In 2018, McKinsey reported that CFOs who didn’t adopt digital innovations like artificial intelligence (AI) were in danger of falling behind their counterparts in IT and marketing. When the COVID-19 pandemic hit two years later, it forced businesses to prioritize digital to stay afloat.
By one estimate from McKinsey, just the first 9 months of the pandemic pushed digital adoption ahead by approximately seven years — further widening the gap between progressive and outdated organizations. And as the economic recovery continues and business operations slowly return to normal, the digital surge shows no signs of slowing down.
Consistent with their 2018 forecast, McKinsey’s late 2020 study found that organizations that invested more in digital than their competitors were twice as likely to report outsize revenue growth. Simultaneously, CFOs who once dragged their feet are now confident in the transformational benefits of digital table stakes like automation and AI.
What does this all mean? Now is the time for CFOs at organizations of all sizes to lean on AI to plan, budget, and forecast with greater accuracy, speed, and confidence. To get you started, here are 5 ways you can use AI to transform finance and 5 ways AI can speed your move away from yesterday’s technology for a total of 10 tips you can put to work today.
If AI or AI in Finance is a new concept for you, here are some other important terms to know:
With the help of AI, finance teams can spend less time on spreadsheets and more time on strategy. As technology crunches the growing volumes of data, soft skills like critical thinking, problem-solving, and communication will become crucial for Finance to succeed.
Without AI, employees are burdened with hours of monotonous tasks like reporting and data reconciliation. The good news is that AI is designed to handle rote tasks like this with ease. A company can reduce overhead costs and gain back thousands of working hours.
But what happens to humans when the bots take over? Research from the Wharton School of the University of Pennsylvania suggests that, since AI can lead companies to become more profitable, companies can then hire more employees.
“Any employment loss in our data we found came from the non-adopting firms,” said Lynn Wu, professor of operations, information, and decisions at Wharton, and co-author of the underlying study. “These firms became less productive, relative to the adopters. They lost their competitive advantage and, as a result, they had to lay off workers.”
The automation of lower-cognitive and repetitive tasks reduces the risk of burnout and improves the employee experience. Employees can spend more time on the high-value work humans are meant to do—using their creativity to solve complex problems, strengthening relationships with colleagues and customers, and making informed decisions. As of yet, technology can’t match human intelligence, especially when it comes to so-called “insight problems” such as those which require irrational, creative, or inconsistent thinking.
The next generation of finance professionals embraces and expects AI-enabled technology to be readily available at their firms. These digital natives, who have been surrounded by digital technology throughout their lives, are “more trusting and accepting of AI,” according to a 2021 study by KPMG.
Unlike humans, AI never makes a typo, flubs a calculation, or takes time off. When a company relies on monotonous human effort and ill-designed software, errors are bound to happen. But mistakes made in finance can have disastrous consequences.
Consider how the State of Pennsylvania overpaid a school district by half a million dollars because the spreadsheet data supplied by the district inflated enrollment numbers. When the clerical error was eventually caught, the district pledged to retrain their staff and assign a supervisor to oversee future reporting. As data collection expands and an organization scales, this type of throw-more-people-at-it strategy is simply unsustainable.
AI can automatically detect issues like budget padding and human error at the granular level. These and other potential abnormalities are flagged for review by an employee. So, rather than a human being forced to comb through an entire set of data looking for errors, AI highlights only the potential errors, saving time and focusing the worker’s effort. Over time with machine learning, AI can identify patterns and send warnings to catch potential issues before they happen.
Finance departments of all sizes are drowning in data and the deadlines to report are getting tighter as well. And, as a result of the pandemic, business leaders also expect new and revised scenarios, budgets, and forecasts to be delivered weekly or even daily. Companies can choose to either hire more people or rely on technology to get the job done.
“If you don’t have the modern tools, the burdens you’ve faced in the past are only going to increase. Finance and accounting professionals will continue to work late into the night. Your employee satisfaction and retention will suffer, and your business leaders just won’t have the financial insights they need to make better decisions at the speed they now expect,” said Planful CEO Grant Halloran at the Planful Perform event for finance and accounting professionals.
With cloud-based financial data and nearly unlimited processing power, multiple and complex scenarios can be generated instantly. Armed with solid, reliable, and timely intelligence, the CFO and leadership team can look ahead, modify operations, and reconfigure the business model in response to today’s constantly fluctuating market conditions.
