If you blinked—or at least took an extended holiday—you might have missed it.
Not artificial intelligence (AI) itself—that’s been in development for years, with solutions like IBM Watson, Amazon's AWS AI and the likes hitting the market as early as the mid to late 2010s. But rather, its sudden explosion.
Because, as 2022 came to an end, everyone was talking about it. And just as suddenly, the prevailing message in business circles was that organizations would lose out on a competitive advantage if they weren’t at least thinking about AI.
Like with many new innovations, AI’s usage grew incrementally for years, a natural progression of the automation tools organizations already relied on. In 2021, according to IBM, 31% of companies had deployed AI across their business. In early 2022, though, that number was only marginally higher, at 35%. An escalation in usage was clearly happening, in other words—just slowly.
Then, at the end of 2022, applications like ChatGPT and Stable Diffusion suddenly made their appearance—more sophisticated and adaptable than what came before. And suddenly, AI—particularly generative AI—was everywhere. Today, more and more organizations are starting to embrace AI’s possibilities, exploring its potential, researching the best AI tools and finding new ways to use it in their business.
But despite this, finance teams have been reluctant to join the discussion.
When Vena polled finance and business professionals in 2021 for our benchmark report The State of Strategic Finance, only 7% were using AI in their FP&A practices. And still in 2023, when Vena surveyed business leaders and finance and operations professionals at Excelerate Summit in May, 74% of respondents said they hadn’t yet implemented any AI tools into their immediate team.
But as finance professionals slowly wrap their minds around the potential for AI in FP&A and finance, its possible use cases only continue to grow.
“In the realm of finance, AI stands to be a game changer,” said Harjot Ghai, Chief Operating Officer at Delbridge Solutions. “It can streamline financial processes by automating data analysis, optimizing resource allocation and improving forecasting accuracy.”
Before AI can change the game, however, businesses have to build trust for AI technology within their finance teams.
So how do they go about that? What are the benefits AI technology can bring to the field of finance and FP&A in the first place and the use cases where it has the most potential?
We spoke to some of the most tech-savvy finance and business leaders we know to find out.
Before we explore the benefits of AI in finance, let’s look at the current state of AI technology more broadly, and what recent AI breakthroughs have meant for its business applications.
That starts with ChatGPT.
When OpenAI released ChatGPT to the public in November 2022, it changed the AI game, becoming the fastest-growing consumer software application ever within months.
A conversational AI bot, ChatGPT relies on artificial intelligence, machine learning and natural language processing to generate human-like text. It’s able to search internet sources and data to find and communicate information in a natural human-like way—to answer questions, write basic code, translate languages, solve math problems and produce documents and reports, among other uses.
But while it’s gotten a lot of the buzz, ChatGPT isn’t all that’s new in the world of AI. In March 2023, Microsoft announced its own AI assistant, Copilot.
Microsoft Copilot integrates directly with the Microsoft 365 suite of apps, using natural language processing to create content, answer questions and analyze massive amounts of data. In other words, it has the potential to eliminate all of those menial tasks that keep you away from higher-value work.
“The first are the Microsoft 365 tools that we all know and use—it’s Word, Excel, PowerPoint, Outlook. So the whole suite of Microsoft productivity products. The second component is … your content. It could be text, it could be files, it could be documents, it could be Calendar—everything that is actually content that you own. And the third component is the large natural language models that come on top of it. What Microsoft Copilot does is really get those three different components to interact together.”
The release of Microsoft Copilot so soon after ChatGPT isn’t a coincidence—Microsoft, as an investor in OpenAI, embedded ChatGPT into Copilot to fuel its large language model (LLM). And they’re not alone. Many other developers are accessing ChatGPT’s API to apply its open source speech recognition and natural language processing to their own technology.
That means developers from businesses of all sizes are beginning to release new AI-integrated solutions and functionality faster and more cost-effectively, with the same sophisticated capabilities ChatGPT has.
As those new tools hit the market—and AI continues to be integrated into the existing softwares that businesses already trust—more organizations are taking the plunge to implement AI technology into their day-to-day business. In fact, a study by Deloitte found that 94% of organizations see AI as critical to their success over the next five years.
“I think [AI is] really changing the way we’re going to work,” Nicolas said in Vena’s livestream. And in today’s market, the new efficiencies it offers promise to provide a competitive advantage to the organizations that embrace it.
An advantage that finance teams could be leveraging today.
AI can help businesses work more quickly, with agility and a more comprehensive view of the data at their fingertips. And that can benefit all departments—but especially finance, which typically has large stores of data under its control.
