bridging the divide in U.S. healthcare with human-AI collaboration

Podcast Audio Transcript

Mimi: Hello listeners, this is Mimi; thank you for tuning in to yet another exciting and informative podcast from us at Infosys BPM. Today, we are discussing about reimagining healthcare. today we’re diving into one of the most urgent challenges in U.S. healthcare—the nursing shortage—and how AI and human collaboration could be the lifeline we need.

Joining me today are two experts: Ana Maria Sanchez, an industry veteran in the clinical space and a Nurse, and Prashant Ramineni, Solution Design Head of Healthcare practice at Infosys BPM.

Welcome to both of you!

Ana: Thanks, Mimi. It’s great to be here!

Prashant: Likewise. It’s exciting to be part of this podcast.

Mimi: Awesome! Let’s start with the big picture, shall we? Ana, how serious is the nursing shortage in the US and what is driving it?

Ana: It’s more than serious, Mimi. I would say we are currently in crisis. By 2030, the US is projected to face a shortage of over 500,000 registered nurses. This is according to the US Bureau of Labor Statistics.

That’s not just a staffing issue—it’s about overall care delivery. A few big factors are behind this: We have an aging population with more chronic conditions, an aging workforce with nearly a million registered nurses nearing retirement, and bottlenecks in nursing education—over 92,000 qualified applicants were turned away just due to shortages of faculty and clinical sites, this was reported by the AACN

Add to that workplace stress, burnout, and even violence, and we’re looking at a situation where fewer people are staying in or entering the profession. What’s the ripple effect on this? Delays, increased hospital costs, and potentially compromised care quality.

Mimi: Wow, Ana, that really does seem complicated. Must be really overwhelming. So, how does this shortage impact patients and healthcare operations on the ground?

Ana: I couldn’t agree more, Mimi. Quite an overwhelming situation. The impact is universal—from ER backlogs to longer wait times and overworked nurses. When nurse-to-patient ratios drop, we see more missed diagnoses, delayed treatments, and lower patient satisfaction.

Nurses burning out results in higher turnover, and hospitals then spend more on recruitment and training to just stay afloat. Even behind the scenes, the shortage affects prior authorizations, care coordination, and claims processing. The whole continuum of care takes a hit. This is why many organizations are rethinking how they deliver care and looking at scalable solutions—especially in AI-powered outsourcing and digital interventions —to manage the demand without sacrificing quality.

Mimi: Right! Outsourcing and technological interventions can be the perfect solution to many problems. Can you share how healthcare organizations are using BPM to bridge this concerning care gap?

Ana: Absolutely, Mimi. Business process management is key in addressing our nursing shortage. BPM organizations mitigate the risk by outsourcing clinical support tasks, such as care coordination, prior authorization, and utilization management.

There’s a clear shift toward globally distributed teams—leveraging skilled nurses and care coordinators from nearshore and offshore hubs like India and South Africa. These professionals handle non-core functions such as case preparation and claims review, working closely with the U.S-based providers.

You know, the advantage of this model is that it reduces administrative strain, boosts operational efficiency, and allows clinical staff to focus more on direct patient care.

Mimi: Now, AI is a key piece in this puzzle. We are seeing a lot of AI being deployed in outsourcing interventions.

Prashant, from your perspective, what specific roles does AI play in mitigating such a crisis?

Prashant: Great question, Mimi. I would say AI tools go hand-in-hand with healthcare professionals.

At Infosys BPM, we utilize multi-agent AI framework which can handle tasks such as data capture and digitization of prior authorization requests from various sources (fax, email, portals), including handwritten and unstructured formats. AI agents can extract relevant clinical information, generate case summaries, and highlight key decision points for clinician review. AI agents can also prioritize, and route cases based on urgency and policy rules, with auto-approval for low-risk requests and even generating outcome recommendations, that frees up lot of time for the US-based nurses to focus on actual patient care.

We also deploy centralized dashboards and unified case management tools to streamline workflows and improve coordination across teams. It’s a true collaboration between human expertise and machine efficiency.

Mimi: That’s awesome! I bet it really makes things better for your customers.

Prashant: No doubt about that! Customer experience is vital for us. We are constantly investing in AI-powered tools to elevate patient experience by delivering fast and personalized customer services.

Here are some examples: Intelligent chatbots and voice assistants offer 24/7 multilingual support, while predictive AI helps anticipate patient needs, like reminders or follow-ups. These technologies create smoother, more responsive interactions, making healthcare feel more accessible and customer centric.

Mimi: That’s great to hear Prashant! I agree, exceptional customer experience is an absolute necessity these days.

What are some of the more advanced AI tools being used, and how do they enhance patient care?

Prashant:Yes Mimi.

One standout example is our GenAI-powered AnswerSmart tool. It dynamically generates context-specific responses to clinical and administrative questions—so instead of digging through manuals or asking around, nurses get immediate, reliable answers.

We also use predictive analytics to flag care gaps and identify high-risk patients. Combine that with remote patient monitoring and agentic AI assistants, and you’ve got a care system that’s not just responsive, but proactive.

These technologies empower teams to make faster and smarter decisions without overwhelming the staff. By automating routine tasks and extracting relevant insights, they reduce cognitive load. This way, we can keep the humans in the loop for critical judgment and compassionate care where it matters the most.

Mimi: Final thoughts. Ana, how can healthcare leaders begin this transformation? What’s the mindset shift required?

Ana: The key is to stop thinking of this as just a temporary fix for a labor shortage. It’s actually a moment to reimagine care delivery.

Healthcare leaders need to embrace a hybrid model—where human empathy meets digital intelligence. It’s about building a resilient, data-driven, patient-centric ecosystem.

Start with your biggest operational pain point—whether it’s administrative overhead or care coordination—and look at how intelligent automation and distributed teams can help.

At Infosys BPM, we work with payers to tailor this journey, combining global talent and technology to meet long-term care demands. The sooner we act, the better we’ll be prepared—not just for 2030, but for the next generation of healthcare.

Mimi: Thank you, Ana and Prashant, for these incredible insights. It’s clear that solving the care divide won’t happen overnight, but with smart, human-AI collaboration, the future looks bright. Thanks for being part of the Infosys BPM podcast.

Ana:It was a pleasure, Mimi. I truly enjoyed our conversation and will definitely look forward to more such engaging and insightful discussions in the future.

Prashant:Thanks, Mimi! Loved our chat on tackling this nursing crisis — AI and BPM have so much potential to make a real impact.

Mimi: Great! Thank you both!

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Also, if you have any queries, do reach out to us through the Infosys BPM website – www.infosysbpm.com. Once again, thank you for tuning in, stay safe and sharp. This is Mimi signing off. Have a great day!