Partial automation means data still moves through disjointed systems, relying on manual hand-offs and Excel spreadsheets (which 1 in 10 respondents admitted they still rely on).
The problem isn’t just inefficiency; it’s exposure. While legitimate businesses are testing AI, fraudsters are mastering it.
“Legacy tools simply can’t handle today’s complexity,” notes Petr Baudiš, CTO at Rossum. “It’s been proven AI can eliminate manual data entry, but the next step is achieving verifiable accuracy and predictive power.”
The report suggests that traditional detection methods—catching bad invoices after the fact—are obsolete. The new standard is prevention, using AI to spot anomalies (like a duplicate invoice or a fake supplier request) before a single cent leaves the account.
The sentiment across the market is shifting aggressively toward ROI. According to data cited in the report from Domino Data Lab, 88% of enterprises have improved their ability to deploy AI at scale. This signals that the infrastructure is ready; now the output must justify the spend.
Finance leaders are responding by getting granular. They aren’t measuring success by “digital transformation” buzzwords anymore. Instead, 34.2% of leaders are tracking specific operational KPIs like cost-per-invoice, error rates, and processing speed.
As Olivier Gomez, a global automation authority featured in the report, puts it: “If it doesn’t reduce cost or generate revenue, it won’t survive.”
If the technology is ready, what’s the hold-up? Trust.
There is a lingering skepticism about letting AI take the wheel on financial decisions. The report highlights that improving the accuracy of financial data is now the top priority for 31.3% of leaders. CFOs are rightfully wary of “black box” algorithms. They need governance, audit trails, and “financial guardrails” to ensure that an AI agent doesn’t just make a decision, but can explain why it made it.
The Document Automation Trends 2026 report doesn’t just list problems; it outlines seven specific trends that will define the next two years of finance.
We won’t spoil them all here, but they cover the critical shifts in Global Compliance (Trend #7) and the move from Data Entry to Decision Engine (Trend #1). The report also includes specific “KPIs to watch” and action plans for moving your department from partial automation to full “hyperautomation.”
If you are still debating whether to automate end-to-end or keep relying on manual oversight, this report is your roadmap to closing the gap before your competitors do.