39% of CFOs Say AI Is Their #1 Priority: Here's What They're Actually Doing with It

Finance leaders are operating in a fundamentally different environment than they were even five years ago. Economic uncertainty, rising compliance expectations, and growing pressure to deliver real-time financial insights are compelling finance teams to rethink how work gets done—and who they partner with to get it done.

A 2025 survey by Gartner of more than 200 CFOs found that 39% rank accelerating AI adoption as one of their top strategic priorities, highlighting the growing pressure on finance teams to modernise their operations.

This shift reflects a deeper structural reality. Modern finance and accounting departments are now expected to function as strategic partners to the wider business. To do that effectively, they require faster data processing, more accurate forecasting, and significantly fewer manual workflows.

This is precisely where AI in accounting is beginning to reshape finance functions, particularly through advanced accounting automation.

Why Finance Functions Are Turning to AI

Historically, accounting and bookkeeping services relied heavily on structured processes and manual checks. While this approach prioritised strong controls, it also created operational bottlenecks that limited the function's ability to contribute at a strategic level.

Routine activities such as invoice processing, reconciliation, and expense categorisation consumed a disproportionate share of finance teams' time. In many organisations, these tasks still depend on spreadsheets, manual reviews, and fragmented systems that were never designed for the scale or speed now required.

AI-powered accounting offers a credible alternative. By embedding machine learning into financial workflows, organisations can automate repetitive processes, detect anomalies more quickly, and analyse financial patterns at a scale difficult to achieve through manual efforts.

The result is not only faster processing, but also a finance function that can operate with greater agility and keep pace with the businesses it supports.

Where AI Is Actually Being Used in Finance Teams

While discussions around AI often focus on future possibilities, many finance teams are already deploying the technology in targeted, high-impact ways across their accounting workflows.

Invoice Processing and Data Extraction

Intelligent invoice processing is among the earliest and most widely adopted applications of AI in accounting. Platforms such as Ramp, Rossum, Tipalti, and Stampli use machine learning and OCR technology to capture invoice details, match them with purchase orders, and automatically post entries into accounting systems.

These tools significantly reduce the time finance teams spend on invoice handling while improving accuracy and audit readiness.

Automated Reconciliation

Reconciliation has traditionally required finance professionals to manually match transactions across multiple systems. AI-driven reconciliation tools can analyse thousands of transactions simultaneously, identifying discrepancies and suggesting matches with a speed and consistency that manual processes cannot replicate.

Expense and Fraud Detection

AI systems can identify unusual spending patterns or irregular transactions by analysing historical data in real time. Rather than relying solely on periodic manual audits, finance teams can use AI to surface anomalies continuously, strengthening internal controls while allowing finance professionals to focus on areas that require stronger judgement.

Forecasting and Financial Modelling

By analysing large volumes of operational and financial data, accounting automation systems can generate more dynamic, scenario-responsive forecasts. This allows finance leaders to model complex variables quickly, gain clearer visibility into financial performance, and make faster, better-informed decisions.

AI Will Augment Finance Professionals, Not Replace Them

The question of whether AI will replace roles within finance teams remains widely debated. In practice, most leading accounting firms recognise that the technology strengthens finance professionals rather than replacing them.

AI can process large datasets quickly and surface patterns that would otherwise go undetected. What it cannot do is replace professional judgement, regulatory interpretation, or the strategic decision-making that defines senior finance leadership.

Finance professionals remain essential for validating AI outputs, applying business context, and communicating insights to leadership in ways that drive action. That remains fundamentally a human skill.

In this sense, AI in accounting should be understood not as a threat to the profession, but as a capability multiplier—one that strengthens the effectiveness of finance teams and elevates the value they deliver.

The CFOs Who Act Now Will Define the Finance Function of Tomorrow

The Gartner finding reflects a broader, irreversible transformation underway across the finance profession.

AI is no longer a theoretical innovation reserved for early adopters. It is becoming a practical operational tool for improving efficiency, strengthening financial controls, and enabling more informed decision-making at every level of the organisation.

However, successful adoption depends on more than technology alone. It requires clean data, thoughtful integration, strong governance frameworks, and expert accounting services providers who ensure systems, processes, and financial records work together seamlessly.

For finance leaders, the real opportunity lies not simply in automating tasks, but in fundamentally redefining what their finance function is capable of.

For finance leaders, the real opportunity lies not in automating tasks for the sake of it, but in fundamentally redefining what their finance function is capable of.