AI in Finance: Key Insights for CFOs

CFOs aren’t just managing the books anymore. They’re making fast, strategic decisions—and AI is helping them do it better. The biggest shift? AI tools take over repetitive tasks and give CFOs real-time insights into how money is spent and where it’s going. The role is moving from financial controller to business driver.

Despite the upside, adoption is low, with only 9% of 900 CFOs actively using AI in 2024. Leaders are cautious about handing over critical processes to AI for fear of potential disruptions and internal pushback. Read on to learn how to get ahead of the curve and tackle these challenges head-on.

What Is AI in Finance?

AI is now baked into many areas of finance. It handles the routine work—generating reports, reconciling data, flagging errors—so finance teams can focus on bigger decisions. But it doesn’t stop there.

Unlike traditional AI, generative AI tools also identify trends and risks that would take humans hours (or days) to notice. They can use data from across the company—sales, ops, supply chain, even market news—and turn it into useful insights. The result? CFOs can act early instead of reacting late.

Examples of AI in Action

The focus of finance is no longer on chasing data or fixing errors. It’s about using real-time insights to make informed decisions faster. Companies already use AI in key areas of finance. Here’s a breakdown of where it’s making the biggest impact:

• Procurement: AI procurement software automates invoice and purchase order processing. Instead of poring over the numbers, teams can use AI to track spend, detect maverick expenses, and ensure accuracy. In turn, CFOs can use these insights to negotiate vendor terms and control costs.
• Forecasting and Planning: AI can extract live data from various sources, forecast trends, and run scenario analysis. CFOs use this to adjust plans on the fly, not just at the end of the quarter.
• Risk and Fraud Detection: AI scans for unusual patterns in transactions and vendor behavior. It alerts teams early, and CFOs can address the issues before they become costly.
• Cash Flow and Working Capital: AI predicts late payments, spots liquidity risks, and even automates parts of accounts payable and receivable. That means tighter cash management and smarter capital allocation.
• Reporting: Instead of manually creating reports, AI handles the heavy lifting—whether it’s a balance sheet or ESG compliance. Reports are generated faster and with fewer errors.

Benefits of AI in Finance

AI isn’t just a passing trend or a flashy new technology. Artificial intelligence is here to stay, promising tangible business advantages:

Fewer Errors

Most spreadsheets have mistakes—94% of them, in fact, according to recent data. AI eliminates that risk by automating calculations and checking for inconsistencies across systems. Advanced solutions validate data, run checks, and reduce human error across the board.

Faster Teams

The month-end close doesn’t need to take a week. AI tools handle reconciliations, generate reports, and process payments in minutes, not days. That’s the time your team can spend solving real problems that require human expertise.

Cleaner Centralized Data

Data silos waste time and create blind spots. AI breaks them down. It pulls information from ERP systems, procurement platforms, and finance tools into one clear view. Everyone has access to the same data.

Smarter Cost Control

AI helps CFOs spot overspending, hidden costs, and saving opportunities, such as better negotiation terms or more affordable vendors. It turns cost management from proactive to reactive. Artificial intelligence can flag unnecessary purchases, track budget drift, and even suggest how to reallocate funds.

Proactive Risk Management

Finance is full of pitfalls—late payments, supply chain gaps, market shifts. With AI, CFOs and their teams can spot them early and receive data-based suggestions before these challenges explode into full-blown issues.

Why CFOs Are Still on the Fence

Although AI is already reshaping traditional financial processes, not every company is ready to implement it on a full scale yet. Here’s what’s holding finance leaders back:

• Upfront Cost: AI tools can be expensive, and many CFOs aren’t convinced the return on investment will come fast enough to justify the upfront spend.
• Tech Hurdles: Many companies still run on outdated systems that weren’t built to support AI. Integrations can be messy, time-consuming, and disrupt regular business operations—something not every company can afford.
• Privacy Concerns: Financial teams are apprehensive about inputting sensitive data into public AI tools like ChatGPT. They’re concerned that this information could leave the company’s control and fall into the wrong hands.
• Team Pushback: Employees worry that if AI can do parts of their job, they’ll be replaced. That fear can lead to pushback and stall adoption, even when the tools are useful.
• Bias Risks: AI reflects the data it’s trained on. If that data is flawed or biased, the outcomes will be too. That can affect hiring, supplier decisions, and financial modeling in ways that are hard to catch until something goes wrong.

These are valid concerns. But they’re also solvable with the right approach.

AI Introduction Strategy in Finance

AI adoption doesn’t have to start from zero. The best approach is to begin small—target one clear problem like reporting delays or invoice errors, apply AI, and expand from there. Before rolling out any tool, define what you want to improve.

Bring your team in early. If employees don’t understand or trust the tool, adoption will stall. Show how AI supports their work, not replaces it, and provide the training to back that up.

Good AI needs good data. Make sure systems are connected, inputs are clean, and everyone knows what’s being pulled in. Additionally, set ground rules. Define how AI is used, who owns the output, and how the results are verified.

Key Insights

AI is already changing the way finance teams operate. From procurement and forecasting to fraud detection and reporting, AI handles the busywork and sharpens strategic decision-making. Yes, there are hurdles—cost, integration, resistance—but they’re not dealbreakers. With a clear goal, clean data, and a focused rollout, AI becomes a helpful asset in the hands of a savvy leader. CFOs who act now won’t just keep up; they’ll get ahead.