Ahmed Ezzat, ACMA, CGMA, is rather busy.
He’s the CFO of a venture capital and private-equity company in Saudi Arabia. The company manages a significant portfolio of investments across various sectors with a streamlined team. Ezzat’s role includes participation on multiple startup boards, helping guide their strategic direction. Part of his work involves evaluating numerous investment applications each year, leveraging advanced technology to enhance the assessment process and ensure a comprehensive analysis of potential investments.
“Managing extensive data is challenging, and we continuously refine our processes to capitalize on potential opportunities effectively,” he explained in a recent interview with FM. “The investment decision is critical, especially for a tech company in the early stage.”
In recent years, as part of his company’s tech-forward approach, Ezzat has been using generative AI to augment his reviews of companies seeking investment — looking for the strategic strengths and weaknesses in scores of startups.
It’s part of a larger trend: Finance leaders, executives, and board members are trying to use generative AI and machinelearning tools to augment strategic decision-making, and technology companies are racing to help them.
Some companies have even appointed AI systems as virtual advisers to their boards, with the promise of surfacing hidden trends and steering a company’s financial future.
But many individual finance leaders, including Ezzat, have started with much smaller experiments. They’re finding ways that emerging technologies can expand the depth and breadth of an executive’s decision-making process — and they’re learning to work around the technology’s shortcomings.
In a series of interviews for FM, Ezzat and other finance leaders shared their early impressions of how AI could support strategy and leadership.
“If you are not learning yet about ChatGPT and AI tools, how [they] work, and how to integrate [them] with your system, I think it’s almost too late,” Ezzat suggested. “If you didn’t start yesterday, start now.”
Starting small: How finance leaders are applying gen AI
For some finance leaders, generative AI agents have already become a personal tool for planning, analysing, and communicating clearly.
As Ezzat reviews a startup’s proposal, he might ask ChatGPT to review the basics of its business pitch. Then he’ll ask the system to apply business frameworks, such as a strengths, weaknesses, opportunities, and threats (SWOT) analysis or Porter’s Five Forces, to the proposed business model.
For others looking to test generative AI tools, remember to review assurances from the tool provider regarding data privacy, security, and ownership before uploading documents or making statements that may contain confidential or sensitive information to a generative AI system.
Often, Ezzat has found the AI makes astute observations. For example, one startup was selling a financial service for consumers.
“I liked this idea,” Ezzat said, adding that he could imagine using such a service. But the AI quickly surfaced a concern: The business model had low barriers to entry.
“ChatGPT came back and said, ‘This market is very easy to enter by other competitors,’ ” he said.
Indeed, when this writer gave ChatGPT a description of the same business model and asked it to run an analysis, the AI bot produced the same concerns. It also listed several other risks — such as cultural resistance to change, interest rate sensitivity, and the risk of overextending credit to consumers — as well as several sensible strategic recommendations.
None of the AI ideas were all that original. Ezzat, with his experience, surely would have thought of them himself. But the software agent raised worthwhile questions and successfully drew connections to numerous related concepts and ideas.
In turn, Ezzat immediately knew what questions he wanted to ask the startup’s founders. He believes AI’s role for leaders will be “enhancing their ability to process and analyse vast amounts of information and align this information with a company’s strategic plan”.
Other finance leaders are using AI in similar ways to generate ideas, to raise questions, and to support and expand research to streamline the strategic planning process (see the sidebar, “Using AI as a Research Assistant”).
No matter how they use it, finance professionals should keep in mind that using generative AI-sourced information without ensuring its validity may complicate their fiduciary duties. If the software’s methods and inner workings are unclear, but they are relying on it to make decisions, it may raise questions about ethics and standards, warned Russell Tucker, ACMA, CGMA, group finance manager for a multi-family office in England.
Could AI have a role on the board?
While finance leaders experiment with generative AI at a personal level, some companies have started to dream much bigger. Could AI itself take on enhanced strategic roles, especially on the board?
A Hong Kong venture capital fund said an AI system had an informal adviser role for its board of directors, and a major company in the United Arab Emirates has done the same.
But some finance experts remain sceptical of the idea that AI will advance into a true leadership role anytime soon.
“I struggle to believe there’s an all-singing, [all]-dancing AI member that can hit all professions and functions appropriately,” said James Owen, FCMA, CGMA, global CFO, Profiles Division at Kantar.
Instead, he sees AI playing an information processing role — with potential strengths such as tracking board action and helping board members prepare for meetings.
“Everyone at the table will have had their pre-briefing from an AI-inspired source,” Owen predicted.
