Doing More With Less: How AI in Healthcare Cost Reduction Is Changing the Cost Equation

Introduction

The United States spends about 18% of its GDP on healthcare, far more than peer nations, and that share is on track to reach roughly 20% in the early 2030s. A big part of the problem is not care at all. Administrative work such as billing, insurance tasks and compliance accounts for an estimated 15 to 30% of total health spending

At the same time, the people who keep that machine running are stretched thin. In Third Way Health's 2026 survey of 200 healthcare executives, 92.5% said their practices were not fully and sustainably staffed. Patient calls, scheduling requests and insurance questions keep coming regardless.

So how does AI reduce costs in healthcare? In short, it automates routine administrative and patient interactions, makes every staff member more productive, and reviews every conversation to catch problems before they become expensive. Researchers writing for the National Bureau of Economic Research (NBER), a US economics research group, estimate that wider AI adoption could save 5 to 10% of US healthcare spending, or $200 to $360 billion a year (in 2019 dollars).

But "doing more with less" does not mean doing it with fewer people. The organizations seeing real returns pair AI with their teams instead of swapping one for the other. Here is where the savings come from, and how to capture them without hurting the patient experience. If you want the contact center view first, start with how AI cuts healthcare contact center costs.

Why Is Healthcare's Cost Equation Broken?

Healthcare organizations face a squeeze from both sides. Costs keep rising, and the workforce needed to manage patient demand keeps shrinking.

Front-office and contact center teams feel it first. Turnover in front-office roles has reached at least 40% in nearly three in ten organizations, according to the same Third Way Health survey. Every departure means recruiting, onboarding and training, while the remaining staff absorb the extra calls. Wait times grow, calls get abandoned, and patients who cannot get through either go elsewhere or call back, adding more volume to an already overloaded queue. Shorter agent ramp time is one way teams soften the blow of constant turnover.

The traditional answer has been to hire more people or outsource to a business process outsourcing (BPO) vendor. Both add cost, and neither fixes the underlying problem: too much skilled human time goes to work that does not need a human.

Where Does AI in Healthcare Cost Reduction Actually Happen?

Not all healthcare AI saves money on the same timeline. It helps to split the opportunity into two buckets.

1. Clinical Care and Drug Discovery: Big, but Long-Horizon

Morgan Stanley Research estimates AI could generate $400 billion to $1.5 trillion in US healthcare savings by 2050, much of it from faster drug development and better hospital care. These gains are real, but they take years to show up in budgets. AI-assisted drug discovery alone is likely at least five years from meaningfully affecting costs.

2. Administration and Patient Operations: Savings Now

The nearer-term opportunity is administrative. The 2025 CAQH Index, an annual industry report on healthcare administrative spending, found that automation and electronic transactions helped US healthcare avoid an estimated $258 billion in administrative costs in 2024, with about $21 billion more still on the table. More than half of health plans, but only a quarter of providers, now use AI in administrative workflows.

That gap is the opportunity. And nowhere is it bigger than in the patient-facing operations layer: the contact center, scheduling desk and member services teams that handle millions of conversations every year. Healthcare organizations can see the full picture in this guide to AI in healthcare operations. Three moves deliver the biggest impact.

1. Automate the Routine

A large share of patient calls are simple and repetitive: booking or moving an appointment, checking insurance coverage, confirming a location or asking about a bill. These requests matter to patients, but they do not need a trained agent.

AI virtual agents can resolve these low-touch requests end to end, any time of day, with no hold queue. Every request they handle is one less call for a human agent, which frees staff to focus on complex, sensitive or high-value conversations: clinical questions, billing disputes, worried patients who need reassurance. Scheduling is a good example, and this look at AI voice agents for patient scheduling shows how it works in practice.

The result is lower cost per contact and shorter wait times for the patients who do need a person. In one example, a global healthcare provider automated 45% of its prescription requests with Level AI.

2. Make Every Agent More Productive

For the conversations that still need a human, AI can make that person faster and more accurate. Real-time agent assist listens alongside the agent, shows the right answer or next step, and handles after-call work such as summaries and disposition notes (the label that records how a call ended).

That translates directly into lower average handle time (the total time an agent spends on one call) and higher first-call resolution (the share of issues solved on the first contact). Fewer callbacks mean less repeat volume, and faster calls mean each agent can serve more patients per shift. Over time, organizations can absorb significant growth without adding headcount at the same rate. Contact center leaders can see how this works in how leaders use Level AI to reduce average handle time.

The returns are showing up in the data. The 2026 Healthcare AI ROI Scorecard from Bain & Company and Bessemer Venture Partners, based on a survey of 226 executives across payers, providers and pharma, found healthcare AI delivered an average 3.5x return, typically within about 12 months instead of the 24 months executives expected. Provider front-office use cases returned 3.1x, and payer member engagement returned 3.2x. For a step-by-step way to track your own numbers, see how to measure the ROI of AI in healthcare call centers.

Source: Bessemer Venture Partners, with use-case figures reported by HLTH.

