Russell Lester, CFO of payments software provider Versapay, says there are two secret weapons that have become critical for tackling the growing demands of his job: leveraging valuable data and cultivating a team of curious thinkers.

Both align closely with what he sees as the evolving role of the finance chief as a “strategic adviser” in the post-COVID-19 pandemic era.

“There’s no time like now to be a CFO,” Lester said during a podcast posted earlier this month by software-as-a-service management company Zylo. “It is not for the faint of heart.”

CFOs are currently faced with a “perfect storm” of challenges: macroeconomic pressures, remote workforces, and a massive acceleration of data use among businesses, just to name a few areas, according to Lester, whose career in corporate finance has spanned over 20 years.

Lester joined Versapay in 2022, according to his LinkedIn profile. Prior to that, he served as CFO of scheduling automation platform provider Calendly and e-mail marketing and sales automation company Keap. He also previously did a stint at Intuit as senior director of analytics.

The veteran finance leader isn’t alone in seeing the dawn of an unprecedented era for his profession.

In a June survey, nearly half (48%) of CFOs at small-and-medium-sized businesses said they were living through the most difficult time in their career due to a combination of factors, including supply chain issues, geopolitical risks and rising interest rates.

CFOs are also increasingly dealing with the stress of mission creep, with their responsibilities reaching well beyond the realm of accounting ledgers and excel sheets to areas such human resources, cybersecurity, and customer service management, as previously reported by CFO Dive. 

However, Lester said he also sees opportunities for CFOs in the current environment.

“More and more CEOs are saying they’re looking for strategic advisers — they want the CFO to be the thought partner,” he said during the podcast. “It’s because we see it all. We’re privy to all of the good, and the bad, and the ugly that goes on behind the scenes, which the numbers bear out. And so, we’re here to tackle that challenge with data at the epicenter of all of that.”

But compiling a bunch of data and reports isn’t good enough, according to the finance chief. “It’s about presenting that data in context for people... And so you need the type of talent that can ... assimilate information quickly and connect pieces together.”

SaaS management is one area where Lester sees an opening for the finance team to swoop in as the “hero” of the organization, in partnership with the IT department.

In 2022, for the first time ever, more money was spent on SaaS than on-premise software, and by 2026, SaaS spending is expected to comprise two-thirds of all enterprise application revenue, according to Zylo’s 2023 SaaS Management Index Report, released in January.

However, along with the rapid growth of SaaS spending, “underutilized applications, redundant functionality, chaotic renewals, and ungoverned purchasing have become the norm,” Ben Pippenger, Zylo’s chief strategy officer and co-founder, said in the report’s introduction.

While this has traditionally been the turf of the IT department, it also falls squarely under the jurisdiction of the finance function, according to Lester.

“It’s natural for finance to be interested in understanding where there’s wastage in the system,” he said.

The generative AI hype cycle is still going strong, but what’s really exciting about the technology’s advent is that it’s put the AI discussion at the CEO and board level, Katie Stein, chief strategy officer and and global business leader, enterprise services and analytics for global professional services firm Genpact, said.

It’s “really recentered the discussion on, ‘every company should be an AI company in the future: What does that mean?’” she said in an interview.

Answering that question effectively means having a transparent understanding of how introducing the technology will affect all aspects of the business: a space where the company’s CFO, as well as other senior leaders, must play a critical role.

Developing an AI ‘SWAT team’

Genpact is one among many companies which have moved swiftly to incorporate generative AI’s capabilities, announcing a partnership with Microsoft — the backer of ChatGPT creator OpenAI — late last month to enable its business teams to access Microsoft’s OpenAI services. Earlier this month, the New York-based company announced it had integrated generative AI into its own intelligence platform, allowing clients to access the tool to help make operational decisions.

The company is viewing the integration of generative AI as an “offense strategy move,” Stein said, tackling it with a “cross-functional SWAT team” which goes up to Stein as the CSO as well as the company’s CEO, with whom they meet regularly to provide updates.

Genpact also used a series of hackathons to help democratize idea generation surrounding the technology, and is now in the process of reviewing those ideas, figuring out how to potentially scale them as well as determining the value proposition to the client, she said.  

“I think this is so early, that companies that are taking it really seriously, are really engaging all the way to the CEO,” she said in an interview. “And then as an executive team, we meet once a week, where we go through where we are in the plan, what our commitments are, what we need to change, because you have to be agile.”

