As artificial intelligence rapidly reshapes the finance landscape, accounting leaders face a pivotal moment.
The path forward is clear: Accounting functions must become AI-ready, moving beyond incremental automation to a future state where technology and talent work seamlessly together. For accounting, where the primary product is accurate, timely and relevant financial information, the AI shift has especially significant implications.
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1. Extend AI-ready accounting into automated, continuous processes
The foundation of an AI-ready accounting function is the shift from periodic, manual processes to continuous, machine-driven operations. In this model, activities such as reconciliation, adjustment and financial reporting are largely automated, enabling a continuous, on-demand or even autonomous close. This not only accelerates the pace of reporting, but also improves accuracy and transparency. Accountants oversee and extend automation, focusing their expertise on exception handling, insight generation and decision support, the areas where human judgment remains essential. The more routine activity becomes embedded in systems, the more capacity accounting teams create for judgment-based work.
2. Recognize digital talent and upskilling as essential
By 2030, Gartner predicts 90% of finance talent will need digital skills, with accountants expected to build, manage and optimize technology tools. This is a dramatic shift from today, where less than 30% of finance teams are considered digital talent. Upskilling is critical, not just in using advanced tools, but in understanding how AI and automation can transform workflows. Organizations must invest in targeted training, hands-on experimentation and peer learning networks to close the digital talent gap and empower their teams for the future. In practice, this means developing not only advanced technology users, but also people who can build, modify and manage finance data and technology capabilities.
3. Embrace new accounting roles and team structure
The composition of accounting teams is changing. As automation handles routine tasks, organizations will need fewer entry-level accountants and managers, but more skilled individual contributors who are adept at technology work. In many functions, the traditional talent pyramid is likely to become a smaller "talent diamond" over time, as the majority of transactional work is reduced, and roles shift toward oversight, analytics and technology work. New roles are emerging, such as model builders who create and refine AI algorithms, and AI investigators who monitor and optimize system performance. These technology-first roles are essential for developing, maintaining and improving AI systems, and they will become increasingly central to the accounting function.
4. Evolve controllers into finance information orchestrators
The role of the controller is evolving into a finance information orchestrator. Controllers must model technology adoption, partner closely with IT and owners of upstream data sources, and focus on data flow and system integration. Their expertise in financial data remains crucial, but the emphasis shifts to ensuring data integrity, championing technology acceptance and designing roles where accountants leverage AI-generated outputs to create insights and support business decisions. In practice, that means leading collaborative data management, driving integration across systems, helping the team adopt technology more confidently and defining roles that support stronger business partnering work. Controllers must also facilitate collaboration across finance, IT and business units to drive successful AI adoption.
5. Accelerate AI adoption through hands-on experimentation and tailored upskilling
Traditional training alone is not enough to prepare teams for AI. Leading organizations accelerate AI adoption by facilitating hands-on experimentation, collaborative problem-solving and peer coaching. For example, structuring learning sessions around real work challenges and mixing employees of varying AI maturity levels helps build confidence and practical skills. Rather than treating AI training as generic instruction, effective leaders ground learning in the actual friction points employees face in their daily work and give teams room to test solutions together. Tailored learning plans and ongoing feedback loops ensure that upskilling efforts are relevant and effective, supporting both career growth and organizational transformation.
Moving forward
Building an AI-ready accounting function is not a one-time initiative. It's an ongoing journey that requires deliberate action, investment and leadership. By embedding automation into core processes, prioritizing digital talent, embracing new roles, evolving leadership and fostering a culture of experimentation, accounting teams can position themselves at the forefront of finance transformation. The organizations that act now will be best equipped to deliver timely, accurate and strategic insights in the AI era, while creating roles where accountants focus less on manual processing and more on interpretation, oversight and better decision support.
