Cigna AI Strategy | How They Cut Costs & Improve Health

Shifting the Focus: Cigna's AI Strategy

Katya Andresen joined The Cigna Group as chief data, digital and AI officer in September 2021. The rapid rise of generative artificial intelligence shortly thereafter prompted a common question across the industry: how can we use this technology? Andresen rejects that premise. She argues that the objective is not simply to adopt tools but to lead in an age of machine intelligence. This perspective prioritizes measurable health outcomes over the simple acquisition of software.

Cigna is currently testing this approach with financial projections tied to specific clinical interventions. The company expects AI and predictive analytics to help patients identify chronic conditions like cancer, kidney disease, and high-risk pregnancy. These tools aim to connect patients with clinicians earlier than traditional methods allow. Cigna projects this will save roughly $200 million in medical expenses over the next three years. A separate $100 million investment through 2028 is currently targeting the administrative burden on clinicians. By using AI to handle documentation, the company intends to speed up the prescription process.

Solving Complex Healthcare Problems

One practical application of this technology involves biosimilars. These drugs treat chronic diseases at a lower cost than biologics, yet they differ in composition. Cigna analyzed thousands of customer service calls to understand why patients were hesitant to switch to these cheaper alternatives. The data showed a lack of clarity in communication. Using those insights, the company crafted targeted messaging to explain the benefits of biosimilars. This campaign resulted in over 80% of targeted patients switching to the more affordable drug, generating substantial savings.

Generating these efficiencies is vital for a company with $275 billion in annual revenue. National healthcare spending in the United States now exceeds $5 trillion annually. Factors like an aging population and the high cost of hospital stays drive these figures upward. Many patients feel frustrated by the current system. Gallup research from April indicates that millions of adults now turn to chatbots for health information before visiting a doctor. Some even skip professional appointments after using these tools. This shift creates a need for clear governance.

Governance and Future Outlook

Healthcare remains a highly regulated sector. Andresen notes that Cigna does not start from zero regarding oversight. The company has applied strict controls to machine learning models for more than a decade. Any data accessed by third-party vendors faces similar scrutiny. While the company partners with firms like Microsoft, OpenAI, and Anthropic, it also builds proprietary tools to maintain a competitive advantage. For example, Cigna deployed an AI virtual assistant within its mobile app and uses large language models to summarize call center interactions.

Future success depends on personalization. Andresen envisions a system that is conversational and proactive rather than reactive. She believes the ability to feed results back into models will improve recommendations over time. As the technology continues to evolve, the distinction between hype and utility will become clearer. Cigna intends to focus on the specific problems that warrant an automated solution, ensuring that each investment contributes to better patient health.