3. Quality and Compliance at 100% Coverage

Most healthcare contact centers still review only a small sample of interactions by hand. That means quality teams miss most of what happens, compliance risks slip through, and coaching relies on a handful of calls. The hidden cost of unreviewed customer conversations adds up quickly.

AI changes the math. Automated quality assurance can score every phone call, chat and email against your criteria, reducing the manual QA workload while giving leaders a complete picture. Instead of guessing which agents need help, supervisors get data-driven coaching plans tied to the outcomes that matter: quality of care, patient experience, health outcomes and payment collections.

Full coverage also strengthens compliance. When every interaction is reviewed, issues like missed disclosures or privacy lapses are caught early, before they become costly. Here is a practical walkthrough of how to audit 100% of healthcare calls.

Does AI Raise Healthcare Costs? The Honest Answer

Not every expert is convinced AI will lower healthcare spending. Health economists have raised fair concerns, mostly about clinical AI:

1. More imaging and testing. Faster, cheaper image reading could increase how often scans are ordered.

2. Care cascades. AI that spots more incidental findings can trigger follow-up tests with no clear benefit.

3. A coding arms race. Providers use AI to capture more billable diagnoses while payers use AI to push back, adding cost on both sides.

These risks share one trait: they increase the volume of care or claims. Operational AI works differently. Answering a scheduling call faster, scoring every interaction for quality, or resolving an insurance question on the first contact does not generate extra procedures. It lowers the cost of each interaction while improving the experience.

That is why patient operations is one of the safest places to start. The savings are measurable within months, the risk of driving extra utilization is low, and patients notice the difference. In the Third Way Health survey, 79% of healthcare organizations that had implemented front-office AI named improved patient experience as their top outcome.

How Can Healthcare Teams Do More With Less Using Level AI?

Level AI works with healthcare organizations across enrollment, clinical support, testing support and scheduling. Its platform brings automation, agent productivity and conversation analysis together in one place, so patient operations teams can grow without growing costs at the same pace. See how this fits healthcare organizations of different sizes.

1. Virtual Agents That Handle the Routine

Level AI's virtual agents for healthcare take on repetitive, low-touch requests such as scheduling, rescheduling and insurance information. Handling those requests without a live agent lowers labor costs and keeps queues short for patients who need a person.

2. Agent Assist That Speeds Up Every Conversation

AI-powered agent assist and co-pilot tools help agents find answers faster, reducing handle time and increasing first-call resolution. Teams can support significant growth without adding staff at the same rate.

3. 100% QA and Data-Driven Coaching

Level AI automatically evaluates every phone call, email and chat, reducing the need for manual QA analysts. Its analysis of patient interactions generates agent coaching plans that improve quality of care, patient experience, health outcomes and payment collections.

4. A Complete View of the Patient Voice

Level AI brings all conversation data into a single view, with drill-downs by BPO, team, agent, product, brand or carrier. The voice of the customer module uses AI that finds patterns on its own to surface emerging trends and sudden spikes in topics, as many teams saw with COVID-19, so leaders can act before small issues become costly ones. Combining conversation data with other operational data breaks down silos and pinpoints avoidable follow-ups.

Built for Healthcare

1. Privacy and compliance: Level AI is HIPAA compliant and signs Business Associate Agreements (BAAs), the contracts that make a vendor legally responsible for protecting patient data. Read more about HIPAA-compliant AI voice agents.

2. Proprietary AI: Level AI runs on its own engines rather than relying on external models like ChatGPT, keeping sensitive patient data under tighter control.

3. Medical vocabulary: Entity detection (the tools that pick out names, drugs and conditions in a conversation) and models are tuned for medical terminology and drug names.

4. Sensitive-topic alerts: Teams can set real-time alerts for sensitive topics, such as signs of suicidal ideation in teletherapy conversations, so a human can step in quickly.

As one theme from Level AI's healthcare customers puts it, AI is not a replacement for human interaction. It is a tool to "supercharge and inform people to do better by their customers, their patients and their organization internally."

How Level AI Helps Healthcare Teams Do More With Less

Healthcare's cost equation will not be solved by any single technology. But the evidence is clear that AI in healthcare cost reduction is already working where patients and staff meet: in the contact center, at the scheduling desk and across member services. Automating the routine, making every agent more productive and reviewing every interaction let lean teams do more with less, without trading away patient experience.

The organizations pulling ahead are not choosing between people and AI. They are using AI to help their people do their best work, and Level AI gives healthcare teams the tools to do it with the privacy controls patients expect.

Ready to see what that looks like for your team?

Level AI helps healthcare teams cut the cost of every patient interaction without cutting the care behind it. Book a short session to see virtual agents, agent assist and automated QA applied to your own conversation data. You will leave with a clear view of where your biggest savings sit.

Schedule a demo

Ready to see what that looks like for your team?

Level AI helps healthcare teams cut the cost of every patient interaction without cutting the care behind it. Book a short session to see virtual agents, agent assist and automated QA applied to your own conversation data. You will leave with a clear view of where your biggest savings sit.

Schedule a demo