Why 95% of Healthcare AI Fails and How Post-Acute Care Can Scale Automation That Works [INOvators]

Описание: Why do most healthcare AI solutions never make it to scale?

In this episode of INOvators, Sudha Sureddi, VP of Product Management at Brightree, explains why 95% of AI products in healthcare fail and what post-acute and home care organizations can do differently.

We explore how successful AI adoption isn’t about flashy automation, but about compressing workflows without disrupting them. Sudha shares real-world examples of AI embedded directly into existing processes, including how automation reduced order-to-cash timelines from days to minutes, enabling faster scheduling, quicker patient response, and better operational outcomes.

You’ll also hear Sudha’s perspective on:
• Scaling AI in post-acute and home care
• Avoiding workflow disruption and “visual shock”
• Measuring intangible ROI beyond cost savings
• Why AI governance and training determine adoption success

If you’re navigating reduced reimbursements, workforce shortages, or rising operational costs, this conversation offers a practical roadmap for using AI where it actually delivers value.

Listen to the full INOvators episode and learn how to scale automation that works without breaking the workflow.

For more insights from industry leaders, check out Inovalon INOvators: https://ow.ly/JJCw50TJNKm

Chapters
0:00 – AI & Automation in Post-Acute Healthcare | INOvators Series
How healthcare leaders are scaling AI responsibly in post-acute and home care.
0:12 – Meet Sudha Sureddi | Product Leadership in Healthcare AI
Sudha Sureddi, VP of Product Management, on building automation that actually works.
0:26 – Why Post-Acute Care Needs Automation Now
Reduced reimbursement, staffing shortages, and rising operational complexity.
1:29 – What Healthcare Workflows Should (and Shouldn’t) Be Automated
Separating repetitive tasks from human-driven clinical decision-making.
2:20 – Proving ROI for Healthcare AI Without Burning Out Teams
Balancing efficiency gains, adoption, and change fatigue in clinical settings.
2:50 – Designing Automation Without Disrupting Clinical Workflows
Reducing “visual shock” to drive AI adoption in healthcare software.
3:38 – Measuring ROI Beyond Cost Savings in Healthcare Automation
From revenue cycle improvements to employee satisfaction and retention.
4:37 – Human-Centered AI in Healthcare: Protecting Empathy
How automation can enhance—not replace—the human element of care.
4:56 – Why Most Healthcare AI Fails (and How to Avoid It)
Putting clinicians and users at the center of AI innovation.
5:53 – Real-World Example: Automating Order-to-Cash in Post-Acute Care
Compressing workflows from days to minutes to accelerate patient care.
7:03 – Scaling AI Across Complex Healthcare Organizations
Standardization vs. customization in post-acute and home health settings.
8:12 – The Future of AI in Healthcare Workflows
Where the next wave of automation will drive the most impact.
8:58 – Preparing Healthcare Teams for AI Adoption
Training, governance, and managing expectations across the organization.
10:15 – Final Takeaway: Scaling AI Without Losing the Human Touch
Why disciplined, purpose-driven AI matters in healthcare.
10:48 – What’s Next on INOvators
More conversations on healthcare innovation, data, and intelligent workflows.
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