6 Steps to Build an AI-Ready Finance Team

Deepen your talent bench as part of building out your AI initiatives

By now, every CFO has heard that AI promises to shake up the work finance professionals do every day by automating many tasks and providing new insights. Embracing AI will of course require finance teams to choose from myriad offerings to find the tools that best suit their needs. Just as important for CFOs, however, is how AI will change the talent required to build out a world-class finance team. CFOs have an opportunity to use their efforts to embrace AI in finance to also strengthen their talent bench. Let’s start by recognizing it’s tough to hire and retain finance talent. Finding the right talent has ranked as one of CFOs’ top concerns for years, and the numbers show why: 300,000 US accountants left the field from 2019 to 2021, according to Bureau of Labor Statistics data,1 and the number of people who took the CPA exam in 2022 marked a 16-year low, the AICPA reported. The dearth of fresh talent also leaves CFOs with fewer people ready to climb up to senior roles—28% of large companies don’t have a formal CFO succession plan in place, Deloitte recently found. Rather than duke it out for a shrinking pool of candidates using well-worn tactics, finance leaders need to reevaluate their talent strategy while realizing that AI could change the skills your team needs

1. Create an intentional plan to experiment with AI
2. Seek out ideas and advice from departments outside finance
3. Identify must-have AI skills and double down on professional development
4. Ditch unfulfilling work with AI-fueled automation
5. Recognize—and reward—those who lead charge in AI adoption
6. Rethink your ideal candidate profile as AI changes the work

to be successful. Based on input from executives implementing AI in their businesses, the six actions described here can help a finance leader not just fill vacancies in an ultracompetitive environment, but also attract the all-stars who will thrive in this new era of finance and leave your organization in good hands for years to come.

1. Create an Intentional Plan to Experiment with AI

First, CFOs and their peers need to develop an initial understanding of how AI could change the work people do in different finance roles. This is where experimentation can be extremely valuable and, given the potentially groundbreaking impact of AI, it’s worthy of healthy R&D investment. Businesses tripled their credit-based purchases with AI vendors in the first eight months of 2024, per Ramp, a sign that many are already trying out the technology.⁴ There are numerous approaches that could work here, but the key is to start with a real problem or a process with clear room for improvement. Then you might pull together a small group of standout team members with a particular interest in technology, ask them to compile a list of AI capabilities that have the potential to help with a few pressing issues, and decide as a team what to try first. You could ask those team members to spend 10% of their time for a few months experimenting with different AI tools and reporting back on what made a real difference and what wasn’t all that useful. Perhaps there is low-hanging fruit in the form of one or two AI applications with a relatively low cost and clear ROI for your business and it makes sense to dive right in. For example, the team could test AI-powered invoice scanning, track the staff time needed for training, and measure any improvement in accuracy and staff time savings. Or, they might test generative AI tools that can summarize reports and charts into narrative reports, or that can draft product descriptions, purchase orders, and emails to customers, and document how well the models performed for different use cases. Be sure to explore AI capabilities that may be available through your existing tech vendors. These could come as enhancements to a system you already use for no additional cost or could be add-on applications that cost more. Ask your account manager or support rep to better understand available capabilities and how they could satisfy specific use cases for your business. Packer Fastener, a distributor of fasteners and industrial supplies, started experimenting with AI capabilities available in its existing NetSuite applications. The team started by using AI features embedded in its NetSuite Analytics Warehouse data warehousing tool to highlight patterns and outliers and run predictive models designed for specific use cases. Now, it’s experimenting with other applications.

“The deeper stuff we’re doing is on the machine learning prediction models. Once we started tapping into that, we have several ideas on where to go. We really just needed to get started, and once we got started, the possibilities became endless.” Bill Feck, CTO, Packer Fastener

Heed Feck’s advice: Just get started. Experimentation of the sort Packer Fastener is doing has the dual benefit of solving a problem and getting your employees more familiar with AI. Any of these approaches will help them understand where and how current iterations of AI can help the finance function and what tools aren’t quite there yet but warrant close monitoring because they could be a difference-maker. These projects will also give your team a stronger sense of how AI could change roles and responsibilities now and in the future. It also directly increases employees’ knowledge of how to understand and use AI tools to empower them to do more, better.

2. Seek Out Ideas and Advice from Departments Outside Finance

Often the best ideas come not from consultants but from inside your own walls. With the rapid emergence of AI and a still-evolving understanding of the best business applications, there is plenty to learn from those around you. CFOs should engage with other department heads and leaders to learn about their AI wins and the impact it’s had on their business and workforce. For example, HR might be using GenAI to produce first drafts of job descriptions. While the subject matter may be much different for finance, there could still be much for them to learn about how to structure prompts that generate the best results and, more broadly, the limitations or weaknesses of GenAI for other tasks. The operations team may have created an impressive model to predict customer demand that could inform financial models or even be adapted to finance use cases relatively easily. Change management is another big area to learn from peers in other departments. Where did they start bringing AI in, what fears did that stir, and how quickly did they expand its use? Did bringing AI into that function’s processes meaningfully change the jobs of just a few workers or affect most employees across their division in some way? What strategies did these leaders find effective in getting their teams to buy in? If a certain initiative intrigues you, dig in. Ask a lot of questions and connect with that leader regularly to hear about additional progress and learnings. In these early days, your company may even want to set up an AI innovation committee that pulls in senior leaders across the business—the CFO, VP of finance, or equivalent most definitely included—to share ideas and the results of their experiments that others can learn from.

