Artificial intelligence has quickly become the business headline of the decade, and in regard to every aspect of the business, leaders are asking: how do we use it, where does it fit, and what happens if we fall behind?
Too many organizations are tempted to rush in simply because competitors are doing it. They are doing so without clear human judgment steering the effort. AI becomes a box to check, not a source of results.
Amid all of this AI excitement, there has been a troubling pattern. Companies make an expensive investment and then treat AI like a magic wand. They buy enterprise licenses, tell employees to “go innovate,” and wait for transformation to appear. It rarely does. The result is disappointment, disillusionment, and the lingering sense that maybe ‘AI is overhyped’.
MIT’s GenAI Divide report found that 95% of enterprise generative AI pilots fail to create meaningful impact. The issue isn’t the sophistication of the models, but rather organizations deploying tools without the human expertise and strategy to adapt them to real workflows.
The reality is that AI by itself doesn’t solve business problems. People do. AI is a tool, and like any tool, it’s only as effective as the person using it.
The Flawed Approach: Tools Without Strategy
Handing out AI licenses and expecting change is akin to giving every employee a laptop before they’ve ever been taught what a computer can do. Some will tinker, a few will get results, but most will carry on as before. The gap between potential and reality widens and leaders are left wondering what went wrong.
The problem isn’t AI itself; it’s the absence of guidance. Technology without strategy creates noise, not results. And when the hype cycle fades, the business is no closer to solving the problems that matter.
Start Small, Win Big
Successful AI transformation begins in the opposite direction. Instead of grand pronouncements or enterprise-wide rollouts, the most effective organizations start small. They identify specific, solvable problems and apply AI in targeted ways.
These early steps, sometimes as simple as automating repetitive tasks or rethinking a single process, are not the wins that make headlines, but they do build confidence, save time, and prove value. More importantly, they create momentum. A series of small wins lays the foundation for enterprise-wide transformation, because it shows employees and leaders alike that AI actually works.
This approach may not sound flashy, because it’s not. Real transformation doesn’t come from throwing AI everywhere and hoping for the magic of transformative results. It comes from building carefully, piece by piece, with strategy leading the way.
Why Finance Is the Right Place to Start
Every transformation begins with a question: where should we focus first? For many businesses, the answer lies at the center of the enterprise: finance.
Finance is the heartbeat of an organization. It measures health, informs strategy, and drives decisions. Finance is where every organization’s “yes!” with AI can, and should, begin. When AI is applied to finance and accounting, the results ripple outward: automating close, accelerating reporting, and freeing up teams to focus on judgment and strategy.
Finance is the natural starting point for AI adoption and investors are betting on it. Venture capital is flowing into AI companies built specifically for the finance function because this is where data, compliance, and strategy converge. Unlike general-purpose tools, finance-focused AI is designed for the unique demands of the field: regulatory scrutiny, risk management, and the need for precise, timely insights that shape business decisions. By beginning in Finance, organizations can unlock measurable value where accuracy and trust are non-negotiable.
Finance leaders, on the other hand, sit at the crossroads of data, strategy, and execution. When they embrace AI and apply it to real-world problems, they transform enterprise growth.
Wisdom Guides the Tools
If there’s a single principle leaders should remember about AI, it’s this: wisdom guides the tools. AI is powerful, of course, but it is not a substitute for human judgment, context, or experience.
That’s why some of the most impressive AI use cases look deceptively simple. A custom workflow that cuts hours out of a monthly process. An automated reconciliation that surfaces discrepancies faster. A chatbot that answers employees’ routine questions accurately. None of these are groundbreaking advancements, but they solve real problems and these small wins add up over time.
The smartest organizations recognize that AI’s value lies in how the tool is applied, and by whom.
Standing for Smarter AI
What separates the companies that succeed from those that stall? Some treat AI as an add-on. They chase the latest branded models or announce big-ticket training investments, hoping to signal innovation. Others integrate AI into the very fabric of their business.
They don’t try to compete with billion-dollar tech companies by building their own models. Instead, they build fluency by learning how AI fits their operations, embedding it in processes, and aligning it with strategy.
That fluency is what makes AI powerful. It’s not about having the shiniest tool, rather, it’s about knowing where, when, and why to use it.
The Smarter Path Forward
AI is not going away. In fact, it’s gaining momentum day-by-day, which is not what you might think, given how loud the AI naysayers have become. The real question for today’s business leaders is whether they’ll treat AI as a passing trend or as a force worth mastering.
The companies that thrive will be those that embed human wisdom into every decision about AI: what problems to solve, what tools to use, and when to scale. They’ll be the ones that start small, build strategically, and let wisdom guide the tools, recognizing that transformation isn’t instant, but with the right guidance, it is achievable.
