Since her appointment as the chief data, digital, and AI officer at Cigna Group in September 2021, Katya Andresen has observed a significant shift in the landscape due to the rise of generative artificial intelligence. This has prompted many to consider a pivotal question: “How do I utilize AI effectively?” However, Andresen believes this inquiry misses the mark. “We are reframing it to, ‘how do I lead in an era of AI?’” she explains. This perspective emphasizes the importance of measuring the impact of AI investments on health outcomes, rather than simply exploring various functionalities.
In line with this vision, Cigna recently announced that its AI and predictive analytics solutions aimed at detecting chronic conditions—such as cancer, kidney disease, and high-risk pregnancies—are expected to generate savings of around $200 million over the next three years by facilitating proactive patient-clinician connections. Additionally, the company pledged a $100 million investment through 2028 to enhance the documentation process for clinicians, thus expediting prescriptions with the help of AI.
Andresen also shared insights into a specific AI initiative aimed at clarifying patient inquiries regarding biosimilars, which offer cost-effective treatments for chronic illnesses. Unlike generics, biosimilars, which are derived from living organisms, have variations compared to their branded counterparts. For context, a treatment like Humira could cost a patient up to $7,000 monthly. By analyzing numerous customer interactions, Cigna was able to enhance its digital communication on biosimilars, leading over 80% of patients to choose this more affordable alternative. “This not only improved margins but also resulted in substantial savings for patients,” noted Andresen.
As Cigna generates $275 billion in annual revenue and ranks 14th on the Fortune 500, these cost-saving measures are crucial amid national healthcare spending exceeding $5 trillion yearly, largely driven by chronic conditions, an aging demographic, and rising hospital stays and drug prices.
Many patients express frustration over navigating the convoluted healthcare system and have turned to AI tools like ChatGPT for answers. According to a Gallup survey, nearly 60% of respondents have utilized AI for health information prior to doctor visits, with around 14 million adults stating they have even skipped appointments after consulting AI. This trend raises vital concerns regarding data security and the accuracy of answers provided by AI chatbots, particularly those developed by insurance and pharmaceutical firms that handle sensitive patient data.
Andresen reassures that Cigna operates under stringent regulations, providing a solid framework of controls established over the past decade for various data-driven models, ensuring data access by third-party vendors is also tightly regulated.
Recently, she confronted personal healthcare challenges when a family member was diagnosed with breast cancer. This experience underscored her belief that AI’s true value lies in delivering personalized insights rather than just improving navigation. “I foresee a future where AI in healthcare becomes conversational, ambient, and increasingly proactive,” she predicts. “This progress allows for greater precision in treatments and recommendations, continuously refining our understanding of effective strategies.”
When Andresen took on her role at Cigna five years ago, it was her first experience in the healthcare sector, having previously held high-level positions at Capital One and tech-focused organizations like Cricket Media and Network for Good. She notes that the rapid evolution of AI necessitates a blend of Cigna’s proprietary data for developing tools tailored to competitive needs, along with strategic partnerships with major AI entities. Recent initiatives include deploying Microsoft’s Copilot and the AI coding assistant Cursor, and collaborating with leading AI companies like OpenAI and Anthropic.
Cigna also emphasizes partnerships with specialized AI startups such as Sierra, known for creating conversational AI tools for customer service. “We’ve engaged closely with them to refine their product development,” Andresen remarks.
Other innovative applications of generative AI at Cigna encompass utilizing large language models to distill insights from millions of call center interactions, aiding employees in quickly addressing queries like policy coverage for specific treatments. The company also developed an AI virtual assistant within its mobile app to respond to patient inquiries. In clinical settings, AI summarization technologies have cut note-taking time for Cigna’s telehealth service, MDLIVE, by up to 90%.
“The core principle guiding these initiatives is clear: what challenge are we addressing, and how can AI contribute?” Andresen emphasizes. “That’s always our starting point.”