3. Identify Must-Have AI Skills and Double Down on Professional Development

Business leaders are convinced that AI will reshape the competencies your workforce needs—75% expect AI to impact their talent strategies, a Deloitte report on GenAI finds.⁵ So how can businesses adjust? Upskilling and reskilling that includes technology training and development of soft skills are key parts of the plan. Early learnings from these trials can help CFOs tailor the plans to various roles and individuals based on skill gaps and what would make a real impact now or in the near future. An accounts payable clerk, for example, may need to be trained on how to gather data from new bill scanning and payment automation software and how they can then put together financial forecasts and scenario plans using that payment data. A controller or a more junior employee on the managerial track might participate in an upskilling program focused on communication, collaboration, and leadership.

“The deeper stuff we’re doing is on the machine learning prediction models. Once we started tapping into that, we have several ideas on where to go. We really just needed to get started, and once we got started, the possibilities became endless.” Bill Feck, CTO, Packer Fastener

And then there’s AI-specific training. In the Deloitte survey, organizations that rated “very high” in GenAI expertise were more likely to have AI fluency programs. This kind of general education on how the rapidly evolving technology works, its capabilities, and known issues is valuable on its own. It can help turn fear of AI eliminating jobs into curiosity and spark ideas about where it could be applied to help more employees. One of the most underestimated benefits of upskilling and reskilling initiatives is that they can improve staff retention. In a University of Phoenix study, 68% of employees said they would stay in jobs with ample opportunity for upskilling.⁶ At minimum, you should start some kind of AI training and explore what AI capabilities your software providers are embedding in your finance systems.

4. Ditch Unfulfilling Work with AI-Fueled Automation

Back-office automation is a trend that started long before the recent emphasis on AI—consider robotic process automation (RPA) and optical character recognition (OCR). For many finance roles and tasks, therefore, AI will feel like the continuation of a trend. However, AI does mark a major leap forward because it is a more intelligent form of automation. It can get increasingly better at identifying anomalies and predicting future sales, for instance, as it ingests more data over time. GenAI expands on that with the ability to provide detailed, contextual explanations and suggested actions based on the data. CFOs will see this additional automation as a way to meaningfully cut costs and increase productivity, which it is. But there is another benefit that is perhaps just as valuable: automating mundane tasks related to bookkeeping, account reconciliations, payroll, and AP and AR processing can make your workplace more appealing and help you hold onto current employees who feel more fulfilled. The most promising finance talent doesn’t want to spend their days reviewing invoices and matching transactions from bank statements. It’s telling that 60% of accountants in a recent FloQast survey said technology was more important to their job satisfaction today than it was two to three years ago.⁷

“My accounts payable manager came to me and said, ‘It’s a huge, error-prone headache of going into our bank account and making all these payments. NetSuite can do payments right out of the bank.’ … I was so impressed with her that I promoted her to accounts payable director.” Jessica Wijesekera, Senior Vice President of Global Accounting, Vytalize Health

Jessica Wijesekera is the senior vice president of global accounting at Vytalize Health, a healthcare company that was recently named the fast-growing US private business by Inc. magazine. Wijesekera described how one of her senior accountants essentially automated himself out of an accounting role focused on reconciling 47 different bank accounts—to his benefit. “He was able to go over to our FP&A side, and now he works in budgeting and analytics,” said Wijesekera, speaking onstage during a keynote at SuiteWorld 2024, NetSuite’s annual customer event. “It’s not that he wasn’t a value-add doing bank reconciliation, but now he really helps us control our costs. And I think he’s a lot more fulfilled in his job now that he works in FP&A instead.” Employees may need training and coaching to shift to more strategic work such as FP&A. But strengthening the team’s critical thinking and analysis skills will only become more valuable in the years to come.

