In healthcare, what doesn’t show up on a dashboard often ends up defining the real story. The quiet backlog of prior authorizations delaying care. Coding errors that slip through unnoticed until denials stack up. Payer-provider misalignment draining revenue in ways that rarely make the headlines. These are the everyday challenges healthcare organizations face in managing the revenue cycle, but they often remain unspoken, unaddressed or misunderstood.
That’s what made the inaugural session of RCM Unplugged: Insights Beyond the Numbers such a timely and necessary conversation. As the moderator of this LinkedIn Live discussion, I had the privilege of engaging with three seasoned experts – Bond Ortiz, Cissy Mangrum and Kari Cornicelli – who collectively brought diverse experience across revenue transformation, operational optimization and healthcare financial strategy.
Their message was clear: Artificial Intelligence (AI) and automation are already re-shaping healthcare Revenue Cycle Management (RCM), but only when implemented with purpose, precision and perspective.
The Numbers Behind Smarter Implementation
The numbers were compelling. At organizations leveraging AI-driven intelligence:
- Denial rates dropped from 37 percent to less than 5 percent within 60 days.
- Claims processing times shrank from 20–30 minutes to as little as 2-5 minutes.
- Dental providers reduced days in Accounts Receivable (AR) to just 2 percent.
- Cash collections accelerated, and cost-to-collect metrics showed significant improvement.
However, the panelists quickly pointed out that these results didn’t come from deploying more technology but from designing smarter systems that align technology with organizational needs and human workflows.
The Hidden Barriers to AI Success
And that alignment is where the real challenge lies. The panelists spoke candidly about the barriers to AI adoption: Frontline staff worried about job security, decision-makers expecting instant results, fragmented legacy systems resisting integration, and implementation teams struggling with training and change management. These aren’t technical challenges – they're human ones. This is why the panelists unanimously stressed that AI should never be introduced as a replacement for staff, but as an enabler of them. When automation is positioned as assistive, not adversarial, it unlocks engagement, trust and long-term effectiveness.
Designing for Impact: What the Best Get Right
“To drive efficiency, first you must understand the deficiency,” noted Cissy. That insight anchored much of the conversation around successful AI adoption. The most effective implementations, we agreed, began with focused use cases – starting where AI could address high-impact challenges like denial management or eligibility verification.
Vendor selection was another critical point: Not just choosing the most advanced solution, but the one most aligned to the organization’s goals, culture and system architecture. Throughout the discussion, the theme of intentionality emerged repeatedly because in healthcare, transformation that sticks isn’t built overnight. It’s built through careful design.
The ROI of Intelligent Orchestration
Panelists also shared financial metrics that reinforced AI’s tangible business value. Beyond denial rates and AR days, they highlighted clean claims rates, eligibility verification accuracy, top-line revenue impact and return on invested time. One panelist described how AI optimization helped dramatically reduce cost-to-collect, while another pointed to millions in annual revenue recovery linked directly to automation efforts.
As Kari succinctly said, “The bottom line from a CFO’s perspective is that it’s about cash uplift.” In an industry under intense margin pressure, that’s not a nice-to-have – it’s a mandate.
And yet, the conversation never drifted into hype. The experts emphasized that AI is not a silver bullet. It doesn't solve every inefficiency or erase complexity. What it does do, when thoughtfully embedded, is turn cumbersome, manual processes into agile, intelligent systems that can evolve as the business grows. AI makes workflows more fluid, outcomes more predictable and resources more focused.
Smarter by Design: Where Technology and People Converge
At WNS, this belief is central to how we approach healthcare transformation – where AI-powered platforms, human ingenuity and domain expertise converge to build operations that perform better, respond faster, scale easier and adapt stronger. In a space like RCM, where accuracy and timing define financial viability, it’s not about adding more tools. It’s about orchestrating intelligence that’s both technological and human.
Closing Thought: It’s Not About More Automation. It’s About Better Design.
The RCM Unplugged panel closed with a powerful reminder: True innovation in RCM isn’t just about chasing automation. It’s about elevating people and processes to new levels of resilience. And that kind of transformation doesn’t happen by accident. It happens by design.
Ready to delve deeper? Watch the full session of RCM Unplugged: Insights Beyond the Numbers to explore real-world challenges, breakthrough outcomes and lessons.