Finance is at an inflection point. AI is reshaping how organizations plan, report, and make critical business decisions. Yet while most finance teams acknowledge AI’s potential impact, only 39% report confidence actually using the technology. Many have concerns about security, ethics, and data quality. Others are unsure of how to integrate AI into their daily workflow. 

The real benefit of AI isn’t gaining access to information – it’s gaining efficiency and access to new insights. Contrary to common belief, the technology is most powerful when used to enhance human intelligence rather than replace it. 

Tech alone won’t reshape the future of work

Despite an ongoing debate that pits humans against AI, technology on its own won’t reshape the future of work. Instead, it will be shaped by humans who know how to partner with technology. 

I saw this shift firsthand when ChatGPT was introduced in 2022. Like many people, I initially tested it with lighthearted questions just to understand its capabilities. But that curiosity quickly evolved into practical application. I began using it as a thought partner, uploading complete and accurate datasets and asking it to flag variances, compare performance against benchmarks, and surface patterns that would have taken hours to identify manually. What started as experimentation became an accelerator for insight. It wasn’t replacing analysts; it was sharpening their output. 

Take today’s finance professionals for example: they’re navigating increasingly complex regulatory requirements while juggling close, consolidation, planning and disclosure in addition to acting as strategic advisors to their business. They’re covering significant ground while being bogged down by manual processes that limit impact. AI offers a way to break this cycle.  

Algorithms can outperform humans in speed, accuracy and scale. They can automate data reconciliation, journal entry validation and variance analysis – repetitive work that consumes hours every week. By handling these tasks, AI gives finance teams invaluable time and mindshare to focus on more strategic work. 

On our finance team, we’ve seen tangible time savings. Month-end variance analysis used to require significant Excel modeling and manual reconciliation. Today, analysts can upload complex datasets and have AI identify version-over-version changes and key drivers in a fraction of the time. Tasks that once took two days can now take two hours. That time and those workers aren't eliminated, they’re redirected. Instead of building spreadsheets, our team is spending more time interpreting results and advising the business.

What AI can’t replace is human judgment. The technology lacks the empathy, ethics and contextual understanding that drives business decisions. As AI takes over routine and repetitive tasks, soft skills like critical thinking, ethical reasoning and emotional intelligence become even more important. The future belongs to finance professionals who can apply their expertise and experience to the time and insights AI provides.

Building trust in human-AI collaboration

The most effective finance teams treat AI as a teammate, and don’t put it on autopilot. As outlined in my company’s publication AI in Finance & Accounting For Dummies, AI delivers value by handling scale, speed and pattern recognition, while humans remain responsible for judgment, ethics and accountability. Trust is built when finance leaders are transparent about how AI works, clear about its limitations and intentional about keeping humans in the loop for high-impact decisions. When those expectations are set early, AI becomes an accelerator for better decision-making rather than a source of risk or skepticism. 

As CFO at insightsoftware, building that trust required discipline. AI is an investment, and early on, quantifying ROI wasn't straightforward. Productivity gains, roadmap acceleration, and improved response times don’t always fit neatly into a spreadsheet. At one point, we had multiple teams piloting overlapping AI tools. We had to step back and evaluate: Are we buying capabilities we may soon be able to build? Are we locking into multi-year contracts for functionality that could quickly become commoditized? That process reshaped how I evaluate emerging technology by balancing calculated risk with governance and long-term value creation. 

In contrast, I see many companies investing heavily in AI while lacking leadership alignment, workforce strategy and internal skills to successfully scale and show ROI.  Instead, their strategy should move forward animated by the simple fact that an organization's ability to transform hinges on its people.