As AI adoption accelerates across the enterprise, women data leaders are uniquely positioned to drive transformative change. While the 2026 CDO Insight Survey reports that 69% of companies have adopted generative AI, data reliability remains a top barrier to success.

In this insightful webinar, a panel of leaders from the annual Global Data Power Women list shares their strategies for building trust, upskilling workforces, and evolving governance frameworks to meet the demands of the AI era.

Featured Speakers

• Diane Schmidt, Chief Data Officer at DTCC
• Kendell Timmers, SVP of Data & Insights at CNN
• Jennifer Zellinger (JZ), Head of Data Strategy, Transformation, and Governance at Centene Corporation

Moderator: Amy Horowitz, AVP for American Solutions Sales at Informatica from Salesforce

Key takeaways

1. Building trusted AI on stable foundations

The panel emphasizes that data quality is not just a technical prerequisite but a core principle that must be intentionally designed and governed.

• Embedded trust: Trust should be built into the entire lifecycle — including model training and deployment — rather than validated after the fact.
• Metadata as the linchpin: For AI to succeed, it must understand the semantic layer of an organization; proper metadata and lineage are more critical than ever.

2. From “literacy” to enablement

Rather than focusing on the “gaps” implied by the term literacy, the leaders suggest focusing on enablement and education.

• Psychological safety: Teams need the “permission to ask questions” and a supportive environment—sometimes referred to as “data therapy”—to unpack concerns and blocks.
• Certification: Leading organizations are now treating AI and data education as a core, non-optional capability for all employees.

3. The evolution of AI governance

Governance is shifting from a defensive “tax” to a strategic enabler of speed and scale.

• Constant evolution: Because AI tools change every few months, guidelines must be flexible and revisited constantly rather than being rigid product whitelists.
• Risk-based approaches: Not every innovation carries the same systemic risk; organizations can move faster by applying deeper scrutiny only where client or regulatory exposure is high.

4. Advice for the next generation

When asked what they would tell their 18-year-old selves, the panelists shared the following:

• Be adaptable: The ability to pivot and stay resilient in the face of change is the most important skill for future interviews.
• Problem mindset over tool mindset: Tools will inevitably change; focusing on how to solve business problems and tell stories with data provides lasting value.
• Growth before confidence: Don’t wait to check every box before applying for a role; jump in, and the confidence will follow.

“Data without drama”

A recurring theme throughout the discussion was the need for collaborative, “no-drama” data environments where CDOs and AI leaders work together to architect enterprise-wide confidence.