Generative AI could also become an interface for the board and other leaders to tap into a company’s deeper data troves and machine-learning capabilities.
As the technology becomes more reliable, instead of depending on dashboards that highlight particular data series — or waiting for quarterly updates from staff — CFOs and board members could use natural language interfaces to simply ask an AI agent for specific analyses of large amounts of company finances, forecasts, and other data.
However, at least for now, the technology may not be as painless or powerful as it’s made out to be. For example, Microsoft has ambitious plans for its Copilot platform to tap into a company’s datasets to generate insights and content based on plain-language inquiries.
But Owen cautions that in its early days, his company’s implementation of Copilot has required troubleshooting and oversight. The technology struggles if files and folders are not uniformly organised, he said. it can’t always “make the linkage” between differently organised files and data, Owen explained. “It’s teaching us to be a lot more organised and a lot more sophisticated.”
It’s a symptom of a larger issue with implementing AI systems, and not just generative AI. “You need structured data for machine learning to be plugged into. And I feel there’s a lot of organisations still in the early part of that journey,” Owen added.
Preparing for AI-empowered leadership
Business technology companies are steadily incorporating generative AI into software most companies rely on, from cloud accounting platforms to enterprise resource management systems.
At the same time, deeper and more effective AI capabilities are being baked into consumer devices and software.
The ultimate limits of this technology have yet to be determined. It may never reach the heights that some are promising today — a truly autonomous system that can execute complex tasks from start to finish.
However, it seems clear that generative AI already offers potent benefits for many of the tasks most important to executives: analysing, summarising, and communicating.
“You need to understand, not necessarily how does it work, but what can it do? What can’t it do?” said Donny C. Shimamoto, CPA, CGMA, managing director of the CPA firm IntrapriseTechKnowlogies.
Those answers should become clearer as the initial hype around generative AI dies down, Tucker said. “We can figure out where the limitations are and then implement the technology to reduce all the things that we do that are time wasting,” he said.
For Ezzat, there’s a twofold task ahead: Individual leaders need to improve their AI literacy, while organisations need to understand how generative and other types of AI can support their strategic decision-making.
“We need to identify specific areas where AI can close the gaps in decision-making and enhance strategic forecasts,” Ezzat said.
Within a matter of just a few years, these experts predicted, AI skills will be a key part of a leader’s skillset — if they’re not already. “We … need to take on AI and implement it in a way that we’re all empowered by it and not replaced by it,” Owen said.
Using AI as a research assistant
Many finance leaders are using consumer-grade AI products like ChatGPT as research assistants — skimming through materials to surface key ideas. As a research tool, AI can help:
1. Quickly digest large datasets
“I think it’s really good in terms of digesting information,” said Russell Tucker, ACMA, CGMA, group finance manager for a multi-family office in England. “For me it’s processing articles, PDFs, books — getting through the data, in order to speed up that process for me, because obviously, day to day, we’re really busy.”
2. Streamline your searches
An AI query can sometimes prove more efficient than a web search. Traditional search engines lead to webpages that could be out of date, are loaded down with ads and paywalls, and may or may not answer your question.
At its best, generative AI can directly answer a question by tailoring its knowledge base to constraints provided by the user. No surfing required.
3. Clearly communicate your findings
Generative AI can also help with explaining research and ideas to others. Tucker uses it to simplify and summarise his writing.
“I’m a really technical guy. Sometimes, I’ll use it to try and bring things into a layman’s term and help present data in a different way,” he said.
4. Transcribe conversations
AI transcription services, such as Otter and Rev, don’t just produce written records of meetings. They also identify key insights and decisions made during meetings, which is helpful for executives who spend much of their day on Zoom or Teams.
Remember: Be cautious
Of course, these tools also have a reputation for making false statements. So, while their developers have worked to reduce “hallucinations”, fact-checking AI answers remains mandatory.
An overreliance on AI can lead to not just misstatements but, potentially, strategic mistakes. While it can be helpful for basic questions and initial research inquiries, it’s unlikely at present to come up with truly novel ideas, and it may struggle with situations that are not addressed in its knowledge base, said Donny C. Shimamoto, CPA, CGMA, managing director of the CPA firm IntrapriseTechKnowlogies.
Andrew Kenney is a freelance writer based in the US. To comment on this article or to suggest an idea for another article, contact Oliver Rowe at Oliver.Rowe@aicpa-cima.com.
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Articles
“ChatGPT: Use Cases and Limits to Its Reliability”, FM magazine, 2 May 2024
“4 Considerations for Finance Teams About Gen AI”, FM magazine, 19 April 2024
“Generative AI: What’s the Potential?”, FM magazine, 12 February 2024