The CFO'S Perspective

These days we’re hearing a lot of clients ask, “How is AI going to affect my business?”

Unfortunately, there’s a lot of fear mongering going around related to AI based on largely unfounded concerns. There’s an uneducated belief that AI could steal jobs away from skilled professionals across various business facets like accounting and finance. However, this is simply untrue! AI is not going to replace your accountant, but what it is going to do is make professionals across finance, accounting, tax, treasury, procurement, and audit better at what they do!

As CFOs, we have a full plate of responsibilities for financial reporting, planning and analysis, and risk management. We’re often skeptical of “breakthroughs” that promise to “transform the finance function” and “shift the paradigm of accounting and finance.” To us, these types of phrases just sound like more of the same – another overhyped management consulting fad based on a Harvard Business Review article. All we hear is just “blah, blah, blah” and we tune it out.

Should we feel that way about the current wave of Artificial Intelligence as well?

The name itself suggests, AI is a technologically derived intelligence. But AI models mostly just repeat what they have been taught. They don’t really “know” things or think like people do. When truly original “thinking” is required – such as creating an original, testable scientific hypothesis – it turns out that current AI models are quite dumb.

Looking at it through this lens, is AI a bane or boon to today’s CFOs?

With all the buzz around generative AI in business, many finance professionals are eagerly waiting to see what the future will hold for AI usage in accounting and finance. Overall, the sentiment seems to be positive, although many are taking a more cautious approach as they wait to see where and how it will be utilized. But while AI integration is still in its early days for most small to mid-sized businesses, companies of all sizes across all industries have been benefiting from Machine Learning (ML) for decades and can largely credit their success to doing so.