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Boards and executive teams are asking finance leaders a direct question: What is our AI strategy and what results are we seeing?
Artificial intelligence is already present across finance organizations. The challenge is no longer whether to adopt AI, but how to govern, prioritize, and operationalize it in a way that improves forecast confidence, accelerates the close, and strengthens decision support.
Many finance teams are experimenting with automation, predictive analytics, generative tools, and emerging AI agents. Without a structured operating framework, these efforts often remain isolated pilots that fail to produce measurable impact or meet audit expectations.
This session presents a practical, technology-agnostic roadmap for evaluating and governing AI across accounting and FP&A workflows. Rather than focusing on vendors or tools, the discussion centers on finance processes, measurable outcomes, executive alignment, and control structures leadership can trust.
Attendees will explore how to:
• Identify high-value, low-risk AI use cases aligned to financial impact
• Improve forecasting accuracy through predictive and scenario-based intelligence
• Accelerate reporting and close cycles with anomaly detection and workflow optimization
• Establish governance, auditability, and oversight structures for AI-enabled processes
• Sequence adoption from experimentation to operational integration
Real-world workflow examples will include variance commentary preparation, reporting package assembly, workforce cost visibility, reconciliations, and anomaly identification.
Participants will leave with a structured framework to determine where AI belongs within their finance organization and how to implement it in a way that delivers measurable ROI while meeting board and audit expectations.