When Craig Kurtzweil joined UnitedHealthcare two decades ago, getting insights from healthcare data involved manually digging through PDFs and building charts in Excel. Fast forward to today, as Chief Data and Analytics Officer, Kurtzweil leads a team that works at an entirely different scale. They’re not just generating reports — they’re turning one of the largest healthcare datasets in the country into real-time, personalized intelligence for employers, clinicians, and customers.

In this conversation, Kurtzweil reflects on the evolution of healthcare analytics and the new challenges that come with it. One of the biggest? What he calls “analysis paralysis,” the tendency to drown in data instead of acting on it.

He discusses the shift from reactive analysis to proactive insight, how his team is using GenAI to cut through complexity, and why the real challenge isn’t just about having better tools. From streamlining call center experiences with AI to helping members find the right care at the right cost, he shares a vision of healthcare that’s more responsive, more efficient, and ultimately more human.

Edited Excerpts 

Q: Can you share your journey to becoming Chief Data and Analytics Officer at UnitedHealthcare? What are the key responsibilities of your role, and how do your team contribute to the company’s mission?

My team and I work to transform vast amounts of data into meaningful insights for our employer clients. This spans everything from large-scale reporting — hundreds of thousands of reports delivered to employers nationwide — to highly customized analytics. We analyze trends such as the impact of smoking on populations, the effectiveness of wellness programs, and the best healthcare providers from a quality standpoint.

Beyond employer-level analytics, we also examine overarching business trends, identifying key drivers and opportunities across the organization. Data policy is another critical area I focus on.

Our mission is simple: Take massive amounts of data, make it insightful, and deliver actionable intelligence to our clients.

Q: With access to the nation’s largest healthcare dataset, how are you using it to uncover insights that improve care, support better decisions, and lower costs?

Over my 20 years at UnitedHealthcare, I’ve seen a dramatic evolution in how we harness data to drive better healthcare decisions. Today, we have access to vast and diverse datasets — medical, pharmacy, advocacy (call center), provider, and digital data — flowing in from multiple sources.

The challenge is not just collecting this data but integrating, organizing, and transforming it into meaningful insights that people can understand and act upon. And we don’t do this once — we do it thousands of times across different stakeholders.

Analytics wasn’t the industry buzzword it is today when I started. I was manually entering data from PDF reports into Excel just to create basic charts. We’ve come a long way in developing interactive capabilities that allow us to provide real-time insights to employers.

For instance, in the past, if an employer asked detailed questions such as whether an issue was driven by employees or spouses, or if it was specific to a location like Dallas or Minneapolis, I would have to take that as a follow-up. This meant going back to my desk, writing code, generating visualizations, and then emailing a response. By the time they received it, they often forgot why they asked the question in the first place. Now, we can deliver these insights instantly.

Broadly speaking, the key challenge is improving efficiency in uncovering meaningful analytical insights so we can quickly identify actionable opportunities. In healthcare, “analysis paralysis” is a real challenge. Accessing and organizing data can be so overwhelming that it slows progress. Our focus is on streamlining this process — getting the right data in hand efficiently — so we can spend more time figuring out what to do with it.

Some of this involves traditional analytics and visualization tools that make insights more accessible. But now, AI is helping us take it even further. For example, if we need to analyze an organization’s healthcare trends by market, age, gender, or other factors, AI allows us to identify key drivers and target sub-populations much faster.

Instead of having my team run these analyses manually thousands of times per year, we can now automate and simplify the process, allowing us to focus more on action and impact rather than just data exploration.

Q: When you say newer analytics capabilities, does it involve GenAI?

Yes, AI encompasses a wide range of capabilities, and I wouldn’t even limit it to just one category. It really depends on how you define it. I’d also include spatial visualization as a key component — finding new ways to access data faster, extract insights more efficiently, and present them in a way that non-data professionals can easily understand.

These are all emerging tools and technologies we’re actively exploring, testing, and integrating into the marketplace to enhance decision-making and user experience.

Q: Can you tell us about the GenAI use cases UnitedHealthcare is exploring? 

In healthcare, it’s crucial to implement these technologies responsibly, ensuring they address disparities rather than exacerbate them. To achieve this, we’ve established AI and ML governance councils to guide ethical and effective use.

Our focus has been on identifying the right opportunities where these tools can create meaningful impact, starting with improving the consumer experience.

For instance, our customer experience experts (aka Advocates) have greatly benefited from AI. Previously, when members called the number on their card, they would be routed to a general advocate who would then determine their needs. Now, using AI-powered analytics, calls are automatically directed to the right specialist based on the member’s history and likely concerns. This eliminates the need for repetitive questions and reduces frustration.

Additionally, AI enhances the advocate’s role by enabling real-time call documentation. Instead of manually typing notes during the conversation, AI records and transcribes the discussion, allowing the advocate to focus on meaningful human interaction. A final review ensures accuracy while streamlining administrative tasks.

Beyond phone interactions, AI is improving digital healthcare navigation. Finding the right doctor or treatment can be challenging, especially for patients unfamiliar with medical terminology. By leveraging natural language processing, users can simply describe their symptoms in plain language, and AI will match them with high-quality, cost-effective providers.

