CFO

This a blog post from our partner Workday Adaptive Planning, highlighting key findings in the “Global CFO AI Indicator Report,” which Workday commissioned with FT Longitude. 

While the opportunity for AI in finance is nearly unlimited, it can also be overwhelming. To clarify a path forward, we created the “Global CFO AI Indicator Report,” commissioned with FT Longitude.

The CFO role has always been a pressure cooker—but today’s finance leaders face higher expectations than ever. To fulfill their charge of increasing efficiency and managing costs while driving deeper insights, CFOs understand they need to embrace the promise of AI.

The potential value is huge: generative AI can cut through lengthy reports by highlighting relevant information. It can automate repetitive manual tasks such as gathering and reconciling information at period end. It can detect anomalies and manage exceptions with lightning speed, providing real-time recommendations so teams can turn their attention to higher-value strategic work.

While the opportunity for AI in finance is nearly unlimited, it can also be overwhelming. To clarify a path forward, we created the “Global CFO AI Indicator Report: Four Steps for Finance Leaders to Expedite Time to Value with AI,” commissioned with FT Longitude. Through extensive research this global report explains AI’s impact on everyday finance duties and underscores the urgent need for finance leaders to start embracing AI and explore use cases.

In the words of Michael Schrage, a research fellow at the MIT Sloan School of Management’s Initiative on the Digital Economy, AI gives CFOs a “wonderful opportunity to revisit the fundamentals of value creation, capital allocation, capital management, and regulatory and organizational compliance.”

AI Pioneers: Paving the Way

To serve as our North Star, we separated the top third of all respondents—including CEOs and the heads of finance, IT, and HR—who responded to our survey, based on their level of AI investment and adoption maturity. This cohort, which we call the AI Pioneers, has already embraced AI to work more efficiently and create significant value.

Among AI Pioneers, 195 of those are in finance. They are working faster and more efficiently, finding more opportunities to reduce risk, and delivering significant strategic value to the business.

These respondents also express higher confidence in AI’s ability to deliver key benefits. Consider: more than half of finance AI Pioneers (52%) call the technology a gamechanger for the finance industry, compared to 39% of finance respondents overall. Similarly, 43% of finance AI Pioneers say AI will drive increased revenue and profits, and 39% believe it will boost data-driven decision-making, versus just 30% and 32%, respectively, of overall finance executives.

Based on our research, we expect this divide between AI early adopters and everyone else to continue to grow. This gap will be particularly problematic in the finance world, where they have been slightly slower to adopt and implement AI than those in other functions: only 31% of finance teams have made good progress in deploying AI to automate workflows, while 32% of HR teams and 41% of IT teams have done so.

To follow AI pioneers in creating an actionable AI strategy, finance should start to get their data in order, and then implement small, tangible use cases that produce immediate results. From there, confidence and investments in the technology can expand.

The Data Imperative: Why Strong Data Management Matters

Managing ever-increasing sources of data is proving to be a significant struggle for finance. In fact, 63% acknowledge that their company’s data is somewhat or completely siloed. This doesn’t bode well for AI, which relies on clean data to deliver high-quality outputs. To truly harness the power of AI, finance teams first need a strong data foundation that can unify and contextualize disparate data sources.

Right now, finance teams everywhere have room for improvement in this realm. Only 7% of finance AI Pioneers find their data fully accessible, while a staggering 41% report siloed data. Among other finance teams, it’s even worse, at 47%. Because they’re naturally positioned to lead the implementation of AI in data-focused processes, finance departments should embrace a robust data strategy immediately so they can reap AI benefits down the line.

Creating Value: Hitting the Gas on Finance Transformation

As finance teams’ age-old responsibilities around reporting cash flow, investments, and P&Ls become increasingly automated, CFOs face a growing imperative to lean into value creation through improved access to data and deeper, more informed analysis. With AI-enabled workflows, today’s CFOs are in a unique position to connect the dots and become a key value architect within their organization.

No wonder, then, that AI Pioneers are already seeing the benefits of AI to improve value delivery. Only 23% of this group expressed dissatisfaction with the number of administrative tasks their teams need to complete—versus 34% of finance respondents overall.

Leaning in: The Best Way to Mitigate Risk

While the repetitive tasks in the finance function provide obvious use cases for AI, the function’s emphasis on risk mitigation and predictability make it understandably skeptical of the technology’s potential pitfalls. 

In fact, 35% of finance leaders report finance and accounting as the area of the business least prepared for AI and ML integration, with cybersecurity, compliance, and privacy capabilities a close second at 30%. In addition, when we asked finance heads to what extent they were concerned about specific issues which might arise as AI and ML become more integrated within their function, we found that 36% believed a lack of AI and ML transparency would weaken security and compliance. 

We also asked respondents what they believed would be the biggest risks to AI and ML adoption in finance, finding additional concerns around errors, bias, and security (see below).

Though it may at first seem counterintuitive, the best response to these valid concerns is to get your data in order and lean into early adoption. Not only does embracing AI allow finance teams to acclimate to the technology faster than competitors, but the AI itself will mature and become better as it ingests more data. Despite skepticism, the time to adopt AI is now.

As the “CFO AI Indicator” report concludes: “Finance may be a naturally risk-averse, careful segment of the business, but it is also one of the most promising areas in which remarkable innovation and change is possible.” By embracing AI and building a robust data strategy, finance teams can emerge as changemakers within their organization, fearlessly pushing beyond traditional roles to create new value.

Get your roadmap to value creation here: “Global CFO AI Indicator Report: Four Steps for Finance Leaders to Expedite Time to Value with AI.”

