AI in Finance: Governance, Risk, and the Rise of Agentic AI

Executive Summary
This executive panel examines how finance leaders are deploying artificial intelligence while maintaining strict governance, compliance, and operational reliability.

Panelists discuss the growing importance of deterministic AI models in financial environments, the emergence of agent-based workflows, and the need for strong controls as AI moves from experimentation to enterprise-scale deployment.

The discussion highlights real-world implementations of AI across finance operations, including reporting automation, productivity gains, and risk management modernization.

As AI adoption accelerates, finance functions are emerging as one of the most critical proving grounds for responsible, scalable enterprise AI.

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Featured Panelists

Marie Myers
Executive Vice President and CFO
Hewlett Packard Enterprise

Andrew Moore
Chief Financial Officer
Prime Communications

Admiral Douglas Fears (Ret.)
Chief Operating Officer
Artis International
Former Homeland Security Advisor

Kerry Back - Moderator
J. Howard Creekmore Professor of Finance and Professor of Economics
Rice University

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Key Discussion Topics

• AI governance and regulatory compliance in finance
• Deterministic vs probabilistic AI models
• Agentic AI workflows in enterprise finance
• Managing AI risk, controls, and audit requirements
• Workforce transformation in AI-enabled finance teams
• Data integrity and trust in financial decision-making

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Key Takeaways from This Session

• Finance teams are adopting AI deliberately, prioritizing reliability, traceability, and accuracy.
• Deterministic outputs are essential in environments where auditability and compliance are mandatory.
• Agent-based AI workflows are emerging as powerful tools but require strong governance and monitoring.
• Organizations investing in workforce training and reskilling are accelerating successful AI adoption

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Frequently Asked Questions About AI in Finance

How is AI used in finance operations?

AI is used to automate reporting workflows, analyze large datasets, identify operational trends, and improve forecasting accuracy across financial processes.

What is deterministic AI in finance?

Deterministic AI produces consistent outputs from identical inputs, making it essential for financial reporting, auditing, and compliance processes.

What is agentic AI?

Agentic AI refers to systems that take actions based on predefined workflows, enabling automated decision support and process execution.

How does AI impact financial risk management?

AI enhances risk management by identifying anomalies, improving forecasting accuracy, and enabling faster detection of financial irregularities. Organizations can shift from reactive risk response to predictive risk management using AI-driven analytics.

Why is governance critical for AI in finance?

Governance ensures that AI systems operate within regulatory boundaries, maintain data integrity, and provide traceable decision outputs. In financial environments, governance frameworks are essential to maintain trust, audit readiness, and regulatory compliance.

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