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.”
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.
While the opportunity for AI in finance is nearly unlimited, it can also be overwhelming.
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.
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.
Not only does embracing AI allow finance teams to acclimate to the technology faster than the competition, but the AI itself will mature and become better as it ingests more data.
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.”
In this special episode of the Workday Podcast, guest host Megan Wright, head of innovation at FT Longitude, is joined by three global emerging technology thought leaders as we dive headlong into the topic of AI and machine learning in the workplace.
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