As the financial nexus of the business, CFOs are essential when it comes to creating that agility — the CFO “at the end of the day is sort of the arbitrator that doesn't care whose land it is, what they care about is what the financial metrics are going to be,” Stein said.

Finance chiefs also have the ability to bring together all of the disparate information needed for the business to form a clear picture of how to move forward with upcoming initiatives.  

Stein pointed to bringing AI to the order to cash process as an example, which requires senior leadership to have a deep understanding of a host of often siloed information, including what the customer is looking for, how such a move could affect one’s supply chain, and current sales — all data the finance chief can help to aggregate.

“So when you come back to this integrated execution management, I think the CFO becomes this really critical stakeholder driving all of these teams (to) play a team sport, versus playing for their individual optimization,” she said.

Bracing for the AI culture shift

With everyone eager to become a generative AI expert, the nascent technology’s introduction also changes some “fundamental things” regarding not just one’s business strategy but one’s culture, Stein said.  

The advent of generative AI means that companies like Genpact can now move into areas they may not have considered previously — such as software engineering or digital marketing — “because it’s a scale game,” she said. That changes when tools like generative AI can take half of a software engineer’s potential workload, she said.

“Certainly we're looking at it that way, which is, how do we aggressively attack spaces that before maybe were a little in our periphery vision?” Stein said.

This is a fundamental shift, forcing leaders to consider not just where to put such technology in their existing processes, but “how does this change what we can offer, how we deliver our services, where we participate in which markets?” Stein said.

The democratization of AI also means that businesses need to prepare for the evolving ways their workforce will utilize the tool as well. Because of the technology’s open source nature, companies now must contend with the majority of their employees using generative AI — both in the workplace and on personal devices — rather than just a handful of their workforce.

Given that shift, Stein also stressed the importance of developing responsible AI at one’s organization, a topic which is becoming a key area of focus for senior leadership. Michael Kelly, partner and management consulting consultant at Big Four firm Ernst & Young, noted CFOs will need to spend some time determining the technology’s “guardrails” in a recent interview with CFO Dive.

“I think responsible AI is a really important topic that boards are talking about, which is not just data privacy and IP privacy, we have to come back and reevaluate all that, but also values and culture,” Stein said. “With all of your employees accessing and using AI, what are your values?”

Since the launch of Open AI’s ChatGPT last November, the transformative potential of the technology has captured companies’ attention — but as executive leaders take a look at where such tools could best fit in their businesses, it can be difficult to choose a starting point.

The best thing for CFOs today is just “take a look at their operations,” Michael Kelly, partner and management consulting consultant at Big Four accounting firm Ernst & Young said. When developing a game plan for generative AI and next-gen AI solutions, CFOs can “start with the key basics,” Kelly told CFO Dive in an interview.

“You look through your order cash, procure to pay, or even the hire to retire type format,” he said. “And you start thinking about, ‘okay, where are the touch points? Where are the manual efforts that are happening in this?’ Because really, what you want to do is move the needle to be a touchless process.”

Developing ethical AI

CFOs looking to bring generative AI and other emerging technologies to their businesses can start with areas like financial planning and analysis — the use of machine learning and other AI solutions have helped FP&A to advance over the past few years, but tapping next-generation solutions can help finance leaders to “really move the needle” in that area, Kelly said.  

By combining internal and external data sources with next-gen AI tools, companies can start to get deeper insights on their data, he said, as well as reduce the time and the people needed to complete key processes. Kelly cited EY clients who have reduced the time it takes to produce a forecast down to 90 minutes from six to eight weeks, for example.

Payroll is another area where next-generation AI could be tapped, easing friction when dealing with the benefits and queries that go along with the deceptively complicated process, he said.

Before, dealing with such queries was a manual process. Now, with emerging AI tools, “I can put some capabilities in front, and kind of own that customer experience, and answer those questions within a couple seconds and provide that feedback back to the employee,” Kelly said.

Among its other AI experiments, EY itself is working with Microsoft — which has invested heavily in ChatGPT parent OpenAI — to develop a generative AI chatbot that can help to answer employee payroll queries, the companies announced in early June. The chatbot will leverage both the Microsoft cloud service and ChatGPT in the software firm’s Azure OpenAI service, Microsoft said, which will help to “analyze information from pay slips, tax regulations and employer policies” to help answer such questions.

