AI is changing the way finance teams operate, but the real value isn’t just faster reports or automated reconciliations. It’s how leaders use that time and insight to make smarter, faster and more confident decisions. The companies seeing real ROI aren’t the ones chasing every new tool. But they’re the ones using AI in Finance to strengthen human judgment, without replacing it.

Over the past few years, I’ve watched the finance industry invest billions into artificial intelligence, and I’ve had countless conversations with finance leaders, founders and peers who all ask the same thing: Is it actually paying off?

The answer is short and simple — Yes, but not for everyone.

The difference between companies that see real ROI from AI and those that don’t usually comes down to how they use it. Buying the right tools is only the first step. Real results come when leaders know where AI fits into their processes, their people’s work and their decision-making.

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Where most companies go wrong

Many organizations treat AI like a magic switch. They buy a platform, connect their data and expect transformation overnight.

But finance isn’t just numbers. It’s more. It’s timing, context and judgment, altogether.
AI can process faster than any person, but it can’t replace the way leaders think about risk, compliance and opportunity.

The biggest mistake I see is that AI projects are handed entirely to IT or data science teams. That’s like letting the mechanic drive the car just because they built the engine. Finance AI only works when finance leaders own it, when they decide what questions AI should help answer and how those insights are used.

What real ROI looks like

The first thing AI gives you is time. Automating reconciliations, reports or expense matching can cut manual work by nearly half. That alone is a win, but it’s not the full story.

The real ROI is reflected when finance teams use that saved time to make smarter decisions.
When people stop spending days cleaning data and start using it to forecast trends, assess risk, or plan investments, AI stops being a tool and becomes a partner.

Across the industry, the numbers tell a clear story.

According to KPMG’s 2024 Global Finance AI Report, most finance leaders already see measurable returns from AI. 57% of leaders report that their ROI exceeds their expectations, compared to 29% of others. Many are reporting 30–40% faster closes and higher forecast accuracy as automation takes hold.

Banks that have rolled out AI-powered compliance systems have reduced manual checks by more than half, while improving detection rates and audit quality. At the enterprise level, the results are becoming clear.

JPMorgan Chase, for example, is seeing real returns on its AI investments. As Jamie Dimon shared, the bank’s $2 billion annual spend on AI is already paying off, proving that when large-scale investments are backed by strategy and strong leadership, the business impact follows.

These aren’t hypothetical projections anymore. They’re the early results of applying AI with purpose, not just to speed up processes, but to elevate how finance teams think, plan and make decisions.

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The ROI you can’t always measure

Not every return shows up on a balance sheet.

When finance teams spend less time fixing spreadsheets, they start solving bigger problems. They catch risks earlier, see patterns faster and make decisions with more confidence.

That confidence becomes its own kind of ROI, the one that shows up in culture, speed and trust. Teams start feeling less reactive and more predictive. They spend less time firefighting and more time shaping strategy.

That shift isn’t measured in percentages, but every leader feels it when it happens.

Lessons I’ve learned along the way

After years of watching AI evolve across industries, here’s what separates companies that talk about ROI from those that actually achieve it:

1. Start small and make it real.
   Don’t launch a giant AI initiative. Pick one pain point and prove the value there first.

2. Fix your data before you fix your process.
   AI can’t fix bad data. Clean, connected data is 80% successful.

3. Keep humans in the loop.
   Always have experts review what AI suggests. That’s how you maintain high accuracy and trust.

4. Measure outcomes, not activity.
   Track forecast accuracy, faster closing and reduced error rates, not just hours saved.

5. Invest in your people.
   The best AI results come from teams that are confident using it, not just those who are trained on it.

These steps sound simple, but they’re what separate pilot projects from lasting transformation.

What I tell other leaders…

When fellow COOs and CFOs ask me about AI ROI, I tell them this:

• If you want quick returns, automate simple tasks.
• If you want real, lasting returns, build systems that help people make better decisions.

AI will give you insights. But only your people can turn those insights into outcomes. AI can process the numbers, but only your people can interpret them.
The smartest algorithms in the world won’t move your business forward if your leaders don’t know what to do with what they see.

ROI isn’t just about efficiency. It’s about better, faster and more confident decisions made by people who understand the business behind the data.

The road ahead for finance AI

AI is changing finance faster than any technology before. But it’s not the hero of the story.

The real advantage comes from leaders who know how to use it wisely, balancing data with judgment and keeping people at the center of transformation. AI will keep getting faster. But it still takes human leadership to turn speed into strategy.

That’s where the real ROI happens.