Role of the Chief Financial Officer in implementing agentic AI

CFOs can play a crucial role in driving the use of agentic AI.
Agentic AI – systems capable of autonomous action based on specific goals – introduces numerous opportunities for the Finance function.
Use cases are already making an impact.

The role of the Chief Financial Officer (CFO) is shifting to a strategic leader capable of driving innovation across the organisation. In the current technology landscape, reshaped by advances in artificial intelligence (AI), the Finance function stands at a pivotal juncture. It has the potential to enable transformative value or risk being left behind. Agentic AI – systems capable of autonomous action based on specific goals – introduces numerous opportunities for the Finance function. These include autonomous end to end transaction processing, real-time risk sensing, self-service analytics, and continuous closing processes. However, alongside these promises comes the need for new governance frameworks, capabilities and operating models.

In this article, we explore how CFOs can harness AI to unlock new capacity in Finance, navigate key governance considerations, implement effective operating models, and learn from leading use cases driving transformation.

Helping Finance become the partner the business needs

Business leaders are increasingly looking to Finance not only for reports and forecasts but also for real-time insights and strategic advice that aid smarter, faster decision-making. Agentic AI plays a crucial role in meeting these expectations. By automating the groundwork – data gathering, report drafting, trend highlighting, and risk scanning – AI allows Finance teams to focus on analysing, interpreting, and advising on the actions that need to be taken to drive productivity and deliver on the growth aspiration.

A practical example of this in action is FloQast, a financial close management platform. Its Transform capability demonstrates how agentic AI can orchestrate workflows across modules – linking outcomes like month-end reconciliations (from the Close Module) with the AI-driven preparation of reconciling journal entries. These entries are passed into FloQast’s Journal Entry Management tool for review by Finance team members prior to ledger posting, streamlining the process while preserving necessary oversight.

AI enables Finance to pivot from explaining "what happened" to understanding "why it matters" and determining "what should we do next?" Leading CFOs are already implementing AI to expedite processes like closing, enhancing forecasting and developing real-time dashboards that facilitate quick business adjustments. They're embracing AI's capabilities to deliver immediate value rather than waiting for perfect systems and data or ideal use cases.

The CFO's role involves connecting the dots – aligning AI investments with broader business objectives, encouraging teams to adopt new methodologies, and fostering a culture where Finance actively shapes business performance rather than merely reporting on it. This transformation is not about replacing people with machines but empowering people with tools to assume more valuable roles. AI provides the space for Finance to evolve into the strategic partner that businesses have long sought.

Governance: Laying the groundwork for Responsible AI

Governance is a critical aspect of embedding AI in Finance, and the CFO plays a central role in ensuring AI's responsible, ethical and regulatory-compliant usage. Governance requires collaboration with the Chief Risk Officer, CIO, Data, and Internal Audit to address questions around ownership of outputs, transparency in AI-driven decisions, and confidence in data powering these tools. As AI takes on more Finance tasks, maintaining auditability becomes essential. CFOs must ensure AI delivers outcomes that are accurate, fair and accountable.

Rethinking the Finance Operating Model

Integrating AI into Finance is an opportunity to rethink its operating model, structure, processes and roles. Organisations are increasingly adopting agile, cross-functional models – like Finance "chapters" in centers of excellence focused on analytics and AI – to bring Finance closer to business decisions. Agentic AI can automate standard processes and monitor performance, identify issues, and suggest corrective actions in real-time. This shift necessitates a transformation in Finance roles, prioritising data interpretation, accuracy of outputs, business logic/prompts, and insight translation.

Leading use cases: Where agentic AI is already making an impact

The promise of agentic AI in Finance is no longer theoretical – real use cases are already proving value. Some of the most compelling applications include:

AI assisted forecasting and scenario planning
Continuous close and reconciliation
Preparation of regulatory and management reporting
Monitoring of predictive risk management

These examples are just the beginning. As AI capabilities mature, the scope for Finance to operate smarter and faster will only expand. But unlocking that potential depends on CFOs championing the shift – setting the vision, shaping the roadmap and getting teams ready for what’s next.

Final thoughts

CFOs must invest in governance, talent, technology-enabled capabilities, and a culture that embraces new ways of working – piloting, learning quickly, and scaling what works. The future of Finance is not just automated; it is agentic, analytical and advisory, with the CFO serving as the architect of this AI-enabled transformation.

With thanks to Mathea Beck for her contribution.

If you would like to find out more about how Finance can drive AI in your organisation, please contact Paddy McEvoy.

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Paddy McEvoy

Director, Advisory, PwC Australia

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Role of the Chief Financial Officer in implementing agentic AI

Helping Finance become the partner the business needs

Governance: Laying the groundwork for Responsible AI

Rethinking the Finance Operating Model

Leading use cases: Where agentic AI is already making an impact

Final thoughts

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Helping Finance become the partner the business needs

Governance: Laying the groundwork for Responsible AI

Rethinking the Finance Operating Model

Leading use cases: Where agentic AI is already making an impact

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