Paying attention to the data that you are funneling into your generative AI solution is a key part of using the technology effectively — both when it comes to making an informed investment decision when experimenting with the tool and in order to use it ethically, Kelly said. EY, which started to build on OpenAI’s underlying engine several years ago, is taking a careful and measured approach to deploying the technology in the face of data privacy concerns and the nascent tools’ limitations, Jeff Wong, EY global chief innovation officer, told Industry Dive sister publication CIO Dive in a February interview.   

“The flip side of this is, how do I get to do responsible and ethical AI, which is the other piece you’ve got it watch out for,” Kelly said. “So this is where the CFO is really going to have to spend a little bit of time on, is what are the guardrails on using AI?”

Getting ahead of the AI learning curve

Figuring out where generative AI solutions may be best deployed in one’s organization is only the first step in using the emerging technology effectively. CFOs, who are facing something of a learning curve when it comes to the swiftly developing tool, should take a two-pronged approach to its deployment.

First, they should identify what underlying technologies or solutions they need to support the use of generative AI in their businesses, and second, they need to figure out what skills and capabilities their finance staff needs to have to utilize the technology, Kelly said.

Just experimenting with some of the available tools can help to provide companies with an edge while generative AI is in such a nascent stage — allowing employees to play around with tools like Microsoft’s data visualization solution Power BI, for example, can be a “quick, very effective and costly alternative to start providing some new skills for your employees, because the employees are all looking for the experience,” Kelly advised.  

This is especially necessary as CFOs continue to face both talent acquisition and retention struggles in their finance departments, and “if you aren't kind of employing and deploying some of these new tools and capabilities, you're going have a hard time either trying to attract the folks or even better retain them, because they all want these great, fabulous experiences going forward,” Kelly said.

CFOs are also examining how generative AI could be put to use to free up their employees’ time, making that practice and experimentation all the more critical.

Historically, approximately 60% to 80% of finance staff have been focused on producing the company’s financial results, Kelly said, with the remainder focused on decision analytics and insights. However, finance leaders have been attempting to “flip” that percentage, he said, with the aim of having that 60% to 80% focused on analytics and insights.

“The next gen AI and some of the new capabilities that came out the last three, four years have now enabled people to flip that curve a little bit,” he said. “So it’s, what do I do with the information, not spending all my time just trying to produce it.”

Revenues of generative artificial intelligence offerings across a broad range of categories are forecast to reach $3.7 billion this year and expand to $36 billion by 2028, according to a recent report by S&P Global Market Intelligence.

While companies like Google and Microsoft have been experimenting with generative AI for several years, the wide-scale commercialization of the technology is a more recent phenomenon, with many vendors now offering products that are still in the beta or initial launch phase, according to the study.

“We’re at the very early stages of this market, but it’s evolving very quickly,” Nick Patience, managing analyst of Data, AI, Infosecurity & Risk at S&P Global Market Intelligence, said in an interview.

Generative AI refers to tools capable of producing new content, such as text or images, based on what they’ve learned.

Large software vendors and a flurry of emerging startups are in a race to capitalize on the popularity of ChatGPT, a generative AI tool created by Microsoft backed-Open AI. North America represents the largest market for generative AI, with the greatest number of vendors and developed infrastructure to handle the scale of adoption, the report said.

Datarails, a New York-based software provider, announced in March that it was testing ChatGPT-like capabilities in a financial planning and analysis tool for CFOs. Also, San Francisco-based Brex, which provides corporate expense management tools, said in March that it was launching new CFO tools powered by the same machine learning and natural language processing technology behind ChatGPT.

As the nascent generative AI market explodes, it’s also prompting regulatory concerns in the U.S. and abroad. 

“While the technology is moving swiftly, we already can see several risks,” Federal Trade Commission Chair Lina Khan said in a New York Times op-ed piece last month. A handful of powerful businesses control the “necessary raw materials” that startups rely on to develop and deploy AI tools, raising competition questions, she said. And, in some cases, generative AI tools are trained using sensitive, personal data, raising privacy concerns.

The White House and members of Congress are studying policy challenges posed by the market. In the meantime, Khan said the FTC stands ready to police industry players using existing legal authorities.

Overall, the study by S&P Global Market Intelligence analyzed 263 software companies in the world that provide generative AI products, including text, images, audio, and video, according to Patience. Of those, 117 are companies that specialize in text generation, including Jasper, provider of an AI writing tool designed to generate marketing copy and Grammarly, which offers an AI-powered writing assistant, he said.

