Challenges with AI in Population Health – Deployed but No Positive ROI
Although many healthcare organizations have deployed AI, most are not seeing measurable returns. Polling showed that 73% of attendees had deployed AI but not measured ROI, 20% reported no or negative ROI, and only 7% reported positive ROI. These findings mirror industry reports that most GenAI deployments in healthcare have not yet produced measurable value.
The industry’s challenge is not whether AI can be deployed—it’s whether it can deliver ROI. Healthcare cannot afford science experiments. What matters is AI that drives outcomes, lowers cost, and improves patient care.
A key reason for this ROI gap is the limitation of generative AI and LLMs. When not used properly and not given sufficient well-curated data, these models can hallucinate, produce inconsistent outputs, and introduce risks around security, compliance, and bias—issues that are unacceptable in clinical settings. Because of these challenges, healthcare organizations are beginning to pivot toward agentic AI, which not only analyzes but also takes action by orchestrating tasks, validating data, and executing workflows at scale.
Generative AI is only part of the story. The future is agentic AI, which doesn’t just answer questions, it acts.
Audience Poll #1: Which AI solutions have you deployed?
Audience Poll #2: Have you measured ROI from your AI deployment?
Opportunities with Agentic AI
Agentic AI gives organizations more control over inputs, outputs, and actions, enabling reliable scale to impact sufficient populations to develop an ROI. Key use cases include:
- Digital Front Door Agents for 24/7 patient self-service
- Referral Agents to streamline specialist connections
- Care Management Enrollment Agents to automate onboarding
- Care Gap Closure Agents to extend care manager capacity without new staff
“Agentic AI allows us to control the input, the output, and the action—making it possible to scale safely and reliably. The beauty of agentic AI is its ability to automate routine tasks at scale, freeing care teams to do what only humans can do—deliver empathy and clinical judgment.” — Evan Huang, CTO, CareSignal, Lightbeam Health Solutions
Lightbeam’s Predictive and Agentic AI – Automating Routine Tasks
Lightbeam combines predictive risk stratification and prescriptive actioning with agentic automation, turning insights into immediate, scalable actions. This means care teams can identify high-risk patients and intervene quickly, whether through enrollment, referrals, or closing care gaps.
A critical component of this approach is data. Without high-quality inputs, even the most advanced models fall short. Lightbeam integrates both clinical and non-clinical data—such as housing, income, and transportation access—to build a more complete picture of risk.
Lightbeam’s AI Timeline
Lightbeam also achieved Microsoft AI Cloud Partner Certification, one of a handful of their 400,000 partners worldwide, thus far.
Positive ROI Already Emerging – Arizona IDN Case Study
An Arizona-based Integrated Delivery Network applied Lightbeam’s avoidable admission model to 140,000 Medicaid members each month, identifying the top 5% of high-risk patients for intervention. Results included:
Our customer success story in Arizona showed what’s possible: by intervening only on the top 5% of high-risk patients, the care team avoided 65 inpatient admissions in just a few months.
Learn More
Healthcare organizations must move from experimentation to execution with AI innovation. Lightbeam’s predictive, prescriptive, and agentic AI platform is already reducing admissions, driving efficiencies, and delivering measurable ROI.
Visit the link below to learn how your organization can turn AI into measurable value.
https://lightbeamhealth.com/the-art-of-the-possible-with-ai-in-population-health-management/
