The AI Data Fabric Show

What does a 175-year-old farm equipment company have to teach us about the agentic era? More than most expect. Mano Mannoochahr, former CDAIO at Verizon and Travelers and a top 100 AI leader, spent 17 years at John Deere watching petabytes of farm data reshape everything from yield predictions to fuel tank sizing. His argument is simple and grounded: data transformation is not about technology, it is about the decisions it makes possible for the first time.

In this episode, Prat Moghe talks with Mano about three hard-won lessons from three decades of data leadership. At John Deere, precision agriculture data turned counterintuitive insights into real business models. At Travelers, becoming the first formal CDO meant training 20,000 people and using aerial imagery to close the gap between recorded data and ground truth. And on the agentic shift, Mano points to the agricultural revolution as the most instructive parallel: in the early 1900s over 50% of the US workforce was in agriculture, today that number is 1.5%, and the overall impact on jobs and productivity was positive. His case for why AI follows the same arc is one of the most grounded takes you will hear from a leader at this level.

Topics discussed:

• GPS-precision agriculture and petabyte-scale farm data

• Counterintuitive field insights and new farmer business models

• Optimizing fuel tanks and product engineering from fleet data

• The "show me, advise me, do it for me" customer trust framework

• Building a 20,000-person data culture at Travelers

• Aerial imagery and AI closing the ground-truth gap in insurance

• Agriculture as a historical lens for workforce displacement and AI

• Work AI can do that humans could never do at scale

• How the CDAIO role has evolved from governance to transformation

Kjersten Margaret Moody's 4% sales uplift in Southeast Asia came from a data combination most CDOs overlook: cell phone movement patterns merged with internal distribution data. The insight was brutally simple yet invisible until the data revealed it. Convenience stores next to elementary schools were being restocked for night shift workers instead of parents picking up kindergarteners.

Kjersten Moody, now CEO of North America at Elai and former CDO at Unilever, State Farm, and Prudential, walks through the mechanics of this win and why it represents a broader problem: most business strategies don't actually require AI to succeed, which means your data initiatives lack the forcing function of incentive alignment. Her governance framework from State Farm cuts through the bureaucracy paralysis: cars have brakes so they can go fast, not slow down.

Topics discussed:

• Merging cell phone movement data with internal distribution systems to identify restocking mismatches by location type

• Structuring data office charters with explicit "what we don't do" boundaries to prevent scope creep and mission drift

• Aligning AI initiatives to business strategy through incentive structures rather than relying on voluntary adoption

• Building cross-functional teams that balance institutional knowledge with external thinking while screening for collaboration over brilliance

• Establishing shared KPIs with CFOs and P&L owners instead of data office vanity metrics

• Implementing governance frameworks that define clear operational boundaries to enable faster deployment cycles

• Replacing passive-aggressive meeting culture where verbal agreement doesn't translate into resource commitment or execution

• Accelerating business domain expertise by attending customer industry conferences instead of data and analytics technical events

At Generac, Neil Bhandar expans his 20+ year career into IT. Previously at P&G, JPMorgan, and other companies, he operated within business functions. He's a business executive who works in data, not the other way around. This explains how he sees the same sawtooth pattern in inventory replenishment and credit card balances, and launched Tide Coldwater to 4% market share gains in under four weeks.

At P&G during the second Bush administration, oil jumped from $45 to $105 per barrel. His team positioned an enzyme-activated detergent as consumer cost savings, combined it with down-counting to convert Tide from a retail loss leader into a profitable product, then targeted only retailers with high category close rates and golden households. Four weeks later: 4% market share gain for a $7 billion brand.

At JPMorgan, he used organizational network analysis to find which business units weren't communicating. When he tested whether "happy employees make happy customers," he found no data that validated it. His book The Cost of Curiosity addresses analytics' broken economics where each follow-up question costs as much as the first. His biggest AI concern isn't hallucination but the sea of sameness when competitors use identical foundation models.

Topics discussed:

Ajay Sabhlok made architecture the gatekeeper for every IT decision at Rubrik, not a review function that validates choices after they're made. This structural shift meant architects evaluated tools, processes, and vendor capabilities before budget conversations happened. The outcome: scaling from 700 employees to IPO without the shadow IT proliferation or rationalization projects that typically emerge when business units control procurement.