“In one sense, the whole market kicked off last November, when ChatGPT was launched,” Patience said. Still, despite a flurry of generative AI-powered tools that recently flooded the market, the technology itself isn’t new, he added.

An early example of the technology is BERT, a natural language processing algorithm created in 2018 by researchers at Google, according to the S&P Global Market Intelligence report. “Generative AI capabilities have evolved to encompass a wider array of outputs, and the market has transitioned in a for-profit direction, from research to monetized products and services,” the report said.

Text generators create text-based content such as business articles, poetry, and research papers in response to a prompt, it said. The results are intended to approximate what a human might write or speak given a similar prompt. 

The text sector is poised to expand at a compound annual growth rate of 50% from 2023 to 2028, according to the research.

“The challenge for many startups is competition for a focused pool of use cases and user profiles, commonly in sales and marketing, and building a strong enough value-add within the AI stack to justify its position as an interface between a business and foundation model APIs [application programming interfaces],” it said. “These challenges will likely lead to a trimming of the long tail of text generator startups.”

In a Gartner survey unveiled last month, 70% of corporate executives said their companies were investigating or exploring generative AI. Nearly 20% of respondents said their organizations had AI projects in “pilot or production mode.” Another 45% of respondents reported that publicity around ChatGPT had prompted their companies to increase their AI investments.

A KPMG survey released in April found that 65% of executives expected generative AI to have a major impact on their organization in the next three to five years. However, nearly the same number (60%) said they were still a year or two away from implementing the technology due to hurdles such as cost, determining clear business cases, and hiring talent to support implementation.

In addition, cybersecurity and data privacy were top concerns for respondents, at 81% and 78% respectively.

CFOs should take a leading part in adoption of generative artificial intelligence rather than solely rely on their IT departments, thereby ensuring the new technology aligns with business strategy and the full range of company operations, according to a Gartner AI analyst.

“CFOs should have a larger role in generative AI than they have in other technologies,” Rajesh Kandaswamy, said Wednesday, emphasizing that recent AI innovations will likely upend the business and operating models at many companies.

A CFO is more familiar than IT staff with a company’s sources of revenue, its biggest costs and its most promising opportunities, Kandaswamy said in an interview at the Gartner CFO and Finance Executive Conference in National Harbor, Maryland.

Assessing generative AI as part of a cross-functional team, “the CFO is probably in the best position to educate the company to start thinking strategically, not the CIO,” he said.

Kandaswamy spoke after leading a discussion by 20 CFOs and finance executives on the opportunities and challenges from generative AI.

Several CFOs hailed the new technology for streamlining tasks such as answering detailed technical questions and writing first drafts of emails or memorandums.

At the same time, the finance executives flagged several risks from the new technology, including the vulnerability of proprietary data, the spread of “deepfake” misinformation, the potential for copyright infringement and the creation of outright fabrications or “hallucinations.”   

When reviewing generative AI content, “always validate it,” Kandaswamy told the CFOs, noting revelations last month that a New York attorney using ChatGPT submitted in court a 10-page brief that cited several bogus court decisions. 

The creators of some generative AI programs have warned about flaws in their algorithms. OpenAI said in March that the accuracy of ChatGPT-4 in business applications is less than 80%. Google says in a disclaimer that “Bard is experimental, and some of its responses may be inaccurate, so double-check information in Bard’s responses.”

Generative AI currently offers a limited, but potentially valuable, set of reliable use cases,  Kandaswamy said.

The technology can provide a starting point for website content, sales memos and marketing material, he said. Companies such as Microsoft and Salesforce have embedded generative AI tools in their software.  

CFOs should consider using generative AI “anywhere they have content generation that is of low risk,” Kandaswamy said.

At the same time, the weaknesses of generative AI — along with its widespread availability — underscore the imperative of constructing safeguards against abuse, he said. “This is a huge moment of democratizing AI.”

CFOs should insist on a policy of “responsible AI,” he said. Such programs ensure that a senior executive is fully accountable for the technology.

Responsible AI guidelines also seek to ensure that the technology serves a broad range of stakeholders; mines high-integrity data; protects against attacks and rogue use; shields user data; avoids harming people, property or the environment; and is explainable, transparent and reliable.

With such safeguards in place, a CFO can confidently encourage experimentation with generative AI, according to Kandaswamy.

Keeping the focus on how technology can aid businesses looking to slash costs can help tech users weather today’s uncertain economy — and keep the tech companies selling the new wares growing.

