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CDAO Rajesh Arora Reveals Principal Financial’s Four-Pillar Strategy for AI Success

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Written by: CDO Magazine Bureau

Updated 12:29 AM UTC, Wed November 5, 2025

Principal Financial Group, a Fortune 500 global financial services leader with over $700 billion in assets under management, has long been recognized for its commitment to helping customers plan, protect, and invest for a secure financial future. As the organization deepens its focus on digital transformation, it’s betting on data and AI to power that future responsibly and at scale.

At the helm of this transformation is Rajesh Arora, Vice President and Chief Data & Analytics Officer, who oversees the company’s enterprise data strategy, AI Center of Excellence, and innovation initiatives. In this first part of an interview with Dominic Sartorio, Vice President of Product Marketing at Denodo, Arora discusses how Principal Financial is laying a strong foundation for AI success — one built on education, governance, and value realization.

Building the foundation for data-driven value

Arora’s mission is clear: to integrate data, analytics, and AI across Principal’s businesses and enable smarter, more informed decision-making.

This foundation is being built around four strategic pillars:

  1. Modernizing data and analytics platforms to maximize returns on AI investments.
  2. Strengthening AI infrastructure through best-fit tools and partnerships.
  3. Establishing a scalable operating model to support global AI execution.
  4. Embedding AI strategy into culture and operations as an enterprise-wide capability.

Arora notes that this approach is already yielding measurable results: “We have seen value coming through front-end productivity and efficiency gains, improved customer outcomes, and stronger operational resilience. AI is not a one-off effort for us — it’s a capability that’s now embedded into how we operate.”

Empowering the workforce for AI

For Principal Financial, success with AI starts with its people. Arora stresses that AI adoption is a company-wide movement that requires broad literacy and engagement. “The first and foremost challenge is educating our workforce around AI so we can get the best out of it,” he says. “This evolution is different from cloud or mobility — you don’t just need AI builders, you need AI practitioners.”

To address this, Principal Financial has launched an all-employee data and AI literacy program, built around three distinct learning tracks:

  • Foundational training for all employees to build awareness of core concepts in data and AI.
  • Executive education to equip leaders to champion AI initiatives and support teams in adoption.
  • Role-based learning tracks tailored to specific functions — from prompt engineering to analytics.

“We want to empower all our employees, not just technical experts,” Arora adds. “This is about a mindset shift as much as a skills shift.”

Measuring value through AI adoption

Another priority for Arora’s team is bridging the gap between AI innovation and tangible business value. He acknowledges that Principal Financial must balance experimentation with execution.

“We see gaps between the value that’s being created and the value that’s actually realized,” he notes. “To tackle that, we’re introducing a value realization framework that stays active throughout the AI use-case lifecycle.”

The framework focuses on quantification and adoption, ensuring each initiative is measured for impact and aligned with strategic goals. “This is a muscle we’re building as an organization,” he says. “It will take time, but we’re very intentional about it.”

Strengthening the data backbone

Underpinning all these efforts is a focus on data quality, consistency, and governance — critical to fuel reliable AI outcomes.

“Data is a challenge across all these pieces,” Arora acknowledges. “At times, it’s not complete or doesn’t stitch together well enough to give a single view. That’s why building the data foundation remains a core focus.”

As Principal Financial moves from AI experimentation to enterprise transformation, the team is also evaluating which platforms and tools to standardize to simplify operations and scale successfully.

“We’re working diligently to determine what AI tools and platforms are relevant for us as we move forward,” Arora says. “It’s a work in progress, but we’re heading in the right direction.”

CDO Magazine appreciates Rajesh Arora for sharing his insights with our global community.

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