innovation

New York Life’s Tali Rosenblum and Marina Printz shared strategies for measuring AI investments against business and financial outcomes, and deploying generative AI safely at scale.

Artificial intelligence is advancing quickly. For companies looking to put that technology to work at enterprise scale, however, speed is only part of the equation.

At the recent Ai4 Conference in Las Vegas, two vice presidents from New York Life’s AI & Data team, Tali Rosenblum and Marina Printz, shared complementary perspectives on demonstrating meaningful business impact of AI implementations and how to scale AI responsibly at the enterprise level. Rosenblum joined a panel examining how companies can connect AI investments to measurable business and financial outcomes, while Printz focused on the safeguards and oversight needed as generative AI moves from experimentation into broader use.

Together, their sessions reflected a core principle behind New York Life’s approach to AI: success is not measured by how many tools are deployed, but by whether AI creates meaningful value while preserving trust, accountability and discipline.

Measuring what matters

Rosenblum’s panel, “Measuring What Matters: KPIs and Metrics for AI’s Financial Impact,” focused on determining whether an AI investment is producing the outcomes of impact it was intended to create.

The discussion centered on choosing the right KPIs for the right use cases, connecting operational improvements to financial performance and distinguishing meaningful indicators from metrics that demonstrate activity without demonstrating value.

For New York Life, that distinction is important. AI is a core enterprise enabler, not a standalone technology initiative. Depending on the use case, meaningful measures can include improvements in client experience, support for agents and advisors, employee productivity and other outcomes tied to enterprise priorities.

The principle is simple: adoption alone is not the objective; impact is.

Scaling AI with trust and discipline

In her session, “Deploying GenAI Safely at Scale,” Printz approached AI from a complementary angle, focusing on the operating disciplines, safeguards and ongoing monitoring required to move generative AI from experimentation to responsible enterprise scale.

Her message was that responsible scale requires more than a successful pilot. Organizations need to test thoroughly before deployment, continue monitoring after launch and have clear processes in place to respond when something is not performing as expected.

Printz also emphasized that AI quality cannot be reduced to a single measure. Effective oversight requires looking at whether systems are using the right information, producing relevant and well-supported responses, and meeting the needs of the people using them. Human judgment remains an important part of that process, particularly in higher-stakes applications.

The broader takeaway: moving quickly and operating responsibly are not competing goals. With the right foundations and accountability in place, organizations can build confidence in AI and scale it more effectively.

Moving with urgency — and discipline

The two Ai4 discussions highlighted complementary dimensions of scaling AI across the enterprise: the focus on measurable business value and the disciplines required to deploy AI responsibly. Together, they reinforced a common principle: realizing AI’s potential requires more than access to powerful technology. It requires clear business outcomes, strong technology and data foundations, thoughtful oversight, ongoing measurement and human accountability. It also requires continuous learning as the technology evolves.

That approach aligns with New York Life’s broader ambition to become a more technology-, data- and AI-powered company while maintaining the reliability, security and stewardship that define the company. AI adoption is also paired with workforce enablement and AI fluency, with the goal of helping employees, agents and advisors work more effectively and spend more time on relationship-driven work.

For New York Life, scaling AI is ultimately about combining modern agility with enduring trust — using technology to improve how we operate and serve people while keeping business value, responsible use and human judgment at the center.