5. Recognize—and Reward—Those Who Lead Charge in AI Adoption

As CFOs gain a sense of how AI will impact their team’s work in the long term, they can better determine which individuals bring outsized value. Who has the skills that remain valuable or are perhaps more important than ever with this technology embedded across finance operations? Who has found innovative ways to apply AI in ways to increase productivity and provide better insights? You want these people filling out your talent bench, and losing them would be very costly. In many ways, this work is Leadership Development 101: seek regular feedback from managers and colleagues to know who’s standing out, where they excel, and what gaps you have along your talent bench. However, everything about AI has been moving faster than typical technology breakthroughs, so AI’s impact on your talent needs is also likely to happen quickly. For one thing, people who prove they can apply AI to finance operations will be sought-after talent. Given their ability to turn the promise of AI into real business results, you may want to give these top performers the chance to work in various roles across accounting and finance. This will broaden their skillsets, show how quickly they become comfortable with new domains and team dynamics, and help you assess their fit for financial leadership roles. For example, Wijesekera noted how one Vytalize Health team member took the initiative to propose a more efficient and accurate way of handling bank payments. “My accounts payable manager came to me and said, ‘It’s a huge, error-prone headache of going into our bank account and making all these payments. NetSuite can do payments right out of the bank,'” she said. “Now, we make our payments right out of NetSuite and reconcile our bank daily. I was so impressed with her that I promoted her to accounts payable director.” Act quickly, as Wijesekera did, when it comes to rewarding and promoting these exemplary staffers with skills that will prove valuable long into the future. Consider that roughly three-quarters of accounting and finance professionals planning to leave their employer in the next 12 months said they don’t expect to advance in the organization, according to a joint report from the Institute of Management Accountants (IMA) and Robert Half. Younger professionals are more likely to leave, with 39% of surveyed professionals ages 18 to 38 having voluntarily left their job in the past two years, significantly higher than any other age group.⁸

6. Rethink Your Ideal Candidate Profile as AI Changes the Work

“The introduction of AI into the workforce calls for tighter partnerships between the technology team, the line of business that might be hiring, and HR. We’re all in this together to make sure we not only capture the value today, but we really set it up for sustained success.” May Lam, Director of AI Program Management, Oracle NetSuite

Despite widespread recognition that today’s finance professionals are strategic contributors, many companies have not fully adjusted what they look for in a candidate to reflect this shift—especially with AI poised to assume more of the routine work. As you look for talent that can make an immediate impact on your team and thrive in the AI future, it’s critical to prioritize strategic thinking skills and technology savvy in addition to finance and accounting bona fides. Only 23% of CFOs see understanding of financial principles and accounting practices as one of the most critical skills for finance staffers in the future, according to a McKinsey survey. They cited change management, extracting insights from advanced analytics, and making decisions alongside business partners as the skills that will be most important to finance functions in the future in that same survey.⁹ But there’s a glaring gap in today’s finance talent bench: CFOs say change management is the most critical skill they’ll need in the future, yet that ranked lowest among the skills they believe their finance staff currently possesses. So as much as your finance team will need comfort with data analysis and an understanding of where and how AI can be applied, the future may place even more of a premium on skills based in communication and problem-solving. AI may be able to gather and categorize the data and generative AI could summarize key trends, but it’s up to CFOs and their teams to determine where to invest and where to pull back based on that information. CFOs should be quick to ask for help in navigating these changing hiring needs. “The introduction of AI into the workforce calls for tighter partnerships between the technology team, the line of business that might be hiring, and HR,” said May Lam, director of AI program management at Oracle NetSuite. “We’re all in this together to make sure we not only capture the value today, but we really set it up for sustained success.” Keeping an open mind as you evaluate the candidate pool will help you find candidates with these soon-to-be essential skills. Some candidates with strong data science or analytics experience, for example, may not have a business degree, CPA license, or experience in financial planning. But they could still have high upside in a finance role and the ability to pick up the required financial acumen on the job while increasing diversity of thought. Ask targeted questions in interviews to get a sense of their curiosity, willingness to learn, and ability to quickly pick up new concepts. In the face of shifting expectations among finance employees and candidates and technological breakthroughs that will change the skills these professionals need, CFOs should take a long look at their talent strategy. Executives should thoroughly assess the expected effects of AI on their industry, business model, and specific processes as part of their efforts to determine how they can better retain and attract the skilled professionals needed to build out their talent bench. Based on what they learn, they can invest in the right strategies and technology to support those efforts. Right now, the key is to start building a clear plan for the future.

Tools to Support a New Talent Strategy

As CFOs look to build a workforce for an AI-powered future, they’ll need to give that powerhouse team the right technology to succeed. Best-in-class finance systems can handle much of the rote work your staff dreads. NetSuite ERP, for example, can automate many tasks related to accounting, such as invoicing, bill payment, and financial reporting. Add-on NetSuite modules can automate invoice payments and use data from your ERP to create budgets, forecasts, and financial models. NetSuite SuitePeople tracks employee-specific KPIs, goals, and achievements to help you identify and reward top performers. Within these core capabilities, NetSuite is embedding AI throughout the suite, acting as an assistant. These features help your finance team spend more time on strategic work while still delivering the timely and accurate filings, reports, and dashboards that are indispensable to the business. NetSuite Text Enhance uses GenAI to draft narratives summarizing financial reports, personalize collection letters, and add details to journal entries. Prediction algorithms in NetSuite Planning and Budgeting use AI to assess large amounts of data to highlight anomalies and correlations in your plans and forecasts that might otherwise go unnoticed. NetSuite Analytics Warehouse leverages AI to validate and centralize data from various systems and generate predictive models and visualizations.