When you’ve spent years managing a global finance organization, you learn quickly that no two countries—or even two regulators—see the world the same way. Tax laws, compliance requirements, reporting standards: all of it varies, and all of it matters. My team operates across multiple jurisdictions, and that means we often live in two worlds at once: the traditional, rule-bound structures of financial authorities and the fast-moving, experimental world of financial technology.
Right now, no development has made that gap more obvious—or more urgent—than AI. I’ll admit, AI in finance makes me both excited and uneasy. The pace of innovation is staggering, and at times it feels like the ground is shifting beneath our feet.
I hear the same concern from peers across industries: What happens to our people if machines take over? That fear is valid. But I also believe that AI isn’t a replacement for finance professionals—it’s an amplifier. And the numbers back that up: Tipalti’s State of AI in Finance survey found that 57% of finance organizations intend to keep their staffing levels steady even as their business grows, 45% are reallocating headcount into higher-value, more strategic roles rather than cutting staff, and 46% say AI is actually helping them recruit talent by helping people uplevel their skill sets.
With the evidence clearing the path for adoption, the real challenge becomes preparing our teams to adapt.
Key Takeaways
- Most finance organizations plan to hold staffing steady as they grow, using AI to reallocate people into higher-value roles rather than cutting headcount.
- Building an AI-ready finance team is a two-way effort: employees should seek out training proactively, while organizations should provide structured programs of their own.
- Finance professionals want visibility and control over AI, which means the team’s new role is to review, validate, and apply judgment to what the technology produces.
The Old Way vs. the New Way
Finance has always been about accuracy and accountability. Regulators and tax authorities demand it, and for good reason. But those institutions still run largely on old systems and rigid frameworks. AI, on the other hand, thrives on flexibility, automation, and pattern recognition. Bridging these two worlds is the crux of the challenge.
Take auditing as an example. Traditionally, it’s been a painstaking, human-driven process. Today, AI can scan massive volumes of transactions in seconds, flagging anomalies with more precision than even the sharpest auditor. That’s the new way. But regulators still want a human signature on the line, someone accountable for the judgment calls. That tension—between efficiency and trust—is where finance leaders have to navigate carefully.
| How AI is Reshaping Core Finance Processes | ||
| Old Way | New Way | |
| Auditing Process | Manual, transaction-by-transaction review | AI scans thousands of transactions in seconds, flagging anomalies |
| Speed | Hours to days per review cycle | Seconds to minutes per review cycle |
| Human Role | Sole executor of every payment | Reviewer and final decision-maker |
| Core Strength | Deep contextual judgment | Pattern recognition at scale |
| Accountability | Human signature required at every step | AI flags risk; human still signs off |
What AI Means for Finance Operations
There’s no denying it: AI is making certain tasks redundant. Processes that used to take teams hours—data entry, reconciliations, invoice matching—can now be automated in minutes. Early on, I worried about what this meant for job security across my team. But what I’ve seen is that, in practice, automation is freeing people up to focus on higher-value work.
Instead of drowning in spreadsheets, our team now spends more time on scenario modeling, strategy conversations, and cross-functional projects that drive growth. That shift doesn’t happen automatically, though. It requires reskilling, retraining, and a willingness to rethink what it means to “be in finance.”
How Finance Teams Should Adapt
I like to tell my team that patience and curiosity are our best allies right now. AI is evolving daily, and no one has all the answers. But leaning into technology with an open mind is critical.
One story that sticks with me: an investor colleague of mine was worried that his son chose to study software engineering. “There won’t be jobs in ten years,” he said. But I see it differently. In this AI-driven world, technical fluency is a superpower. Finance professionals who understand data, systems, and AI tools will be the ones who shape the future of our function.
So how do we prepare?
- Seek training proactively. Don’t wait for someone else to dictate the curriculum—look for certifications, online courses, or workshops that deepen your knowledge.
- Collaborate openly. Bring your team into the conversation, experiment with tools together, and share wins and failures.
- Lean on your network. Reach out to peers in other companies. Ask what they’re trying, what’s working, and what’s not.
- Push your comfort zone. The most valuable skills of tomorrow are being shaped today, and they often start outside our familiar territory.
Corporations also have a responsibility here, and most are already stepping up: 58% of organizations now offer formal AI skills development through internal resources, and 53% bring in outside vendors, while only 4% leave AI preparation entirely up to employees. Leaders must invest in training, provide clear guidance on where AI fits into existing processes, and ensure integration is consistent across finance functions.
Harnessing AI as a Strategic Advantage
At the end of the day, AI isn’t an enemy to fear. It’s a partner—albeit one that demands careful oversight. Machines are powerful, but they lack judgment. They don’t understand context, ethics, or accountability. That’s where we come in: 55% of finance professionals rate the ability to see and review every action AI takes as extremely important, and 50% prioritize not losing decision-making control to AI.
As finance professionals, our role is to blend the precision of technology with the discernment of human experience. If we can do that, AI becomes more than a cost saver or a productivity hack. It becomes a strategic advantage.
The new age of finance isn’t about choosing between people and machines. It’s about combining them—working with AI, not against it. And for those of us willing to adapt, that future isn’t something to fear. It’s something to celebrate.
