Charles Kenahan on AI Finance Tools and the Changes the Industry Faces

Artificial intelligence is already changing the finance industry. That much is clear, and the pace of change in AI finance and accounting tools has been faster than most business owners expected.

AI finance tools can now help companies gather information faster, compare markets, summarize documents, organize financial data, support research, review contracts, assist with scenario planning, and reduce the time spent on repetitive tasks. For small and mid-sized businesses, those capabilities can be valuable.

But I also think it is important to be honest about where we are.

In my view, AI is still in the early stages of becoming truly functional for high-level finance work. It can be useful, and in some cases very useful, but I do not believe it has reached the point where business owners, boards, investors, or advisors should treat it as a substitute for judgment, experience, process, and people.

That distinction matters.

Much of my work has involved helping smaller companies prepare for growth, a possible sale, a capital transaction, or even the possibility of becoming a publicly traded company one day. Those are serious decisions. They involve financial discipline, market timing, leadership quality, operational readiness, risk management, and a clear understanding of the people behind the business.

AI can help support that work. It should not be allowed to replace the thinking behind it.

AI Can Save Time and Improve Research

There are areas where AI finance tools can be extremely helpful.

One of the clearest examples is research. A leadership team can use AI to gather information about markets, competitors, industry trends, regulatory issues, public-company comparables, customer segments, and possible risks. AI can summarize long documents, extract key points, identify patterns, and help teams prepare better questions.

That can save a tremendous amount of time.

For a company that does not have a large finance department or internal analyst team, this kind of support can be meaningful. AI can help a smaller company begin to organize itself in a more sophisticated way. It can help management see information that may have been buried in spreadsheets, reports, emails, PDFs, and financial systems.

AI can also help with basic data aggregation. That is one area where I believe the cost savings can be dramatic. If a company is spending too much time collecting, cleaning, summarizing, or reformatting information, AI may help create a more efficient process.

In that sense, AI can give smaller companies access to capabilities that previously required more people, more time, or more expensive outside support.

That is a real benefit.

The Risk Is Treating AI as a Shortcut

My concern is not that AI exists. My concern is that some companies may use it as a crutch.

Good input usually leads to better output. Weak input, incomplete data, poor assumptions, and inexperienced interpretation can still lead to bad decisions. AI does not magically solve that problem.

In fact, it can sometimes make the problem harder to see.

A polished AI-generated summary may look credible. A financial model may appear organized. A market analysis may sound persuasive. But if the assumptions are wrong, the source data is weak, or the person reviewing it does not know what questions to ask, the output can create a false sense of confidence.

That is especially dangerous in finance.

A company preparing for a sale, capital raise, or public-market path cannot afford to rely on surface-level analysis. Buyers, investors, lenders, and public-market participants look beneath the story. They want to know whether the numbers are real, whether the business model is durable, whether management understands its risks, and whether the company can withstand pressure.

AI can help organize the conversation, but it cannot be the conversation.

People and Process Still Matter

I tend to focus on process and people factors because those are often what determine whether a company is truly ready for growth.

A business can have a good product and still struggle because its internal processes are weak. It can have revenue growth but poor financial controls. It can have market opportunity but lack leadership depth. It can have an exciting story but no discipline behind the numbers.

Those problems are not solved by AI alone.

Good companies are built by people who know how to make decisions, learn from mistakes, hire well, manage risk, communicate clearly, and build systems that can scale. Those qualities still matter. In my opinion, they matter more than ever.

AI may help a company move faster, but speed is not the same as readiness.

If a company wants to prepare for a future sale or IPO, it needs reliable financial reporting, thoughtful governance, documented processes, customer concentration analysis, compliance awareness, a strong management team, and a clear strategic narrative. AI can assist with pieces of that work, but leadership has to own the decisions.

The tool does not replace accountability.

Experience Matters in Finance

Finance is not just math. It is judgment under uncertainty.

That is where experience matters.

AI has not lived through the crash of 1989. It has not lived through the 2008 and 2009 financial crisis. It has not sat across from clients in difficult markets, helped them make decisions under pressure, or learned from real-world consequences when conditions changed quickly.

I have lived through those periods. I have worked through difficult markets. I have seen how fear, leverage, liquidity, timing, and human behavior affect financial decisions. Those experiences shape how I look at risk.

That does not mean technology should be ignored. It means technology should be put in its proper place.

A person who has lived through market cycles may look at a company differently than a tool trained on data. Experience teaches you to ask what happens if the assumptions do not hold. It teaches you to look for hidden weakness. It teaches you to respect liquidity, timing, debt, customer behavior, and management quality.

Those lessons are hard to automate.

AI Is Better at Support Than Direction

For now, I believe AI is better suited for support than directional decision-making.

It can help gather information. It can help summarize documents. It can help compare data. It can help prepare materials. It can help identify areas that deserve more attention. It can help reduce the burden of repetitive work.

Those are valuable uses.

But deciding whether a company is ready to pursue a sale, raise capital, acquire another business, enter a new market, or begin preparing for a possible IPO requires more than data aggregation. It requires judgment. It requires context. It requires experience with people, timing, incentives, and risk.

AI can give a leadership team more information. It cannot guarantee that the team will interpret that information correctly.

That is why I believe the best use of AI in finance is as an assistant to experienced professionals, not a replacement for them.

The Best Companies Will Use AI With Discipline

The companies that benefit most from AI will likely be the companies that already have strong people and strong processes.

That may sound counterintuitive, but I think it is true.

A company with disciplined leadership, clean data, thoughtful systems, and experienced advisors can use AI to move faster and operate more efficiently. The tool becomes a force multiplier. It helps good people do more, see more, and prepare more effectively.

But a company without good people, clean data, or sound judgment may not get the same benefit. It may simply produce faster confusion.

That is the real issue.

AI does not remove the need for strong leadership. It increases the importance of knowing what to ask, what to trust, what to challenge, and when to slow down.

What This Means for Companies Preparing for Growth

For smaller companies that hope to grow, sell, raise capital, or possibly move toward the public markets, AI should be viewed as part of a broader readiness strategy.

It can help leadership teams review financial trends, prepare internal reports, analyze competitors, draft investor materials, organize diligence files, and identify gaps in the business. It can also help companies think more clearly about the information a buyer, investor, or underwriter may eventually request.

But before a company relies on AI outputs, it should ask basic questions:

Is the underlying data accurate?

Are the assumptions reasonable?

Does management understand the risks?

Has an experienced professional reviewed the conclusions?

Does the analysis match what is actually happening inside the business?

Those questions matter because growth decisions are rarely made in a vacuum. They affect employees, investors, customers, lenders, founders, and families. A poor decision can have consequences that last for years.

A Balanced View of the Future

I am not skeptical of AI because I dislike technology. I am skeptical of overconfidence.

AI finance tools are going to become more capable. They will continue to improve. They will almost certainly become a normal part of financial research, reporting, modeling, diligence, and planning. Companies that ignore these tools completely may fall behind.

But companies that trust them too much may create a different kind of risk.

The future of finance will not belong only to the firms with the best software. It will belong to the firms and leadership teams that know how to combine technology with judgment, process, experience, and accountability.

That is the balance I believe matters.

AI can help people move faster. It can help companies save money. It can help teams find information and prepare more efficiently. But in high-level finance, the final responsibility still belongs to people.

And in my experience, people still matter.

About the author

Charles Kenahan is a seasoned wealth management expert from Rhode Island, with a career spanning more than thirty-five years focused on strategic asset allocation, risk management, and comprehensive portfolio oversight. Learn more at charleskenahan.com.