Generative AI and Finance

In this episode of the Business Excelleration^® Podcast, what impact will generative AI have on the world of corporate finance? How can finance leaders get started using artificial intelligence to improve their operations? A discussion with Tom Willman, a Principal in our Finance Executive Advisory Program, and Vin Kumar, a Principal and The Hackett Group’s Digital Finance & GBS Advisory Program Leader.

Welcome to The Hackett Group’s “Business Excelleration Podcast,” where week after week we hear from experts on how to avoid obstacles, manage detours and celebrate milestones on the journey to world-class performance. This episode is hosted by Tom Willman, principal and global practice leader in Finance Advisory for The Hackett Group. Today’s episode features a conversation with Vin Kumar, principal and AI and Digital Operations practice leader. Together, they will discuss the impact of generative artificial intelligence (AI) on the world of finance, how finance leaders can get started with generative AI and more!

To begin, Vin discusses the difference between cognitive and generative AI. As we know, AI is

not new, but cognitive AI refers to the machine instructions where humans feed an algorithm to run it. We have to provide the instructions for the machine to assist us. In generative AI, we do not need to spell out all the instructions to the machine. It is able to make decisions on its own and has gone through training in that particular domain. This is what has fundamentally changed between cognitive and generative AI, and the impact of generative AI will accelerate the automation, give new skills and provide digital assistance to finance professionals in making decisions.

There has been a lot of hype around generative AI and robotic process automation (RPA). However, as we saw with ChatGTP, the accuracy has declined and didn’t deliver the benefits that many expected it would. Vin explains how we do not need to temper our expectations with generative AI, and he expects that this will be different from what companies saw with RPA. For RPA, the level of specificity that had to be scripted was extreme, and they had complicated decision trees to decide what had to be scripted out for RPA. This took a lot of time, and there were incorrect answers. His advice is to use the enterprise version of generative AI solutions because one cannot control the public version and will get more incorrect data. He suggests using the enterprise versions of generative AI solutions like Microsoft or IBM. Enterprise generative AI has the ability to protect data, has higher accuracy and higher quality of the output. There is always a hype cycle in technology, and he predicts generative AI will fundamentally change how we are processing and servicing from a financial organization, but this will take time to be delivered and for professionals to get trained. Vin says the next five years will show the significance of how generative AI will impact organizations.

Next, Vin discusses how finance organizations will leverage generative AI and what companies are doing today. He is seeing companies exploring this, and clients are also always in exploratory stages for generative AI. Part of the reason for this is the enterprise version of generative AI is released on a limited basis in the industry, with only a limited version by the providers. He sees companies exploring and coming up with proof of concept in generative AI solutions that are embedded with other applications like ServiceNow in managing case studies and Microsoft Copilot in office products. He is seeing generative AI used in cases with external research for summarizing market data, quick scripts, proof of concept, visual basic script, etc. This script could’ve taken a couple of hours for the analysts to do it, but with generative AI, it took 30 minutes to draft it, look it over and send it out. Generative AI will be used mainly for a digital assistant and not in a full-scale employment realm. There are different domains that generative AI specializes in, and we are still very early on in terms of companies figuring out how to get this going in finance.

In closing, Vin suggests that finance leaders start educating the finance leadership teams on what generative AI is and the enterprise version. Companies need to start thinking through the approach they should be taking, the investment in generative AI, which team will be on this, how to address this and what tools the company can start implementing in a gradual manner from next year onward. He believes in the next three to five months finance leaders should start working through these questions as a company to prepare for generative AI. Finally, Vin states that most companies still have foundational work to do and shouldn’t feel bad about where they are but should get started.

Time stamps:

• 0:49 – Welcome to this episode hosted by Tom Willman.
• 2:05 – The difference between cognitive and generative AI.
• 4:25 – Hype around generative AI.
• 5:03 – Should we be tempering our expectations for generative AI?
• 9:27 – How finance companies will leverage generative AI.
• 13:14 – Suggestions for finance leaders on how to get started with generative AI.
• 16:14 – Closing remarks.