AI in Financial Planning: What Accounting Firms Need to Know Before They Buy

Every software company in the accounting space now claims to use AI. Most of them are lying — or at best, exaggerating.

The rush to slap "AI-powered" on marketing materials has created a dangerous environment for accounting firms evaluating new technology. Some companies have bolted a ChatGPT wrapper onto their existing product and called it artificial intelligence. Others are using the term to describe basic automation rules that have existed for years. And a few — a concerning number — are routing sensitive financial data through third-party AI models with questionable data security practices.

Fady Hawatmeh has been building AI for financial planning since 2018 — years before ChatGPT made AI a household term. He has a simple litmus test for firms evaluating AI products: ask the vendor what kind of AI they use, and demand a simple answer. If they cannot explain it clearly, run.

Here is why this matters. There are fundamentally different types of AI, and they carry very different risk profiles. Machine learning analyzes your own data in a closed loop — it learns from your specific financial history and user behavior to generate forecasts, identify patterns, and surface insights. No external data comes in. No sensitive information goes out. It is your data, learning about your business, generating outputs tailored to you.

Generative AI — the kind powering ChatGPT and similar tools — works differently. It is trained on massive public datasets and generates responses based on probability patterns. It is incredibly useful for content creation, summarization, and brainstorming. But when you feed it sensitive financial data without proper safeguards, you are trusting a third-party model with your clients' most confidential information.

The cautionary tale is Scale Factor, an Austin-based company that raised over $100 million by promising AI-powered bookkeeping. In reality, they had teams in Malaysia doing the work manually. When the truth came out, the company collapsed overnight — taking client data, employee livelihoods, and investor capital with it.

For accounting firms evaluating AI tools in 2026, here is what to look for. First, ask about data residency. Where does your financial data go when it enters the system? Is it stored in a secure, SOC 2-compliant environment? Second, ask about model ownership. Does the vendor own their AI, or are they piping your data through a third-party API? Third, look for explainability. Can the AI show you how it arrived at a forecast or recommendation? If it is a black box, it is not ready for financial decision-making.

AI is not optional for the modern accounting firm. But choosing the wrong AI partner can be worse than having no AI at all.