Artificial intelligence and automation are reshaping the corporate finance and accounting (F&A) function. Yet the central challenge facing many organizations is not the technology itself. The greater concern involves people. Finance leaders must develop teams that can work effectively with new digital tools while the profession continues to experience a shortage of CPA and accounting talent.
These themes formed the basis of a recent Controllers Council webinar titled Upskilling Accounting and Finance Teams for AI and Automation, sponsored by insightsoftware. The discussion examined how finance organizations are adopting automation, how accounting professionals are learning to work with new tools, and how leadership roles will evolve as AI capabilities expand.
Panelists included Philip Peck, VP Finance Transformation at Peloton Consulting Group; Gregg D’Eon, VP Controller at LTK; and Kevin Gibson, former Controller, CPA and Senior Solutions Engineer at insightsoftware. Their conversation offered practical observations from consulting, corporate finance leadership, and enterprise software development.
AI Adoption Is Moving from Exploration to Structured Planning
Many organizations initially approached artificial intelligence with curiosity rather than a defined strategy. Finance leaders are now moving beyond experimentation and beginning to introduce more deliberate adoption plans.
Peck described how this shift is unfolding across the organizations he advises. Companies are no longer simply considering the possibility of automation. Instead, they are actively integrating AI into operational planning.
As Peck explained, organizations are now “working through all the important business considerations and then stepping back and crafting more intentional roadmap-oriented playbooks for both deploying and then optimally leveraging automation and AI capabilities.”
This transition reflects a broader maturation in the market. Automation and AI are increasingly viewed as practical tools that support everyday finance operations rather than as distant or experimental technologies.
Early Use Cases Focus on Practical Operational Improvements
Although artificial intelligence offers a wide range of possibilities across the F&A function, many organizations begin with relatively focused use cases that deliver immediate operational benefits.
At LTK, for example, D’Eon described how AI tools are helping employees retrieve information quickly across multiple communication channels and data repositories. These tools allow staff members to ask direct questions about operational details without searching manually through several systems.
He explained that even simple applications can produce meaningful improvements in productivity. In his experience, “high volume AP and AR applications with basic automation and AI can achieve incredible uptick in our productivity across the department.”
In many F&A departments, early automation projects concentrate on activities such as accounts payable processing, invoice tracking, reconciliation workflows, and reporting tasks. These areas often involve repetitive processes that are well suited for automation.
Peck also noted growing interest in more advanced use cases, including automated journal classification, anomaly detection in financial balances, predictive forecasting, and automated narrative reporting for financial statements. These capabilities allow accounting teams to focus less on assembling data and more on understanding what the information means for the business.
Data Governance Remains Essential
Despite the growing enthusiasm for artificial intelligence, panelists repeatedly emphasized that successful adoption depends on reliable financial data.
Gibson highlighted this point clearly during the discussion. According to him, organizations must first ensure that their data sources are accurate and accessible before attempting to rely on AI-driven analysis.
He summarized the issue directly: “The data is the biggest part of this, right? You have to trust the data.”
In practice, many companies maintain financial information across several systems, including enterprise resource planning platforms, customer management software, internal spreadsheets, and communication platforms. When these data sources remain fragmented, AI tools may produce incomplete or misleading results.
As a result, finance teams are increasingly working alongside IT departments to centralize data, standardize definitions, and maintain appropriate security controls.
AI Training Often Begins with Self-Directed Learning
The webinar also explored how F&A teams are learning to use artificial intelligence tools. In many organizations, formal training programs are still developing, which means that employees often begin with self-directed experimentation.
D’Eon described a simple but effective starting point that many finance professionals overlook. By asking software vendors about their product roadmaps, organizations often discover automation capabilities that already exist within their current systems.
As he noted, “If you just ask your software rep whether or not they have or plan to have any sort of AI implementation with their software, you’d be surprised with what you can get out of that.”
This approach reflects a broader trend within the finance profession. Many teams are combining vendor training, internal collaboration, and professional education programs to build familiarity with emerging technologies.
Knowledge sharing within organizations has become particularly important because AI tools continue to evolve rapidly. Finance teams that experiment, exchange insights, and refine their approaches often gain practical experience more quickly than those waiting for formal training frameworks to appear.
The Role of Finance Professionals Is Changing
While automation is expected to handle an increasing share of routine accounting tasks, the panelists agreed that the role of finance professionals will become more strategic rather than less important.
D’Eon illustrated this shift by recalling a lesson from a former CFO who regularly challenged his team to move beyond basic reporting.
After reviewing a presentation, the executive would often respond with a simple but revealing question: “So I see the what… tell me what to do with the information?”
That question reflects the growing expectation placed on finance professionals. Producing financial information remains important, but leadership teams increasingly rely on accountants to interpret results and recommend actions.
Peck offered a similar perspective, emphasizing that analysis should ultimately lead to operational decisions. In his experience, F&A leaders should not stop at identifying trends. They should also guide organizations toward clear next steps and measurable outcomes.
As artificial intelligence accelerates the process of gathering and analyzing data, the human responsibility for judgment, communication, and decision support becomes even more significant.
AI Is Expected to Augment F&A Roles
Another topic raised during the discussion involved the potential effect of automation on entry level accounting positions. The panelists largely agreed that AI will change the nature of certain tasks but is unlikely to eliminate the need for F&A professionals.
D’Eon described this clearly when discussing the oversight required for automated systems. Even when organizations deploy advanced tools, someone must remain responsible for monitoring processes and validating results.
In his words, “You still need someone to sit on top of that process.”
Rather than reducing employment opportunities, automation may shift early career responsibilities toward analytical thinking and operational oversight. Tasks such as manual data entry may decline, while roles involving data interpretation and business insight may expand.
For younger professionals entering the field, this transition may increase the appeal of accounting and finance careers by highlighting their influence on business decision making.
Advice for Finance Leaders Beginning Their AI Journey
As the webinar concluded, panelists were asked to offer practical guidance for organizations beginning to explore automation.
D’Eon provided a concise recommendation that resonated with many participants: “Start small.” Small automation projects allow teams to demonstrate value quickly and build confidence within the organization. Early successes often create momentum for larger initiatives.
Peck added that organizations should combine these early wins with a thoughtful long-term plan. Artificial intelligence capabilities continue to evolve quickly, and F&A teams benefit from maintaining flexibility as new tools and opportunities emerge.
To explore these perspectives in greater detail and hear the full conversation, watch the complete webinar here.
ABOUT THE SPONSOR:
insightsoftware is a global provider of comprehensive solutions for the office of the CFO and the controllership. We believe an actionable business strategy begins and ends with accessible financial data, with solutions across financial planning and analysis, FP&A, accounting, and operations. We transform how teams operate empowering leaders to make timely and informed decisions. Learn more at www.insightsoftware.com.