Ninos Sarkis, the newly-minted CFO for cloud-based e-commerce experience platform Bloomreach, believes his firm is “well-positioned” for the current cycle because it can quickly demonstrate the return on investment its products will provide to potential customers.

“This is hugely critical in decision-making as teams cut down on spending to shrink their cost base,” he said. “They’re more inclined to justify spend if they believe their investment will result in further growth and have a more immediate ROI.”

Championing financial discipline

Large-scale technology companies have struggled to adjust to the current economic environment, with firms such as Meta, Salesforce and Stripe laying off staff and reducing their real estate footprint. As CFOs confronted a slumping economy at the start of the year, part of their bid to reduce expenses included overhauling their technology budgets and zeroing in on the ROI pitch from potential vendors.

Arming Bloomreach with information that will enable the firm to win over customers is a top priority for Sarkis as he takes on the role of CFO. Among other strategic initiatives aimed at fostering growth, Sarkis will “work closely with the executive team to identify high ROI opportunities in go-to-market activities and product development,” he said via email.

Sarkis was named finance chief of the Mountain View, California-based company in May. He previously served as chief accounting officer for digital analytics software platform Amplitude. Before Amplitude, Sarkis logged a 20-year stint at PricewaterhouseCoopers, serving in a variety of roles including partner where he focused on the technology and clean tech sectors, according to his LinkedIn profile.

Over the years he had the chance to learn what a good strategy looks like from watching many companies at Bloomreach’s current stage of growth. 

“From a strategic perspective, I’ve seen the various ways that similar B2B SaaS companies have grown both organically and inorganically,” he said.

Organically, there are “many levers to pull” when it comes to product development and go to market or GTM strategies, he said. In contrast, so-called inorganic growth from outside the firm can come from M&A such as Bloomreach’s acquisition of fellow marketing automation platform Exponea in 2021, he said.

Approaching both types of growth with a discerning financial eye is critical  — Bloomreach is “keeping all of our possibilities” open as it looks to its future growth, and “like any company with over $150 million in ARR, an IPO or public listing is among those possibilities,” Sarkis said.

“Part of my job is preparing to not just be any public company but be a successful public company if or when the time comes,” Sarkis said, which includes “efficient and effective growth through financial discipline on what investments we make,” he said.

The generative AI age 

Bloomreach is also keeping an eye on the fast-evolving AI landscape. Bloomreach, which has employed AI since its inception, has already incorporated generative AI capabilities into its products “to drive efficiency by way of content generation” for channels including email and SMS, Sarkis said.

The company has also fostered partnerships with leading voices in the space such as Microsoft-backed OpenAI, which operates ChatGPT.. The company is “are closely monitoring the evolving digital landscape” when it comes to generative AI, Sarkis said.

Recent breakthroughs in artificial intelligence have dazzled C-suite executives seeking to personalize marketing, juice sales, anticipate customer needs and identify unseen risks.

The explosive spread of Google’s Bard, Microsoft’s Bing chat and OpenAI’s ChatGPT has also triggered backlash. Critics pan AI chatbots as threats to jobs, tools for “deep fake” manipulation and fountains for insights that, although seeming trustworthy, are prone to inaccuracy and bias.

The chatbots pose “profound risks to humanity,” Tesla CEO Elon Musk, Apple co-founder Steve Wozniak, and more than 26,000 other signatories said in an open letter released last month.

AI developers are “locked in an out-of-control race to develop and deploy ever more powerful digital minds that no one — not even their creators — can understand, predict or reliably control,” the open letter says. The signatories call for a six-month pause in developing systems more powerful than ChatGPT-4 and for creation of AI governance structures.

CFOs weighing adoption of AI tools need to look past both the hype and anxiety. They face the challenge of weaving the technology into company operations and reaping immeasurable rewards while not shirking their obligation to limit risk and ensure a worthwhile return on investment, according to AI experts and finance executives.

“The challenge for CFOs right now is that the frenzy around generative AI puts pressure on them to roll this out at scale,” according to Tad Roselund, a managing director at Boston Consulting Group. “You have this commercialization pressure to explore all the benefits of generative AI.”

CFOs need to demystify AI tools — identifying low-risk, high-reward uses — when even the tools’ creators cannot always explain the reasoning behind insights into core strategic topics such as emerging risks, capital allocation and new market opportunities, the AI experts and CFOs said.

