As AI becomes the defining force reshaping financial services, data leaders are tasked with building not just advanced capabilities but responsible ecosystems that can scale sustainably. For Principal Financial Group, this balance between innovation and governance is central to how the company is redefining its data and AI strategy.

In this second installment of a two-part series, Rajesh Arora, Vice President and Chief Data & Analytics Officer at Principal, joins Dominic Sartorio, Vice President of Product Marketing at Denodo, to explore how the organization is operationalizing responsible AI across every business function — from governance frameworks and partner due diligence to enterprise-wide capability building.

Part 1 of this conversation focused on how Principal is laying a strong foundation for AI success — one built on education, governance, and value realization. In this second part, Arora unpacks how the company ensures every model, use case, and partnership reflects those same principles of trust and transparency.

Building guardrails for responsible AI

For an organization operating in a tightly regulated industry, Arora explains that strong governance has long been integral to Principal’s success — and remains the cornerstone of its AI strategy.

The organization has developed an ethical and responsible AI framework that accounts for compliance, privacy, regulatory, and security risks.

“Every single AI use case we work on goes through that framework. We make sure that every single use case is recorded in a centralized system for transparency and inventory. That kickstarts our assessment process,” Arora notes.

Each model deployed within Principal’s ecosystem must meet predefined risk tolerance levels before being greenlighted. This process, he explains, also extends beyond internal models.

“We aren’t limiting ourselves to what we are building ourselves. If we are adopting a solution or model from a partner, we make sure that due diligence happens there as well. We’ll continue to make sure that we stay within the guardrails.”

From experimentation to enterprise transformation

Reflecting on Principal’s AI journey, Arora says the organization’s early successes with AI pilots revealed both the potential and the limitations of experimentation without a broader strategic approach.

“We were in the experimentation mode for the longest period of time,” he recalls. “As we started seeing early successes, we recognized that unlocking the true value of AI requires a much deeper transformation.”

This realization prompted a shift from experimentation to enterprise capability-building — ensuring AI became an embedded function across all business lines rather than a siloed initiative.

Arora also points to changing customer expectations as a critical catalyst for this transformation.

“As the industry evolved, customer expectations started to change. They want faster, more customized, and more secure financial services solutions,” he explains. “That pressure enabled us — if we don’t do it now, we’ll be behind.”

A combination of all these factors led Principal to formalize its AI strategy, focusing on employee training, responsible adoption, and value generation.

A future built on trust, readiness, and scale

As Principal continues to expand its AI capabilities, Arora underscores that trust and responsibility will remain the guiding principles of the company’s innovation journey.

By aligning governance, transparency, and transformation with business value, the organization is demonstrating what sustainable AI adoption looks like in financial services — one where innovation never comes at the cost of ethics.

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