Artificial Intelligence does not equal Artificial Infallibility

By Stephen Kinsella

There’s a phrase I keep coming back to as artificial intelligence continues to find its way into healthcare operations:

Artificial intelligence does not equal artificial infallibility.

It may sound simple, even obvious but in practice, it’s where many organizations get themselves into trouble.

AI is everywhere right now. It’s summarizing documents, scanning evidence, drafting recommendations, and answering questions in seconds. In healthcare, where the volume of data is overwhelming and the pressure to move faster never lets up, AI feels like a lifeline.

And in many ways, it is.

But AI is not a replacement for judgment. It is not a substitute for accountability. And it is certainly not immune to error. That distinction matters, especially in healthcare value analysis, where decisions directly affect patient care, clinician trust, financial performance, and regulatory defensibility.

The Seduction of Speed

Healthcare value analysis has never been a lightweight process. Evaluating new products, technologies, and services requires balancing clinical evidence, safety considerations, operational impact, and financial outcomes, all while navigating multiple stakeholders with competing priorities.

AI promises relief. Faster reviews. Faster summaries. Faster answers.

The danger isn’t that AI is fast.
The danger is that speed can masquerade as certainty.

AI systems are exceptionally good at sounding right. They organize language cleanly. They present conclusions confidently. But confidence is not correctness, and fluency is not fact.

In healthcare value analysis, a polished summary that skips nuance or context can be more dangerous than no summary at all.

Where AI Fits—and Where It Doesn’t

Let’s be clear: AI absolutely belongs in healthcare value analysis.

Used correctly, it can:

• Rapidly digest large volumes of clinical and operational documentation
• Surface relevant evidence that might otherwise be missed
• Identify inconsistencies across submissions
• Reduce the manual burden that keeps skilled professionals stuck in busy work

That’s not replacing expertise, that’s unlocking it.

Where AI does not belong is at the end of the decision chain.

Healthcare value analysis decisions must be explainable, defensible, and auditable. Someone has to be able to answer the question, “Why did we decide this?” with clarity and confidence.  AI can inform that answer, but it cannot own it.

Accountability still rests with people.

The Real Risk: Quiet Erosion of Critical Thinking

The biggest risk I foresee isn’t AI making an obvious mistake. It’s AI being mostly right, often enough that teams stop challenging it.

When professionals defer to AI outputs without interrogation, something subtle happens:

• Critical thinking weakens
• Assumptions go untested
• Biases slip through unnoticed
• Institutional knowledge erodes

Over time, the process may look more efficient but it becomes less resilient.

In healthcare value analysis, resilience matters. Decisions don’t live in isolation. They echo across contracts, formularies, standardization efforts, and patient outcomes.

Why Healthcare Value Analysis Is Different

Healthcare value analysis is uniquely vulnerable to AI misuse because it sits at the intersection of:

• Clinical evidence
• Financial pressure
• Operational complexity
• Regulatory scrutiny

There is no single “right” answer in most value analysis decisions, only trade-offs. AI can help illuminate those trade-offs, but it cannot weigh them in context. It doesn’t understand organizational culture, physician dynamics, or downstream implementation realities.

That understanding comes from experience.

That understanding comes from people.

Blending Human Capital with the Right Amount of AI

This is where the conversation needs to shift from how much AI can we use to how should AI be used.

At Data Leverage Group, that philosophy is embedded directly into VAMS and its AI-powered assistant, VAL AI.

VAL AI was not designed to replace healthcare value analysis professionals. It was designed to support them by doing the heavy lifting that slows teams down while keeping judgment firmly in human hands.

Within VAMS, VAL AI helps teams:

• Summarize complex submissions and supporting documentation
• Highlight relevant clinical evidence and safety signals
• Identify recalls and FDA-reported issues
• Create structured summaries that are transparent and traceable

Just as importantly, VAL AI operates inside the workflow—not outside of it. That means insights stay connected to the request, the documentation, and the decision trail. Nothing becomes a black box.

This is AI that works smarter, not harder and never alone.

The Power of Guardrails

Responsible AI in healthcare value analysis isn’t about limitation, it’s about design.

The right guardrails ensure that:

• AI outputs are clearly distinguishable from human decisions
• Source material remains visible and reviewable
• Teams stay engaged in evaluation, not sidelined by automation
• Accountability remains intact

VAMS was built with the understanding that healthcare value analysis is a team sport. AI strengthens that team by removing friction not by removing responsibility.

A Tool, Not a Verdict

If there’s one mindset shift worth making, it’s this:

AI is a starting point, not a verdict.

In healthcare value analysis, AI should spark better questions, not shut them down. It should free up time for discussion, collaboration, and clinical engagement. It should make strong programs stronger, not replace the very expertise that makes them effective.

When AI is positioned as an assistant instead of an authority, everyone wins:

• Analysts regain time
• Clinicians gain clarity
• Leaders gain confidence
• Patients benefit from better-informed decisions

The Bottom Line

Artificial intelligence is here to stay. And that’s a good thing.

But let’s not confuse intelligence with infallibility.

Healthcare value analysis demands transparency, rigor, and human judgment. The future belongs to organizations that understand how to blend human capital with AI thoughtfully, deliberately, and responsibly.

Because the goal was never to think less.

The goal was always to think better.

Discover the power of VAMS®—click the Request a Demo button below to get started.