Close-Ready with AI: The Fastest Path to Close Efficiency

Most finance teams arrive at AI with the same two questions: where do we start, and how do we apply this without creating new control risks? This session answers both.

Niall McLean will show where AI delivers its most significant impact across the complete close: autonomous reconciliation, exception handling, anomaly detection, variance analysis, and broader EPM workflows. He will map each use case to the right type of AI, rule-based automation, RPA, machine learning, generative, and agentic, so finance teams leave with a clear view of which tools apply where and which workflows to prioritise first.

The session addresses what most AI conversations in finance avoid: how to reduce manual effort without weakening the approval structures, confidence scoring, accountability, and audit trails that enterprise finance depends on.

If your team is deciding where AI belongs in your close process, this session gives you the framework to move forward.

What you’ll learn:

• Which close workflows produce the fastest reduction in manual effort when AI is applied

• How different types of AI and automation map to real finance processes, from matching to exception handling

• How autonomous reconciliation shortens close cycle time without compromising controls

• How to maintain approvals, accountability, and audit trails while driving efficiency

• How AI strengthens broader finance functions, including forecasting, anomaly detection, and variance analysis