AI in finance represents an opportunity for employees from traditionally underrepresented backgrounds to enter or advance within the field. As AI is a new technology, employees at every career stage have the chance to up-skill and become experts.
Companies that seize this window of opportunity with AI training and internship programs will reap the rewards in two ways: they’ll increase the diversity of their workforce and leadership and be better positioned to recognize and mitigate the real issue of bias in AI algorithms.
There are a number of advocates and organizations leading the charge to avoid these pitfalls. Google and IBM, among other organizations, are publishing best practices and frameworks. Knowing how bias and a lack of diversity negatively impact your organization starts by getting the right people at the table and then putting these tactics into action.
For many CFOs, the thought of outsourcing data analysis to AI is a nonstarter. But as new technologies enable more companies to increase efficiency and profits, the pressure to adopt will soon reach a tipping point. For those in the early stages of AI adoption, here are 5 ways you can get started.
If data is the fuel that powers AI, it’s crucial to have a reliable and consistent supply of that fuel. Ray Wang, CEO of Constellation Research, considers this to be step one in AI transformation.
“You definitely want to start building those AI capabilities by getting your data house into order, by making sure that you get into the cloud, by making sure you start asking the right business questions and start looking at where AI and automation can give you an exponential advantage,” said Ray at Planful Perform.
Here are three steps to take at this phase:
Expensive pilot projects require rounds of internal buy-in and can take months to provide significant results. You’re better off running a short-term analysis and letting the data speak for itself.
For example, you can take a previous forecast report that was completed manually and compare the results with the AI-enhanced report. You’ll immediately see where the algorithm picked up on the same red flags as the previous employee-only report. It might even pick up ones you missed.
With these results, you can instill confidence in yourself and your team that the technology works and begin to build out the internal process for data collection.
Overhauling a legacy system is time-consuming, costly, and prone to failure. AI-enhanced FP&A should be built so finance teams can work with user-friendly features like visual dashboards. Choose a technology solution with intuitive features that won’t overwhelm your end-users and provides accessible reporting out of the box.
Like most of the technology that supports our daily lives, from GPS navigation to online banking, AI should work seamlessly in the background to empower workers. Those workers can then better serve your customers, partners, and stakeholders.
As mentioned earlier, the introduction of AI into the business may be perceived as a threat to jobs. CFOs can get ahead of any negative impressions by inviting the workforce into the process before the launch. So consider holding information sessions where you can educate employees on how AI will help reduce monotonous tasks and create more time for enjoyable, fulfilling, and higher-value work.
Information sessions also open a dialogue with your teams to uncover where the most cumbersome processes can be discussed and prioritized for automation. This feedback loop can provide insight on which projects AI can tackle first from the people who are closest to the existing procedures.
AI has a range of applications outside of the finance vertical and it’s likely other departments are considering adoption if they haven’t already started down the path. An oversight and ethics committee can work to establish a common set of practices, share collective learnings, and raise the visibility of AI to the board and senior leadership.
According to Adam Wenchel, founder of Capital One’s Center for Machine Learning, an oversight committee with diverse experience is crucial: “For the majority of systems that are deployed, it’s very tough to understand why a model makes a decision. We need to have explainability for AI. That’s important for any AI system where you’re affecting people’s livelihoods, like finance or health care.”
AI, data science, and machine learning will continue to infiltrate the finance sector around the globe. According to a report by The Economist, 86% of financial services executives plan to increase AI-related investments through 2025. If your competitors aren’t already deploying AI, they will soon.
“I think we’re at the beginning of a new business cycle. We really should take advantage of, if you’re starting this cycle, make sure you think about where analytics, automation, and AI play a role,” said Ray Wang, CEO of Constellation Research, at Planful Perform.
While installing AI solutions, it’s important to keep an eye on the future state. The most significant changes will begin after the business adopts AI and begins to automate its processes. The newly increased capacity opens up countless opportunities for growth, higher quality work, and more satisfied employees and customers. Business leaders should be prepared to oversee an organization that doesn’t follow the traditional finance blueprint.
Financial professionals don’t need to hold an advanced degree in computer engineering to harness the potential of AI, nor do they need to belong to enormous enterprises to afford these powerful, modern solutions.
With user-friendly software like Planful Predict at your fingertips, it’s finally possible for Finance to ramp up AI-enhanced financial planning and analysis in a matter of weeks.
Ready to get started? Schedule a demo of Planful Predict today.