As Dominic DiBernardo, Partner and CPM Practice Leader for Citrin Cooperman, put it: “I think the biggest change AI will bring is the ability to augment the office of finance to do more with less, just like CPM (corporate performance management) has done the last decade-plus. I certainly don’t think it replaces finance people, just makes them more valuable. They will continue to be able to help the company get deeper insights that are actionable.”
In fact, AI has shown that it can benefit finance teams—and FP&A in particular—in a number of ways:
When we polled business and finance professionals at Vena’s 2023 Excelerate Summit, 44.5% said that the most appealing benefit of AI for them was the improved productivity and efficiency it offers.
In fact, improvements in productivity are one of the biggest advantages that make AI attractive across business functions, with one 2023 study by the National Bureau of Economic Research clocking an average 14% boost in productivity when it looked at generative AI-based conversational assistants.
AI can especially improve productivity because it can take over repetitive manual tasks like data collection, data entry and data formatting. “This increased automation can improve efficiency, reduce errors and allow professionals to allocate their time to more complex and value-added activities,” said Brian Zahn, Managing Partner of Capitalize Consulting.
And by letting your finance employees focus on higher-value tasks such as analysis, strategy building and business partnering, AI can actually improve job satisfaction too. One study by SnapLogic showed 51% of employees believe AI helps them achieve a better work-life balance.
Data drives organizations today—and nowhere is that more true than in a finance department.
Finance controls much of the data that businesses draw on, but if you can’t get to it quickly and analyze it with agility, it isn’t offering as much value to your organization as it could be.
“AI's ability to harness and analyze massive volumes of data has opened new avenues for valuable insights and data-driven decision making,” Harjot from Delbridge Solutions explained.
And that can be a huge help for finance teams for multiple reasons. In our 2023 survey of Excelerate Summit attendees, when asked about the benefits they saw in AI, 18.6% of respondents saw the enhanced ability to identify risks and anomalies as particularly appealing. For 29% of respondents, a better ability to surface and analyze strategic insights stood out.
Human error is an inevitable part of doing business, especially when that business involves manual, repetitive tasks that don’t keep employees engaged.
Still, for finance teams, it can take time and resources to identify and fix these types of issues. And that’s where AI and machine learning tools can step in, to help identify typos, recognize missing data and even point out formula errors. These tools also get better over time—learning your business to become more and more accurate and recognize anomalies faster.
By taking over those tasks, AI not only saves time but reduces the chance of error as well. “AI applications help us identify the human errors, and also remove any conscious or unconscious bias,” Priya Jain, SVP of Corporate Finance and CAO at 6sense Revenue AI, said in our Vena Excelerate Summit 2023 livestream, Practical Applications of AI and Automation in FP&A.
More than that, though, AI—through its ability to analyze large amounts of data quickly—has the potential to assess potential risks and compliance issues.
“Generative AI can assist in streamlining compliance processes and risk assessments,” Brian from Capitalize Consulting said. “The technology can analyze large volumes of data to identify potential regulatory compliance issues, fraudulent activities or anomalies. This can help finance professionals identify and address risks more efficiently, ensuring adherence to regulations and enhancing overall risk management practices.”
FP&A teams are often barraged with questions from stakeholders across their organizations—whether it’s from departments like marketing or sales, investors or board members. And every question can mean someone on the team has to manually dive through the data to find just the right answer—a time-consuming task that takes up resources that aren’t often available.
With generative AI’s natural language processing capabilities, you can ask it those kinds of questions directly, cutting down the time it takes to gather the necessary data and present it in the best format possible, letting finance focus on more important work instead.
“AI can be like your assistant, in the sense that when a question comes in, AI can now inspect the data and provide a response,” Vena’s Chief Technology Officer Hugh Cumming explained during in the livestream, The New Tech Empowering Finance-Led Innovation.
Of course, there’s another byproduct of having all of that readily analyzed data at your fingertips: spotting trends and forming insights becomes easier than ever.
This allows you and your team to pivot with agility in the face of market changes and make critical data-driven decisions more quickly.
“Improved generative AI models can analyze vast amounts of data and provide valuable insights to support decision making,” Brian said. “These models can identify patterns, trends and correlations that humans may overlook, enabling finance professionals to make more informed and data-driven decisions. By leveraging generative AI, finance professionals can enhance risk management, optimize investment strategies and improve forecasting accuracy.”
Despite the benefits it offers, however, finance has been slow to embrace AI.
