Cigna Group is shifting its AI strategy from chasing use cases to measuring outcomes - and the company says the approach is already producing hundreds of millions in projected savings. Katya Andresen, Cigna's chief data, digital and AI officer, said the emergence of generative AI led many executives to ask "How do I use AI?" She thinks that's the wrong question.
"We've been on a mission to change that question to, 'how do I lead in an age of AI?'" said Andresen. That framing focuses less on any single tool and more on measurement that shows an AI investment can change health outcomes.
Projected savings from targeted AI use
Cigna announced this summer that it projects the AI and predictive analytics tools it uses to help patients identify chronic conditions - including cancer, kidney disease, and high-risk pregnancy - can save an estimated $200 million over the next three years by proactively connecting patients with clinicians. Separately, Cigna announced a $100 million investment through 2028 to use AI to reduce the time clinicians spend documenting cases and speed up the prescription process.
Another use case involved using AI to understand common inbound patient questions about biosimilars, which treat chronic diseases at a fraction of the cost of biologics. Unlike generic drugs, biosimilars aren't an exact match because they're made from living organisms like bacteria and plant cells, but both are approved by the Food and Drug Administration.
One biologic, called Humira, can cost a patient $7,000 per month to treat inflammatory and autoimmune conditions. Cigna analyzed thousands of prior customer conversations about biologics and biosimilars, then used those insights to craft stronger digital messaging encouraging a switch to the cheaper alternative. More than 80% of patients opted for the biosimilar, Andresen said.
"That led to a lot of margin," she said. "But more importantly, it created a couple hundred million dollars of savings for patients."
These savings matter for Cigna, which generates $275 billion in annual revenue and ranked 14th on the latest Fortune 500 list. National healthcare spending exceeds $5 trillion annually due to chronic conditions, an aging population, and soaring costs for hospital stays and new prescription drugs.
Patients are already turning to AI chatbots
Patients frequently say they're frustrated navigating the industry's complex system, and millions report they've turned to ChatGPT and other AI chatbots for health-related questions. Nearly six-in-ten report using AI to research health information before a doctor visit, and about 14 million adults say they have skipped a visit with a provider after using AI, according to a Gallup survey published in April.
That movement raises questions about guardrails around AI chatbots, even those created by insurance and pharmaceutical companies, because they handle sensitive patient information and must accurately answer complex questions about medical plans and treatments.
"The good news is, because we are highly regulated, we have a massive amount of controls in place to begin with," said Andresen. "We are not starting from zero." That compliance and governance layer has existed for over a decade for the machine learning models Cigna uses, she added, and is closely controlled for any data accessed by third-party vendors.
Andresen recently had to hunt for answers to these common healthcare questions after a close family member was diagnosed with breast cancer. She said the experience showed that personalization, not just navigation, is the differentiator AI can provide.
"I think we're headed to a place where we are going to find that AI in healthcare becomes conversational, ambient, and more proactive," said Andresen. "We can be more and more precise with treatments, with recommendations, and we can get better and better at understanding what works…and feed that back into our models, so that everything gets better all the time."
How Cigna builds and buys AI
Andresen joined Cigna in September 2021, her first role leading a healthcare company after serving as a senior vice president at Capital One and in executive roles at tech firms Cricket Media and Network for Good. Earlier in her career, she worked as a foreign correspondent for Reuters News and the Associated Press.
She said AI technology is evolving so rapidly that a mix of Cigna's proprietary data and partnerships with big AI players will be the differentiator. Cigna has deployed workplace tools like Microsoft Copilot and AI coding agent Cursor, while working with OpenAI and Anthropic to tap their large language models.
There are also times when Cigna works closely with AI startups focused on specific use cases, like Sierra, which builds conversational agents for customer service. "We've worked really closely with them on their product roadmap," said Andresen.
Other generative AI use cases include using LLMs to summarize millions of phone calls to call center agents, then creating an AI tool that makes it easier for employees to search for answers to questions like, "does my policy cover this treatment for plantar fasciitis?" An AI virtual assistant inside Cigna's mobile app addresses patient questions, while AI-enabled summarization has reduced note-taking by up to 90% for health practitioners who work for Cigna's telehealth service MDLIVE.
"The principles behind all this are hopefully clear, which is, what problem are we trying to solve, and how can AI help?" said Andresen. "That's always the starting point."
Why this matters for healthcare professionals
Cigna's approach offers a template for healthcare organizations under pressure to show ROI on AI investments. The company pairs cost-saving initiatives - like the biosimilar campaign that redirected patients to cheaper alternatives - with clinician-facing tools that cut administrative burden. For healthcare professionals evaluating AI for AI for Healthcare applications, the lesson is to start with a specific problem, measure the outcome, and let the data guide expansion. Andresen's framing - "how do I lead in an age of AI?" - applies to clinicians and administrators as much as executives: the goal isn't adopting technology, it's improving care and reducing costs. For those working in AI for Insurance contexts, Cigna's use of customer conversation data to drive enrollment decisions shows how AI can translate unstructured information into measurable action.
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