In this podcast episode produced by CFO Dive, presented in partnership with Workday and Kainos, financial services leaders discuss what AI readiness truly means for today's CFO. Adam Scheidler, Vice President of Financial Services and Insurance at Kainos, Kyle Davidson, Director of AI Technology at Kainos, and Jim Gahagan, Senior Director of Financial Services Solutions Marketing at Workday, share real-world perspectives on how organizations can move from isolated AI experiments to scalable, enterprise-wide impact.

The conversation centers on the foundational pillars of AI readiness, including clean and connected data, clear governance frameworks, and employee empowerment. The guests provide practical guidance to help CFOs balance innovation and risk while driving faster decisions and measurable business value.

Key Topic: From Experimentation to Scale

The three experts agree that many financial institutions have launched multiple AI pilots, but the real challenge lies in scaling successful initiatives across the organization. Adam Scheidler notes: "AI readiness is not a single technology deployment, but a systematic upgrade of organizational capabilities, data foundations, and governance mechanisms." Kyle Davidson adds that technology teams need to work closely with business units to ensure AI solutions align with actual financial processes.

Data: The First Pillar of AI Readiness

Jim Gahagan emphasizes that data quality and connectivity are prerequisites for AI to be effective. "If data is scattered across multiple systems and lacks unified standards, any AI model will struggle to produce reliable results." He advises CFOs to prioritize investment in data governance and integration architecture to lay a solid foundation for AI applications.

Governance and Risk Balance

On the balance between innovation and risk, the guests believe that a clear governance framework is indispensable. Kyle Davidson mentions that financial institutions need to establish clear AI usage policies, including model monitoring, compliance reviews, and ethical boundaries, to build stakeholder confidence. Adam Scheidler cautions that governance should not be overly rigid but should support rapid iteration and experimentation.

Employee Empowerment and Change Management

AI readiness also depends on the human factor. Jim Gahagan states: "Finance teams need to understand how AI assists decision-making, rather than replacing professional judgment." He recommends enhancing employees' data literacy and AI application skills through training and cross-functional collaboration, thereby driving cultural transformation.

Practical Advice: A CFO's Action Checklist

  • Assess existing data assets, identify key gaps, and develop an integration roadmap.
  • Establish a cross-departmental AI governance committee with clear responsibilities and approval processes.
  • Start with high-value, low-risk scenarios as pilots, then gradually expand to core financial processes.
  • Invest in employee upskilling and incorporate AI literacy into finance team development plans.

Finally, the guests emphasize that AI readiness is not a one-time project but a continuous evolution. CFOs should regularly review technology, process, and talent strategies to ensure the organization remains at the forefront of change.

Listen to the full podcast!