For insight into additional aspects of the C-suite and early adopter advantage, download “C-Suite Global AI Indicator Report: AI Is the Ultimate Level-Up.”

More from our FP&A Done Right Series:

The Mandate for Business Agility

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Fortune Interview with Workday’s CFO on Artificial Intelligence

This is an excerpt from a blog post from our partner Workday Adaptive Planning. It is a recent discussion between Workday’s Terrance Wampler and Stanford Professor Erik Brynjolfsson, explaining why CFOs are well-positioned to lead the AI revolution using a human-centered approach to artificial intelligence.

Erik Brynjolfsson, a professor at the Stanford Digital Economy Lab, has some advice for finance professionals concerned about whether artificial intelligence (AI) will replace their jobs: “AI is not going to replace CFOs. It is going to replace CFOs who don’t use AI with those who do.”

I [Terrance Wampler] had a great discussion with Professor Brynjolfsson recently at the Workday Future of Intelligent Finance Tour in San Francisco. The event—hosted in partnership with American Institute of Certified Public Accountants-Chartered Institute of Management Accountants (AICPA-CIMA) and Accenture—was designed to help finance and IT professionals leverage AI, machine learning (ML), and other advanced technologies to accelerate their journey to becoming finance futurists.

Brynjolfsson, who also serves as a senior fellow at Stanford’s Institute for Human-Centered AI, gave attendees a crash course on how AI will reshape the future of finance as we know it. Having just come from a visit to Washington, D.C., to brief the White House and the Council of Economic Advisors on the impact of AI, Brynjolfsson has a front-row seat to the potential for AI to change workforce dynamics. 

“In the early stages of AI, we knew that low-skilled labor would be impacted,” he told me. “As the technology has progressed, we’re seeing that professional workers—CFOs, accountants, lawyers, doctors—are going to be very much affected. Affected doesn’t mean automated. It doesn’t mean replaced. Rather, AI is going to augment your abilities and give you the freedom to do new things.” 

I couldn’t agree more with that positive assessment, which is why we’re investing so heavily in generative AI as the innovation engine for Workday Enterprise Management Cloud. As the group general manager for Workday’s suite of solutions for the office of the CFO, I see generative AI as an enabler of finance’s dual role as value protector and value creator.

Value protection tasks such as internal audit, risk management, and regulatory compliance can benefit from AI’s ability to comb through vast amounts of data to detect and surface anomalies before they destroy a company’s value or market reputation. Large language models (LLMs) can be trained to stay updated on the latest financial regulations, ensuring that compliance is always up to date. They can also assist in risk management by identifying patterns in data that might signify potential risks and by building robust risk models that consider a wide array of factors.

AI can also help drive value creation, whether that’s automating routine tasks to drive cost savings or enabling top-line growth. LLMs, for example, can help predict customer behavior, create more accurate forecasts, and improve scenario modeling by processing a large volume of data and considering a multitude of variables. Augmenting the capabilities of financial planning and analysis (FP&A) teams would allow them to prepare for a wider range of potential outcomes, making planning more resilient and adaptable to changing market conditions. 

Thanks to productivity gains like these, Brynjolfsson predicts that generative AI will be bigger than any of the technologies we’ve used over the last 10 years. He provided an example from new research he led on how generative AI is boosting call center productivity. 

“A couple of years ago, we teamed up with a company and a couple of Stanford professors and graduates to start a company that helps call centers do a better job,” he said. “And what we found was that the operators who used the AI model were dramatically more productive and more successful than the ones who didn’t, with the least skilled operators 35% more productive.” 

Brynjolfsson went on to explain that the model learned from the most successful operators, listening in on their conversations and identifying phrases or suggestions that improved customer sentiment. The model then passed on those skills to the newest operators. “That’s the kind of tacit knowledge that was previously really hard to automate.”

Generative AI and the CFO Role

Gartner analysts recently noted that CFOs are best positioned to help lead the implementation of generative AI in corporations because they have more insight into opportunities to leverage the technology to reduce costs, improve productivity, and increase revenue streams. “The CFO should be on the frontier of the AI revolution,” Brynjolfsson said. “CFOs understand how to work with unstructured and structured data and do sophisticated analyses on that data, which is why they can make such a big impact.” 

Brynjolfsson also sees human resources teams benefiting. “I did an estimate a few years ago and found that the value of human capital in the U.S. economy is a little over $200 trillion—10 times the value of the gross domestic product (GDP). But the problem with human capital is it’s very poorly measured and understood,” he said. “There are a lot of soft intangibles in there. AI’s large language models can do a lot to capture and understand the value of your human capital.” 

Given AI’s power to disrupt the economy, I asked Brynjolfsson about his take on the mood in Washington around regulating AI.

“I came away from my trip really impressed with how up to speed the government officials I met with were on generative AI,” he noted. “They understand that there’s a tidal wave coming that will be bigger than the impact of the pandemic on remote work, and they are taking it very seriously.” 

Brynjolfsson closed out our chat on a positive note, predicting that AI could potentially double the productivity rate currently estimated by the Congressional Budget Office over the next decade. He also sees AI giving us more resources to address challenges we face on the healthcare front, such as cancer, and on the educational front, such as personalized education. The reason is AI’s ability to unlock human potential versus just seeing it as cost-saving automation. 

“Any one of you who has tried to call an automated voice response system knows it can be very frustrating, especially when there’s a long tail of questions that we ask that aren’t common,” he said. “We humans are much better at dealing with exceptions than machines, so a good partnership is where AI can answer common questions and humans can deal with exceptions. AI has a much higher upside in terms of creating additional value than simply trying to take costs out.” 

Read the full blog post on the Workday blog.

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FP&A Done Right: Trends in Accounting and Finance