The AI wave in healthcare revenue cycle management (RCM) shows no signs of slowing down. Every week, new solutions promise automation, intelligence, and operational efficiency. But for CFOs, the real challenge isn’t in hearing the pitch — it’s in separating substance from hype.

AI is not magic. It’s software. And like any software investment, it demands thoughtful evaluation.

Before signing a contract or approving a pilot, here are five questions every healthcare CFO should be asking about AI. The answers will reveal whether a vendor is offering true value — or just repackaging familiar automation with a shiny new label.

1. Can You Show Me the AI’s Work? (Explainability Matters)

It’s easy for vendors to claim their AI “learns” or “makes decisions,” but if the system can’t show its reasoning, that’s a problem. As a CFO, you should expect transparency.

Ask the vendor:

How does the AI surface its decision-making process?
Can my team see which rules, data points, or payer guidelines were used for each task?

This isn’t just an academic concern. In a denial review or audit scenario, your team needs clear documentation of why a submission was made a certain way. A mature AI solution should provide an explainable path from input to outcome — not just a black box result.

2. What Business Outcomes Will You Measure — and How?

Good AI vendors focus on business results, not just task automation. You should be hearing clear metrics like:

Reduction in denial rates
FTE hours saved
Improvements in first-pass claim success
Turnaround time for workflows like prior authorization

Beyond promising these metrics, the vendor should commit to tracking and reporting them regularly. If a solution claims to reduce denials by 20%, it should be able to show you baseline performance, incremental improvements, and a roadmap for optimization.

Don’t settle for vague promises. Make them quantify.

3. How Will You Ensure Compliance and Audit Readiness?

AI’s ability to automate tasks is a double-edged sword. If not properly governed, it can amplify compliance risks — particularly in areas like coding, documentation, and payer guidelines.

CFOs should ask vendors:

How do you align AI outputs with payer requirements and CMS regulations?
What audit trails are created for each automated transaction?
How are exceptions flagged for human review?

Regulatory scrutiny in healthcare isn’t decreasing. Any AI solution must embed compliance into its workflows, not bolt it on later. Audit readiness needs to be part of the product, not an afterthought.

4. Is Your AI a Black Box — or Can We Tune It?

One of the most overlooked risks with AI investments is vendor lock-in through opacity. If the system’s logic, rules, or performance thresholds can’t be configured by your team, you’re left dependent on the vendor for every adjustment.

You should ask:

How adaptable is the AI to our specific workflows and payer mix?
Can we adjust rules or thresholds as our needs evolve?
What visibility do we have into its learning process over time?

AI solutions must be flexible enough to reflect your organization’s policies and adaptable as payer dynamics shift. Avoid systems that operate like sealed boxes — you’ll end up handcuffed.

5. How Will This Integrate with Our Existing Systems?

No AI solution lives in isolation. Its success depends on how well it fits into your existing EHR, practice management, and RCM workflows.

CFOs should demand clarity on:

How does this AI solution pull data from our current systems?
Will it require additional interfaces, middleware, or manual data entry?
How will it impact staff workflows — will it reduce clicks, or add them?

Interoperability isn’t just an IT problem; it’s an operational efficiency problem. AI that doesn’t “speak” to your systems creates workarounds that negate its value. A good solution will integrate seamlessly, enhance workflow efficiency, and reduce redundancy.

6. What’s the Cost Model — and Where’s the ROI?

AI is often pitched as a path to efficiency. But for CFOs, the conversation needs to get more specific, with a breakdown of total cost of ownership (TCO), including:

Upfront and ongoing costs — including licensing, integration, training, and support
How pricing scales with patient volume, claim load, or expansion to new sites
Projected ROI and payback period, tied to tangible metrics like FTE savings or reduced denials

Equally important is understanding how costs scale over time. Will your spend double if you add a new site or increase patient volume by 20%? Is pricing tied to outcomes, or simply to usage?

The Takeaway: Skepticism is Healthy

As a CFO, you have a responsibility to cut through vendor gloss and ask the tough questions.

Focus on outcomes, transparency, and alignment with your organization’s real-world workflows. If a vendor can’t provide clarity on these five areas, they’re not ready to be a partner in your success.

To explore how Infinx AI supports patient access and revenue cycle teams, visit www.infinx.com/revenue-cycle-ai-agents.

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