CDO Magazine’s San Francisco Executive Boardroom Dinner on April 1 convened senior data, analytics, and AI leaders from the Bay Area to exchange insights on successful enterprise AI. The evening featured a panel discussion on the theme “How to Drive GenAI Impact with AI-Ready Data.” 

Conversations delved into aligning data strategy with AI goals, embedding AI insights into business decision-making, addressing bias in AI models, and enhancing data management practices to fuel GenAI initiatives. Attendees shared real-world challenges, actionable strategies, and lessons learned — resulting in a candid, forward-thinking dialogue on how to unlock tangible business value with generative AI.

The panel of experts were:

• Deepa Harnalli, Forge SVP, Global Head of Data, AI/ML & Analytics Platforms, standing Chief Data Officer

• Shadaab Kanwal, former Charles Schwab Managing Director, Digital, Data & Analytics

• Jean-Paul Saliou, Synopsys Senior Director, Business Intelligence & Analytics

The session was moderated by Kevin Fleet, Informatica VP, Technical Sales Strategy & Operations.

Slideshow – Click to enlarge

“If you can’t explain your data and track its lineage, it’s not enterprise-ready — it’s not AI ready… especially not in a regulated space,” says speaker Harnalli. She shares the following takeaways:

1. Data readiness for models — Laying the groundwork for success: One point that really resonated with me – 80% of an ML project’s time is still spent prepping data and it shows how vital readiness is. We discussed how model-ready data goes far beyond just availability. It needs to be accurate, fresh, complete, and consistent — or we’re feeding our models noise.

   Some leaders shared how they’ve implemented data observability tools like Monte Carlo or Databand to stay ahead of schema drifts or silent data failures. I loved the emphasis on automated lineage, quality scoring, and cataloging — these aren’t just “nice to haves” anymore, they’re core to trustworthy AI. One best practice that stood out was data contracts between producers and consumers to reduce last-mile surprises in downstream ML pipelines.

2. Data governance — Easier to sell when the stakes are clear: A few years ago, selling data governance was like pushing a boulder uphill. But today, with AI front and center, the narrative has shifted: garbage in, garbage out is no longer theoretical — it’s a business risk.

   We shared real-world examples of AI gone wrong due to ungoverned data — think biased lending models or healthcare misdiagnoses. That’s when governance clicks for stakeholders. I appreciated the callout of tools like Informatica Axon, Alation, Unity Catalog, and Acryl — which not only trace data but enforce policy, provide clarity, and protect model integrity.

   Governance isn’t just about compliance anymore — it’s about protecting brand trust and customer outcomes in an AI-driven world.

3. Building auditable, compliant AI in regulated environments: Working in highly regulated sectors like finance, I know how hard it is to make AI both powerful and governable. This discussion really drilled into that challenge.

   It’s not enough to train a great model — you need an environment that’s traceable, auditable, and risk-aware. That includes everything from access control and versioning to drift monitoring and model explainability. Tools like Arthur AI, Fiddler, and WhyLabs came up as leaders in AI observability, while frameworks like NIST’s AI RMF and ISO 23894 provide guidance for AI compliance.

4. LLM/AI and data governance – Mutual enhancements with Informatica: LLMs and AI enhance data governance by automating data discovery, classification, quality checks, and policy interpretation, while robust governance ensures trustworthy, compliant data for AI training and operations. Informatica’s key features — such as CLAIRE AI, Enterprise Data Catalog, Axon Data Governance, and Data Quality — enable intelligent metadata management, lineage tracing, and automated policy enforcement. Together, they drive greater data transparency, efficiency, and accountability across both human and AI-driven processes.

Addressing the challenge of bias in AI systems, speaker Kanwal says, “To proactively identify and mitigate bias in AI models, focus on data management, diverse development teams, bias testing, and algorithmic fairness techniques while continuously monitoring and updating models.”

On the topic of aligning data efforts with business outcomes, panelist Saliou highlights the strategic mindset required to succeed. “Aligning data strategy with AI isn’t about technology; it’s a business-driven approach about creating the organizational muscle to transform raw information into actionable insights and business outcomes. The true potential of AI isn’t replacing human judgment but augmenting it.”

Prasad Suravarapu, BMO VP of Enterprise Data Management, underscores the evolving role of data governance as a value driver in the age of AI. “The organizations that succeed won’t just govern data — they’ll leverage it as a catalyst in their AI journey for innovation, growth, and trust.”

Slideshow – Click to enlarge

Reflecting on the event, Bill Gannon, CDO Magazine EVP & General Manager, says: “We are incredibly fortunate to partner with Informatica in facilitating this insightful discussion on real-world data and AI use cases — exploring both challenges and opportunities. Our panelists shared deep expertise, offering practical perspectives that resonated with the audience. The engaging conversation, enriched by a diverse cross-section of industry leaders, also sparked thoughtful questions and dialogue among attendees.”

Slideshow – Click to enlarge

Moderator Fleet sums up the discussion, saying, “Data leaders are very concerned about heightened expectations from their business stakeholders regarding the impact of AI applications. Without addressing the underlying data challenges present in their organizations, it will be impossible to achieve the intended business value.”

Special thanks to Informatica for their partnership in making the event a success.

*Deepa Harnalli is a member of the CDO Magazine Global Editorial Board.

Executives attending the San Francisco CDO Magazine Executive Boardroom Dinner included: 

Ozlem Bishop, Renaissance Park Chief Data Officer; Melania Calinescu, AI4ALL Solutions Founder & CEO; Frankie Cancino, Mercedes Benz Sr. Data Scientist; Sharath Gokula, Sam’s Club Head, Product Operations Data Science; Deepa Harnalli, Forge SVP, Global Head, Data, AI & ML, & Analytics Platforms, standing Chief Data Officer; Subramanian Iyer, QXO SVP, AI; Ercan Kamber, former Angi Chief Data Officer; Shadaab Kanwal, former Charles Schwab Managing Director, Digital, Data & Analytics; Francesca La O, Early Warning Chief Data Officer; Gary Patel, Albertsons Companies Sr. Director, BI & Analytics; Alyssa Simpson Rochwerger, Blue Shield of California Sr. Director, Product Development & Platform Technologies; Jean-Paul Saliou, Synopsys Sr. Director, Business Intelligence & Analytics; Bala Sahejpal, DocuSign Chief Data Officer; John Shields, ETR Director, Data Strategies & Insights; Prasad Suravarapu, BMO VP, Enterprise Data Management; Jan Tai, Rula Director, Revenue Analytics; Keith Brosh, Informatica Director, West Commercial Sales; Kevin Fleet, Informatica VP, Technical Sales Strategy & Operations; Scott Koles, Informatica Regional Sales Director; Jim Kurtowicz, Informatica VP, North America Sales; Steve Bangsund, CDO Magazine Sr. Director, Programs; Bill Gannon, CDO Magazine EVP, General Manager.