AI, Trust, and Data Governance Dominate CDO Magazine's Dallas Leadership Dinner
Senior data, analytics, and AI leaders gathered at Chamberlain's Steakhouse in Dallas on October 16 for focused conversations on one topic that matters to every executive: how to implement AI while keeping data secure, private, high-quality, and accessible.
The throughline of the evening was clear-trust fuels adoption, governance enables speed, and business value must show up fast. With agentic AI moving from pilots to production, leaders traded practical tactics for building guardrails without slowing results.
What leaders said that matters
Co-chair Zul Sidi captured the urgency: "Everyone sees the potential of Generative AI and feels the urgency to act. No one wants to be left behind, but the real challenge lies in figuring out how to make it work reliably and at scale."
Co-chair Priya Reddy called the discussions "dynamic, grounded in real experiences, and full of optimism," adding that leaders were focused on doing AI right-practical, transparent, and accountable.
- Start small, prove value: Begin with a contained agentic AI use case. Add clear guardrails. Show business impact early. As Nitin Kumar noted, don't expect deterministic results from probabilistic systems-manage expectations.
- Retail moves fast: Karthikeyan Ilangovan shared how teams are automating supplier-to-fulfillment workflows with lightweight PII protections and quick pilots that include feedback loops.
- AI that supports sustainability: A leading solar firm is using chatbots to help partners serve customers more efficiently-proof that operational efficiency and sustainability can align.
- Data culture beats tooling: Jagadeesh Tupakula emphasized literacy and change management. Culture is the multiplier.
- From Hadoop to flexible AI stacks: Teams are moving to faster, modular tooling that enables governed sharing and safe experimentation.
- Speed with responsibility: Leaders are testing with smaller vendors, launching quick pilots, and supporting small-business scenarios-while keeping safety and purpose front and center.
Bank of Oklahoma CDO Shanthi Pudota called the exchange "truly energizing," noting the shared focus on AI governance, balancing risk with innovation, and delivering more personalized customer experiences while keeping the human touch.
Best Buy's Aamer Charania added a simple rule that resonated with the room: "Start with the simplest AI technique that solves the problem, rather than starting with the most popular LLM for every use case. This avoids the risk of a 'hammer looking for nails' mindset and gets you the best ROI."
Jenna George underscored a mindset shift: governance isn't about restriction-it's about access, trust, protection, and faster decisions with the right controls.
ThoughtSpot's Jason Little summed it up: "It was inspiring to hear how innovative companies are pushing the boundaries of AI in real and meaningful ways... The future is incredibly bright for AI."
Dremio's Sydney Arthur noted a common theme across companies at different stages: get the fundamentals right-governance, taxonomy, expectation management-and keep the value case strong enough to sustain investment.
Playbook: Turn discussion into outcomes
- Pick one workflow and instrument it: Define the user, decision, data inputs, and success metric. Ship a constrained pilot in 4-6 weeks.
- Stand up guardrails early: Policy-based access, PII redaction, prompt/content filters, human-in-the-loop review, and audit logs.
- Use the simplest model that works: Baseline with retrieval and smaller models before escalating complexity or cost.
- Codify data contracts: Ownership, lineage, and quality SLAs for critical data products. Break-glass access for exceptions.
- Make culture operational: Data literacy programs tied to roles, playbooks for use-case intake, and change champions inside business units.
- Privacy by design: Minimize data, tokenize sensitive fields, and enable consent tracking-especially for customer-facing use cases. See the NIST AI RMF and GDPR for reference.
- Close the loop: Capture user feedback, compare human vs. AI outcomes, and retrain or refine prompts and policies on a set cadence.
- Tie spend to value: Track cost-to-serve, time-to-decision, win rates, or error reduction-then publish wins and learnings widely.
Who was in the room
Co-chairs included Saba Dossani (Comerica), Thrushna Matharasi (Solera), Priya Reddy (former Reprise CDO), Hemal Shah (Southwest Airlines), Zul Sidi (Bank of America), Alissa Schneider (Sinclair), Aniketh Bothra (Capital One), Anand Balasubramanian (Cortico-X), Swamy Ramajayam (Meta), Sydney Arthur (Dremio), Narendran Sreedharan (Capital One), Dalia Powers (Humana), and Shveta Garg (Truist).
Executives from leading organizations took part, including Best Buy, Walmart, Verizon, Meta, Microsoft, JPMorgan Chase, Bank of Oklahoma, Southwest Airlines, Sinclair, Capital One, Humana, Salesforce, Rent-A-Center, Marriott International, MODE Global, UNFI, DTCC, Raising Cane's, McLane, Toyota Motor Credit Corporation, QCells, and more.
Why this matters for executives
The path to scale is disciplined and boring by design: guardrails, data contracts, and measurable value. The leaders winning today are operationalizing governance, starting small, and proving outcomes fast-then expanding with confidence.
If your teams need practical upskilling paths to support this shift, explore executive-focused programs here: AI courses by job function.
Thanks to our partners
Special thanks to ThoughtSpot, Alation, and Dremio for supporting a high-signal conversation and helping make the event a success.
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