Artificial intelligence has become a fixture in healthcare. Yet, despite the excitement, most of what we call “AI innovation” today remains incremental. The transformative promise of AI lies in its ability to redesign—not merely refine—how patients experience care, how care providers deliver it and how payers work with both to enhance the healthcare journey.
Leaders at the intersection of business, clinical practice and technology must recognize that the next wave of innovation won’t come from “stacking efficiencies” or layering AI on top of old systems. It will come from redesigning products and services with AI in mind to create connected experiences that keep the consumer at the center. This will ultimately help make meaningful gains in affordability, simplicity and sustainability across the ecosystem, as well as help deliver outcomes that are more personal and predictive.
From incremental point solutions to experiences
Healthcare’s digital evolution has often been reactive, responding to inefficiencies one at a time. The result is a proliferation of “point solutions” that optimize specific functions such as billing without addressing systemic fragmentation.
Consider a typical implementation that uses separate AI tools to engage patients, analyze lab results and manage scheduling. While each solution may have a measurable return on investment, this approach creates a disjointed ecosystem. For consumers, this translates into a fragmented healthcare journey. For care providers, it breeds fatigue with too many disconnected tools.
To move beyond this patchwork model, healthcare organizations must reposition digital technologies, such as AI, as platforms that securely and appropriately unify the experience for consumers, care providers, payers and other stakeholders. Such an experience-driven digital technologies approach can drive innovation where AI integrates data and data-driven insights—consistent with privacy and security standards—across clinical, operational and behavioral touchpoints, creating an ecosystem that is more proactive, more supportive, more affordable and simpler.
Imagine a patient with cancer whose physical function significantly declines after chemotherapy. An AI system analyzing electronic, patient-reported outcome data, lab results and population-level patterns, complemented with wearable data, could flag this decline early, triggering an outreach before the patient ends up with more significant healthcare impacts or an emergency. This isn’t science fiction; it’s achievable with today’s technology.
Meeting the needs of patients and providers
One of the more interesting design challenges in healthcare is how to create AI-enabled solutions that serve the needs of both the patient and the care provider simultaneously. Too often, technology helps one at the expense of the other.
Experience-centered AI starts with understanding all perspectives. It recognizes that the patient’s engagement depends on the care provider’s ease of delivery, and the care provider’s trust depends on the patient’s satisfaction and achievement of their desired outcomes. In this new paradigm of AI-enabled tools, care providers can focus more on their patients because payers are helping to reduce administrative burden, and patients are given a simplified healthcare experience.
For example, imagine an AI-driven clinical decision support system that both surfaces evidence-based treatment options and contextualizes them in terms of a patient’s preferences and benefits coverage, as well as their individual situation and needs. This kind of personalization transforms AI from a computational assistant into a communication partner, augmenting, not replacing the human connection.
When both patient and care provider trust the system, treatment adherence increases, communication strengthens, and health outcomes improve. That trust, rooted in transparency and shared experience, creates a reinforcing loop that also improves system efficiency and cost-effectiveness.
Designing for outcomes, not outputs
The promise of AI in healthcare lies not in the sophistication or number of models there are, but in how they’re used to deliver higher-quality outcomes and combine efficiency with empathy. Experience-centered AI reframes the question from “What can the model do?” to “What outcomes can it drive better?”
When designed around human experience, AI becomes a medium for increasing engagement and improving health outcomes in the healthcare system. For care providers, that means giving them more time to focus on their patients and surfacing insights at the right moment to help deliver higher quality care. For consumers, it means being understood as a person, not processed as a record.
Implementing AI responsibly is paramount
AI has the power to transform healthcare, but that transformation must occur responsibly and transparently to foster user trust. As AI rapidly evolves across industries and healthcare, adoption is heavily based on the trust that harmful bias is mitigated and personal data is safeguarded—focusing on innovations that are fair and protect privacy, while simplifying care and enabling personalization.
A responsible AI framework provides clear guardrails, aligns with industry standards and fosters collaboration across stakeholders for credibility and organizational buy-in.
The road ahead
AI’s greatest contribution to healthcare may not be automation or scale; it may be its ability to make healthcare a more consumer-centric and personal experience.
By treating AI as a powerful, intelligent, integrating feature for the healthcare experience, we can move beyond incremental gains to meaningful transformation. We can build systems that are both intelligent and personal, guided by the understanding that technology should be focused on enhancing the healthcare journey.
Organizations that succeed in the next decade will not be those with the most algorithms, but those with the clearest alignment between AI capability, human connectedness, and consumer-centered outcomes.
If we drive a materially better, more cohesive, and trustworthy system among payers, care providers, and consumers, we’ll enhance experiences, address affordability, and improve health outcomes.
Ratnakar Lavu is chief digital information officer at Elevance Health.
Gautam (G) M. Shah chief product officer at Carelon, which is part of Elevance Health.
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