To avoid failure when adopting the newest AI, CFOs should try to find a “balance of being urgent but being deliberate,” Roselund said in an interview.

AI for the rest of us

Generative AI and conversational AI such as ChatGPT — both forms of machine learning — widely expand access to advanced computing.

The software can write college essays, computer code, market research reports, jokes, translations, blogs, legal briefs and help in medical diagnosis and drug discovery. They sweep away technical and developmental obstacles and “democratize” AI, offering front-line employees computing power once available to a few, Roselund said.

Broader access has spurred a record adoption rate for conversational AI. ChatGPT hit 1 million users in less than a week, compared with 10 weeks for Instagram and 20 weeks for Spotify, according to DiploFoundation and KPMG.

The market for conversational AI will surge to as much as $20 billion by 2025, or 20% of total AI spending, according to UBS.

The potential market for generative AI may total $150 billion compared with $685 billion for the software industry, Goldman Sachs said. During a 10-year period generative AI may add 7% growth to global gross domestic and push up productivity by 1.5 percentage points.

Use of AI tools has boomed as OpenAI, Microsoft, Google and other AI innovators fight for market share. By providing free or low-cost access, they can vacuum up oceans of user feedback to improve their algorithms and gain an edge.

New AI tools help CFOs analyze data, make financial projections, prepare financial statements, manage risk and more easily supervise treasury and accounting tasks. Employees freed from routine work can turn to more creative, fulfilling projects.

Adobe, Shopify, Instacart and Zoom have adopted generative AI tools. Salesforce in March said it planned to integrate ChatGPT into Slack and meld generative AI into its customer relationship software.

Walmart uses chatbots to inform customers about simple questions including order status and returns. With verbal queries using the “Ask Sam” app, employees can locate products for sale, look up prices and check their messages or work schedule.

CFOs, at the risk of jarring employee morale, can use AI tools to trim headcount. AI automation may eventually shake up to some degree roughly two-thirds of U.S. occupations, Goldman Sachs said.

A list of at-risk jobs underscores the power of the technology to disrupt the workplace.

So-called large language models such as ChatGPT imperil jobs for workers in dozens of professions, including accountants, auditors, financial quantitative analysts, blockchain engineers, interpreters, mathematicians and journalists, according to a study by researchers at the University of Pennsylvania and OpenAI.

The technology over time will streamline at least 10% of the tasks performed by 80% of workers, and half of the tasks done by 19% of workers, the researchers said.

CFOs should not adopt generative or conversational AI without first sizing up its many risks, the financial executives and AI experts said. Some AI tools may end up on the list of much-maligned innovations that, at high cost to early adopters, over-promised and underperformed.

“AI has the potential to be yet another technology in that rogues’ gallery, especially with so much speculation that these AI systems could end up replacing workers,” according to the article describing survey findings by MIT Sloan Management Review and BCG.

AI on the sly

AI tools pose several risks. First, the spread of generative and conversational AI may undermine a company’s ability to manage or catalog AI use.

Employees who retain their jobs after adoption of the new technology will potentially gain access to vast computing power. They may engage in “shadow AI,” or computing without company oversight, and either mistakenly or deliberately leak proprietary or customer data.

Second, companies unable to fully explain how AI tools generate insights may face scrutiny from regulators, lawmakers, shareholders and other stakeholders. The “black box” hazard is especially problematic for asset managers and other AI users with fiduciary obligations.

Third, AI tools expose a company to litigation or a reputational setback by engaging in “hallucination.” They may access flawed or biased data, come to erroneous conclusions and perpetuate inaccuracies or discrimination and stereotyping.

OpenAI acknowledged last month that the accuracy of ChatGPT-4 in business applications is less than 80%. Google says in a disclaimer that “Bard is experimental, and some of its responses may be inaccurate, so double-check information in Bard’s responses.”

Fourth, wrongdoers both within and outside a company could use AI tools to improve deep fakes and other misinformation, or for schemes at phishing, impersonation and intellectual property theft.

Regulators in the U.S., Europe, China and other countries have proposed setting guardrails around AI tools. UNESCO’s 193 member states have unanimously endorsed a framework for averting AI abuses.

“The world needs stronger ethical rules for artificial intelligence,” UNESCO Director-General Audrey Azoulay said in a statement last month. “This is the challenge of our time.”