The execution reveals how it works. At VMware, he performance tested Salesforce Service Cloud despite enterprise customers not doing that, found telecom provider bottlenecks, and co-developed DR capabilities with their product team. At Rubrik, every enterprise tool passes through a quarterly board with the CFO, CRO, and co-founder before purchase approval. When sales requested territory management software, the CRO delayed it three years until manual processes actually broke at scale.

His "comprehensive thinking" framework maps failure scenarios during discovery, not after implementation. It's why Rubrik declared cloud-only infrastructure early and centralized all software budget authority under IT.

Topics discussed:

How do you convince executives to fund 14-month foundational builds when CDOs typically have quarters to prove value? After orchestrating multiple enterprise transformations at Fidelity—including bringing all enterprise data into a single cataloged, modeled platform—Mihir Shah reveals the tactical playbook that enabled 30 years of technology migrations without losing architectural coherence.

Shah's approach stems from hard-won lessons at Churchill Insurance in the late 80s, where his team built real-time underwriting systems that processed "billions and billions of rows" while customers waited on calls. That foundational discipline—investing 14 months in architecture before launching—became his template for navigating technology shifts from mainframes to cloud-native AI platforms.

His counterintuitive strategy: aggregate all planned data initiatives across business units to reveal the true cost of fragmented execution, then redirect that same budget toward unified foundations. The result? Technology-portable architectures that survive decades of vendor transitions while delivering immediate business value.

Topics discussed:

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Ever wondered why graph databases promise so much but often fail to reach production? In this episode of The Data Fabric Show, Kaycee talks with Weimo Liu, CEO of PuppyGraph, about creating the "Trino of graph databases." 

Drawing from his experience at a previous graph startup and Google's F1 team, Weimo describes how PuppyGraph enables organizations to visualize complex relationships like money laundering patterns or supply chain dependencies without moving data from existing platforms like Snowflake, Oracle, or Databricks. 

By treating data logically as a graph while physically remaining as tables, PuppyGraph has broken through the adoption barrier that has plagued graph database implementations for years.

Topics discussed:

Check out Puppygraph on LinkedIn, YouTube and on X!

Joyce L. Myers, CDO of MTSI, considers herself more of a "builder" digital officer who's architecting additions to an already successful foundation.

In this episode of The Data Fabric Show, Joyce tells Kaycee her approach to building upon the strong foundation of an employee-owned defense contractor with a 31-year history. She explains how MTSI recognized the need for better data organization as they continued to grow, comparing their situation to an entrepreneur with too many files in cabinets who can't find what they need.

Joyce discusses the unique challenges of implementing data governance and AI solutions within the constraints of the public sector and defense industry, where security and protection of proprietary, sensitive, and classified information are paramount concerns. This security context creates additional complexity when adopting GenAI tools, requiring careful consideration before implementing solutions that might expose sensitive data.

Topics discussed:

In this episode of The Data Fabric Show, Kaycee speaks with Bruce Desmarais, PhD, Professor & Director of the Center for Social Data Analytics, Penn State University. Together, they dive into the role of advanced data science tools in analyzing social media data to address issues like misinformation and online bullying. 

Bruce shares insights on the collaboration between academia and tech companies. The conversation also explores the transformative potential of generative AI in social research, including the creation of synthetic social systems for experimentation. 

Topics discussed:

In this episode of The Data Fabric Show, Kaycee speaks with Robin Sutara, Field Chief Data Strategy Officer at Databricks, who shares her unique journey from repairing Apache helicopters in the U.S. Army to leading data strategies in the tech industry. 

Robin dives into the importance of fostering a data-driven culture within organizations and the critical role of change management in digital transformation. Additionally, Robin discusses how generative AI can enhance data strategies, emphasizing the need for robust data foundations to ensure trust and accuracy in AI outputs. 

Topics discussed:

In this episode of The Data Fabric Show, Kaycee speaks with Matt Clark, Data Leader of National Grid Electrical Transmission, who shares his expertise on the evolving landscape of data leadership. He discusses the various roles of CDOs, including the caretaker, arsonist, phoenix, and scapegoat, highlighting the unique challenges and opportunities each role presents. 

Matthew emphasizes the importance of empowering business users to take ownership of data and analytics, fostering a culture of collaboration and innovation. He also explores how emerging technologies like data fabric and GenAI can enhance data accessibility and quality, paving the way for more effective decision-making in organizations.

Topics discussed:

• The evolving role of chief data officers, including caretaker, phoenix, arsonist, and scapegoat, and how these roles impact organizational effectiveness and culture.