When we surveyed business leaders and finance and operations professionals during the Vena livestream, Practical Applications of AI and Automation in FP&A, 74% of respondents hadn’t yet implemented any AI tools into their immediate team.
But as AI has become more pervasive, FP&A teams are beginning to explore their options. 22% of the respondents of that same survey had implemented some AI tools within their team, with 3% having fully integrated AI into their function.
Compare that to our 2021 benchmark survey, at which time only 7% of respondents said they were using AI in their FP&A practices at all, and the growth in usage is clear.
“I think from the finance industry perspective, financial planning has been on this change journey,” Hugh said. “It's been pressured by this need to create more agile and nimble organizations.”
So where can finance start to take advantage of this new technology and begin introducing it to their day-to-day functions? Let’s look at a few areas where AI promises to add value:
Finance teams rely on data analysis to build better insights and create strong strategies that keep their organizations on track. AI just makes that easier.
“AI can identify patterns, trends and anomalies within financial data, allowing organizations to make data-driven decisions with greater confidence and efficiency,” said Harjot from Delbridge Solutions.
AI can analyze data to help predict cash flow and identify potential risks, for instance, making it easier for your FP&A team to map a better course for the future. More importantly, by sifting through large amounts of data more quickly than ever, AI can do all of that in real time.
“It makes such a difference when a team can focus its time on decision making, instead of trying to get the data to make the decisions,” Brandon Grant, Vena’s Vice President of CloudOps, explained in our livestream session, Practical Applications of AI and Automation in FP&A.
Scenario planning helps your FP&A team plan for future what-if scenarios, to prepare your organization for whatever happens next. And today, with uncertainty pretty much the status quo, that’s more important than ever. The more informed and comprehensive your scenario planning is, the better.
By allowing you to analyze your data more quickly and thoroughly, AI can ensure you’re building out those scenarios with as much information as possible—not only empowering you to react faster, but also ensuring you’re armed with the best response.
“AI allows you to create new and more insightful scenario-related models to deal with external forces and support strategic decisions,” Lance Mortlock, Managing Partner of Energy for EY Canada wrote. “It becomes your source of truth, processing massive amounts of data quickly and calibrating scenarios in near-real time. Humans can then shift away from feeding the data to focus on taking strategic action as AI offers continuous insight to guide them.”
By offering you a quicker way to analyze large amounts of data, AI technology is also primed to help make recommendations and predictions on how to improve your revenue streams, identifying new opportunities for growth.
Take the NFL’s Kansas City Chiefs, for example. “We've gotten into more complex artificial intelligence, looking at our fan behavior and trying to make recommendations and predictions on what kind of prices we'll be able to charge, and basically trying to make our revenue streams a little bit more predictable for the organization,” explained Michael Ragsdale, VP of Finance Strategy & Analytics for the NFL team, during Excelerate Summit 2023.
Reports like profit-and-loss statements, balance sheets and cash-flow statements still take up a bulk of most corporate finance departments’ time. And the information in those reports is always going to be necessary to your organization’s financial health.
So what if you had a little help with them? AI can do that, producing detailed reports while saving your team much of the manual effort that traditionally goes into reporting.
In fact, as the use of AI in FP&A and finance progresses, Rob Drover—Vice President of Business Solutions with Marcum Technology—predicts AI will change the way companies approach their reporting altogether.
“I believe that the traditional reporting engine of, like, Power BI, is going to go away, and get replaced by a chat interface where basically you ask the question and it just figures out how to mine the data and quickly present it to you in whatever format makes sense,” he said.
“All we’ll really have to do is feed the underlying data into a model and it'll quickly learn how to present that back to us in whatever fashion we want. So gone will be the days of building Power BI reports and standard templates. Like a profit-and-loss statement that’s been built 10 million times and they're 99% the same—why can’t an engine just give you your P&L?”
As with any technology, however, successful AI adoption starts with the right foundation. And for finance teams to successfully adopt AI technology, they need to understand and manage all the risks. “You need to look at whether the organization is ready to adopt AI applications,” Priya from 6sense said during Excelerate Summit.
And that starts with your data. “There has to be clean, usable data that you need to feed into the AI application,” she explained. “At the end of the day, garbage in, garbage out. The outcome from AI applications is clearly dependent on the quality of the data that you feed into the application, or how you train the software.”