The Commerce Department this month requested public comment on ways to limit risks of AI. “Responsible AI systems could bring enormous benefits, but only if we address their potential consequences and harms,” Alan Davidson, Assistant Secretary of Commerce for Communications and Information, said in a statement.

CFOs can limit risks and tap the benefits of AI tools, financial executives and AI experts say, by taking four steps:

1. Ensure “responsible AI”

The newest AI tools highlight the imperative of constructing safeguards against abuse, the CFOs and AI experts said.

“You need responsible AI on steroids” and injected at all levels of a company, according to Roselund. “The tone from the top is incredibly important,” he said, underscoring a need to make a senior executive fully accountable for the outcome.

Responsible AI, as described by BCG, KPMG and other consultants, also ensures that the technology serves a broad range of stakeholders; mines high-integrity data; protects against attacks and rogue use; shields user data; avoids harming people, property or the environment; and is explainable, transparent and reliable.

A company adopting AI should create a cross-functional oversight team including data scientists, attorneys and the leaders of the company’s various departments.

The team should uphold standards for testing and quality control and regularly gauge risks, aware that wider use of AI within the company will require agility and shorter response times.

Employees throughout a company should be free to innovate with AI tools and find new uses for the technology but within clear boundaries, Roselund said. They need to “think outside the box but inside the circle.”

2. Widen the conventional concept of ROI

By posing unusually high benefits and risks, AI tools raise the stakes of ROI measurement, the CFOs and AI experts said.

“AI — for all its hype — still has to prove itself,” SymphonyAI CFO Wayne Kimber said in an interview. “It’s got to go from a science project with a data science engineer to something tangible for business.”

So far the payoff from AI is far from universal. While 37% of executives in 100 countries and 20 industries said their companies derive value from AI, 30% said that their businesses do not, according to 1,741 respondents to the survey by MIT Sloan Management Review and BCG.

“Aligning the achievement of individual and organizational value from AI remains a work in progress,” the researchers said, cautioning against burdening employees with the task of serving the machine.

When gauging ROI, CFOs need to recognize that valuable uses for AI tools will unexpectedly crop up as the software analyzes mountains of data, Aible CEO Arijit Sengupta said in an interview.

“People need to flip their thinking, their traditional approach to setting up ROI goals and expectations for projects that were based on a deterministic world,” he said. “Until you have actually trained the AI on the data, you have no way of knowing how to paint a nice, beautiful picture beforehand.”

CFOs derive the biggest payoff from AI tools by focusing first on increasing revenue, which is comparatively easy to measure, Sengupta said. Next, they should aim to cut costs and limit risks.

3. Adjust to AI’s limitations

OpenAI is candid about the weaknesses of ChatGPT-4, the newest version of its software.

“Despite its capabilities, GPT-4 has similar limitations as earlier GPT models,” OpenAI said in a report last month. “Most importantly, it still is not fully reliable (it ‘hallucinates’ facts and makes reasoning errors),” OpenAI said. It suggested “avoiding high-stakes uses” that lack additional context or review by human supervisors.

The creators of AI tools will gradually eliminate hallucination as they work with their clients on focussed applications, Sengupta said, adding that Aible offers software that aims to spotlight errors by double-checking answers from the AI tools.

“The hallucination problem — use-case by use-case — will get solved,” he said. “But it has to be solved before enterprises can use it.”

4. Start small

CFOs should avoid delay in sizing up AI tools given the opportunity to gain a competitive edge — and the risk of losing market share, the CFOs and AI experts said.

“Organizations need to move quickly to have a clear vision and a transformation, program-led approach,” according to Mukund Kalmanker, global head of AI solutions at Wipro.

At the same time, CFOs can maximize returns and avert waste by initially focusing on proven AI tools on a limited scale, according to Kimber. They should “line up a company with sector knowledge,” he said, “not some stealth skunkworks.”

“We’re not saying to customers, ‘Buy our platform and look for the needle in a haystack,” Kimber said. “We’re saying, ‘Hey, retail customer or fintech customer, we’ve already identified use cases that work.’”

CFOs who take an uninformed approach may push the technology into the same “hype cycle” that has disrupted the adoption of innovations for decades, the financial executives and AI experts said.

“The hype cycle in technology is well known,” even within just the AI subsector, Sengupta said, noting the C-suite mood swings over expert systems and automated machine learning.

“People get excited, then they over-invest, then they lose a lot of money, then they get unhappy, then they under-invest,” he said. “Now we’re seeing it with generative AI.”