On a broader scale, we also use these technologies to analyze industry and market trends, providing macro-level insights. However, the real power of AI emerges when applied at a personal level — helping individuals navigate their healthcare journey more effectively through predictive modeling.

Today, there’s growing discussion around agent-based AI, which introduces even greater automation potential. These AI-driven agents have the ability to streamline processes, enhance decision-making, and further optimize healthcare delivery, opening new possibilities for efficiency and patient care.

Q: What are your thoughts on AI agents or Agentic AI? How do you think AI agents could impact the insurance sector?

There are many different areas within the company where AI and automation can be leveraged, both internally and externally. For example, when a member is searching for healthcare information, AI-powered chatbots can provide natural, intuitive interactions to help guide them to the right resources.

Internally, my team deals with thousands of ICD-10 and CPT codes — something that took me over a decade to fully understand. Now, AI can quickly help new team members get up to speed, significantly reducing the learning curve.

The real power of these technologies lies in their ability to take years of accumulated knowledge and make it instantly accessible, enabling the next generation of healthcare professionals to operate at a higher level from day one.

Q: Can an AI agent sell insurance directly to consumers someday? Could we expect that kind of intelligence and automation?

I can’t predict exactly where all of this will ultimately lead, but one thing is clear — whether it’s brokers and consultants selling insurance or consumers trying to navigate their coverage, AI and automation will make the entire process much easier.

If you look back 20 years, the way we interacted with insurance and healthcare was completely different. Fast forward another 20 years, and the difference will be just as dramatic. 

Q: Have you found any GenAI use cases that could deliver significant ROI for business? How are you measuring it?

There are multiple ways to think about this. On the one hand, there’s the clear financial Return on Investment (ROI), with measurable cost savings and efficiency gains. Beyond that, AI also accelerates innovation, setting businesses up for long-term success — even if the immediate impact isn’t always visible in the short term.

The low-hanging fruit with AI is all about driving efficiency. It automates repetitive, mundane tasks that aren’t enjoyable and allows employees to focus on more strategic, value-added work. This shift delivers an immediate return, as teams can redirect their efforts toward higher-impact projects that benefit both the business and customers.

The more complex aspect of AI investment lies in the long-term vision. Some AI initiatives are about laying the groundwork for transformation that may not fully materialize for another five to ten years. It requires leadership with the foresight to invest in these technologies today, knowing they will drive significant advancements in the future. Ultimately, AI’s value is a balance between short-term operational gains and long-term innovation-driven ROI.

Q: What are the key challenges in driving a data-centric culture and preparing the organization for AI within a large healthcare organization? 

There are many ways to approach that question. From a technical standpoint, AI is only as effective as the quality of data it processes. Ensuring a well-structured, integrated, and clean data architecture is critical — without that foundation, AI will simply amplify any inconsistencies, following the classic “garbage in, garbage out” principle.

Beyond the technical aspects, the implementation of AI represents a significant shift for organizations. Within my team, across account management, and even with clients, this technology fundamentally changes how we derive insights and tell data-driven stories.

Adapting to this new way of working requires breaking long-standing habits — people have grown accustomed to traditional methods of accessing and interpreting data. AI is disrupting those routines, introducing a faster, more dynamic approach.

The real challenge lies in cultural adoption — how quickly teams embrace these changes and integrate them into daily workflows. In my space, it will be fascinating to see how rapidly this transformation becomes part of the norm.

Q: How is UnitedHealthcare using data to personalize care and health plans for individuals? Can you tell us more about the “Find Care & Costs” tool?

Understanding the cost of care can be challenging. While there are transparency sites that display different pricings but the real question is: How do you present that information in a way that’s easy for consumers to understand? Quality of care is even more complex — how can someone know they’re choosing the right doctor for the right procedure at the right time?

We’re leveraging AI to make that entire experience more seamless and intuitive. Behind the scenes, we analyze data to identify not just the lowest-cost providers but, more importantly, the highest-quality providers. Instead of listing options alphabetically or by proximity, our digital capabilities automatically rank providers based on quality metrics, ensuring that the best options appear at the top of the list.

This smarter navigation system leads to higher engagement with top-tier providers, resulting in better patient experiences, improved healthcare outcomes, greater compliance, and ultimately, lower total costs of care. It’s a simple but powerful way to improve healthcare decision-making, backed by sophisticated data and AI-driven insights.

Q: What emerging data trends in insurance and healthcare excite you the most?

That could easily be an hour-long conversation on its own! The healthcare industry right now is going through a generational shift. As baby boomers retire and millennials become the dominant demographic in the commercial space, we’re seeing a fundamental change in expectations. Younger generations want digital-first, on-demand, and virtual care options — something we’re actively exploring.

On the health side, we’re also seeing rising rates of chronic diseases like obesity, which continue to escalate across populations. At the same time, medical advancements — such as breakthrough cancer therapies — are improving patient outcomes but come with significant costs. The challenge is balancing affordability with access to high-quality care.

Another major trend is the growing focus on behavioral health. Stigmas around mental health are fading, especially among younger generations, leading to increased demand for services. This is a positive shift, but it also raises questions about how to scale care and ensure quality outcomes.

These are just a few of the key themes that dominate conversations in healthcare today, and they’re shaping the way we think about the future of the industry.