But clean data is just the beginning. According to Harjot from Delbridge Solutions, there are still other challenges that stand in the way of successful AI adoption in finance. Many CFOs are still wary to introduce AI tech, he said, for several reasons, including:
And the truth is, many of those concerns are justified. Because AI doesn’t come without risks. There are a range of reasons some finance professionals have been slow to trust AI. Let’s look at three of the most common:
For finance professionals and others, AI is often described as a “black box,” and the inability to see behind the curtain and understand how calculations are made can be one of the biggest concerns. Especially since solutions like ChatGPT have also displayed “hallucinations,” or mistaken outputs that are factually or contextually incorrect—leading to further distrust.
In fact, Deloitte found that 50% of organizations say that managing AI-related risks like “a lack of explainability and transparency in AI decisions” is still a top obstacle to scaling their AI usage.
Cybersecurity is also a serious concern. ChatGPT, still the most popular AI tool on the market, “opens up new avenues for hackers to potentially breach advanced cybersecurity software,” the Harvard Business Review writes.
If they want to make AI a part of their day-to-day business, finance teams need to understand the security risks and find ways to mitigate them.
Finally, AI’s threat to data privacy and compliance is a risk many organizations are currently grappling with.
Natural language processing technology like ChatGPT’s is continually drawing on input data to train itself and improve its output. And for many businesses that use those solutions, that might put sensitive, confidential or proprietary data at risk—making it accessible or searchable to others that use the tool, including competitors.
One way to avoid these kinds of risks, though, is to turn to established and targeted platforms you already trust—including tools like Microsoft Copilot (part of your company's secure Office 365 environment) and those already in your tech stack that are adding AI to their offerings.
In fact, research from Dresner Advisory Services shows that finance teams are already taking this approach. In 2023, they found that 77% of companies they surveyed expect their enterprise performance management software vendor to provide AI capabilities in future releases of their software. Thirty-six percent were prepared to be early adopters.
Still, there’s an even bigger roadblock finance leaders face. Because one of the biggest challenges for finance leaders interested in introducing AI into their operations isn’t necessarily the tech itself—it’s their own teams.
“Implementing AI technologies often necessitates organizational and cultural changes,” Harjot said. “Some CFOs may be wary of the disruption and resistance that can accompany these changes. Overcoming this hurdle requires effective change management strategies, including clear communication, training and involvement of key stakeholders throughout the AI adoption process.”
So how do CFOs and other finance leaders change the culture of their finance teams to build trust for AI and all that it offers? Putting a strong set of checks and balances in place to identify mistaken outputs and identify risks is a good place to start. But there’s more that you can be doing too.
“Finance folks like to be in control. They like to understand what’s happening. And in a lot of cases, AI is viewed as this black box and people are certainly concerned,” industry analyst Howard Dresner, Chief Research Officer with Dresner Advisory Services, said in Vena’s 2023 Excelerate Summit livestream session, Latest Trends in FP&A, AI, Extended Planning and Performance Management.
When Dresner Advisory Services did their own deep dive into the use of AI in finance, they found that while finance professionals are beginning to warm to the possibilities of AI, around 15% still thought their users were likely to resist the automation offered by machine learning and AI. In fact, even as the use of AI has exploded everywhere else, that number actually grew from 2022 to 2023.
“From a finance perspective, those in the analyst role are very conservative. And because they can't see how AI came up with a number, for example, they don't trust the number,” added Stacy Brown, Vice President of FP&A Solutions with Marcum Technology.
But it’s only by building trust for AI that your team will be able to unlock the new efficiencies and productivity gains that AI tools promise—not to mention the competitive advantage.
So how do you build the change in your organization and make that happen? Here are six steps to follow, according to the experts we talked to:
Distrust is often borne out of a lack of knowledge. That means that if you jump on AI without properly educating your team, trust can be slow to follow.
No wonder, then, that Deloitte found that the organizations they surveyed “relied heavily on training as a key to mitigating AI risk.” And for 34% of them, that involved training and supporting employees to “foster productive, positive relationships to AI.”
That training and education will look different depending on your organization. “Leaders can organize workshops, seminars, or online courses to familiarize employees with AI concepts and how it can enhance their work,” Brian from Capitalize Consulting said.
But the goal is the same no matter the approach you take. It “helps employees to embrace AI as a tool that can augment their capabilities,” Brian added. By educating both your immediate team and leaders on the benefits and uses of AI, you’ll start to get them excited about the possible advantages it can bring. But it’s just as important to educate them on its risks and limitations too, so that they understand how to use it safely and effectively.
As with any new technology, getting comfortable with AI starts by getting familiar with it. Encouraging your team to experiment, then, can get them comfortable with what the technology has to offer. Often this means starting with the team members who’ve shown early interest—then letting them become champions to the rest of the team.
“Set up a safe space for them and say, ‘go play with this,’” Rob from Marcum Technology said. “It's a lot easier to do that today than it used to be because you can get free trials and free learning and all kinds of things that you used to have to pay thousands of dollars for in the past. It's a lot more of an open world these days in terms of what's available.”
When Capitalize Consulting started experimenting with AI themselves and determining how to apply it to their business strategies and those of their clients, they took a very deliberate approach—conducting market research, assessing its feasibility and doing a full risk assessment.
But that wasn’t the end of their evaluation period. Before fully embracing AI throughout their business, they developed a small-scale pilot project to “test the viability and effectiveness” of the technology, Brian said.
That’s something he suggests finance teams do as well—introducing AI gradually into your day-to-day business and building trust bit by bit.
“Initiate AI adoption through pilot projects or small-scale implementations,” Brian said. “This allows employees to witness the benefits and practical applications of AI firsthand, reducing skepticism and fear. Gradual implementation also provides opportunities for learning, adjustment and addressing concerns in a controlled environment.”
“What we always tell [our clients] is, ‘rely but verify at first, and then when you get comfortable with it you can start to accept it as is,’” Stacy from Marcum Technology said.
By encouraging your team to not only experiment with AI, but to verify any results they get, you can start to slowly build up their trust in the technology—until they eventually learn to use it like it’s second nature. The same way we use tools like, say, Google Maps.
“I always relate it back to Google Maps,” Stacy added. “When it first came out, it was telling us how to get from our origination to our destination. But maybe we didn't trust it—we printed out the directions beforehand. But eventually now we just all get in our car, we put in Google Maps that this is where we want to go, and we trust that it's going to get us there and it's going to get us there the fastest.”
AI doesn’t remove the need for human guidance or oversight. And while it may change the nature of some jobs, it also adds new responsibilities and even new positions—meaning shifts in your team (rather than outright job losses) may need to happen.
Just as people are critical, though, so are processes. It’s important to have processes in place to ensure AI is being used properly, that your business is getting the most out of the AI tools you’re using and that usage meets your corporate standards.
That may even mean hiring an outside team to ensure all of the right checks and balances are established. Deloitte found that 33% of the high-outcome organizations they surveyed did just that, hiring outside vendors to independently audit their AI systems.
Processes like these can help build trust within your finance team, showing them that there’s still proper oversight in place. Hiring specialized in-house talent as your AI efforts grow can further build that trust, demonstrating a commitment to creating a depth of knowledge within your team and to using AI properly and safely.
“Provide ongoing support and feedback to employees throughout the AI adoption process,” Brian said. “Regular check-ins, one-on-one discussions and team meetings can help address concerns, provide guidance and celebrate successes. This creates a supportive environment and reinforces a culture of continuous learning and improvement.”
It also allows you to stay transparent on your use of AI and make your team and other stakeholders part of the entire process. By asking for their opinions, you’ll ensure your AI solutions are getting the type of results you’re looking for and that you’re tackling any ongoing misgivings or challenges head on. Sometimes you may also need to tweak the inputs you’re using to get more from your tools, or new use cases may emerge.
Whatever the case, having a continual feedback loop will allow you to continue to see where you can make improvements to your AI strategy and build on the ways you benefit from AI technology—all while ensuring everyone feels like they have a voice.
AI isn’t going anywhere. In fact, the consensus according to the finance and operations professionals who attended Vena’s Excelerate Summit this year is that AI will completely transform the field of FP&A, or play a supplementary role in its future.
And for finance teams that want to give their businesses a competitive advantage, now’s the time to start embracing the advantages it offers.
AI promises to change the way organizations work, offering new efficiencies and deeper insights. And to continue building your position as strategic partners to the rest of the business, FP&A and finance teams can’t afford to get left behind.
So start taking advantage of the benefits AI offers, to free up your time and dig deeper into the data you rely on. Through deeper analysis and higher-level strategy—and with the right checks and balances in place—it can help you reach your goals faster.
Vena can help get you started. Vena Insights provides finance teams with real-time intelligent reporting and analysis using embedded Power BI and Microsoft’s best-in-class AI and machine learning technology. Get more from your Vena data with advanced machine learning models, predictive analytics and anomaly detection. As a result, you’ll get answers to complex business questions faster and drive smarter and more strategic planning.
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