The Physician's Guide to Evaluating AI Vendor Claims

Every week, a new AI vendor emails your practice promising to "revolutionize" your workflow, "eliminate" burnout, or "transform" patient outcomes. The pitch decks are polished. The demos are impressive. The ROI projections are extraordinary.

And most of it is misleading.

I've evaluated over 40 AI vendors for healthcare clients in the past 18 months. The pattern is consistent: aggressive marketing claims, thin clinical evidence, vague compliance documentation, and pricing structures designed to lock you in. This guide gives you a systematic framework for cutting through the noise.

Step 1: Evaluate the BAA Before the Demo

Before you watch a single demo slide, request the vendor's Business Associate Agreement. This is your first and most important filter.

Red flags in BAAs:

• •The BAA excludes AI/ML processing from its scope. Many BAAs were drafted before the vendor added AI features and don't explicitly cover model inference on PHI.
• •The BAA allows the vendor to use de-identified data for model training without explicit opt-out. "De-identified" under HIPAA has specific criteria (Safe Harbor or Expert Determination), and vendors sometimes apply looser definitions.
• •The BAA has a breach notification window longer than 30 days. HIPAA allows 60 days, but reputable vendors commit to faster notification.
• •The vendor resists providing a BAA or says one "isn't needed" for their product. If PHI touches their system in any form, a BAA is required. Full stop.

What to look for: A BAA that explicitly covers AI processing, commits to US-only data residency, includes a clear data retention and deletion policy, and names all subprocessors.

Step 2: Demand Clinical Validation Data

Vendor claims like "95% accuracy" or "saves 2 hours per day" are meaningless without context. Ask for the underlying data.

Questions to ask:

"What was your validation methodology?" The gold standard is a prospective study in a real clinical environment with physician reviewers. Most vendors use retrospective analysis on curated datasets, which inflates accuracy. If the vendor validated on their own training data, the number is worthless.

"What is your accuracy by specialty?" AI scribe accuracy varies dramatically by specialty. A tool that achieves 95% accuracy in primary care follow-ups may drop to 78% in complex cardiology consultations. Ask for specialty-specific data, particularly for your specialty.

"What is your hallucination rate?" This is the metric most vendors avoid. An AI scribe that's 94% accurate but hallucinating clinical findings 3% of the time is dangerous — those 3% errors could include fabricated exam findings, incorrect medication reconciliation, or made-up patient statements. Ask for the hallucination rate specifically, not just overall accuracy.

"Can I speak with three current customers in my specialty?" If the vendor can't connect you with satisfied users in your clinical context, that's informative. References from large health systems are less relevant if you're a 5-physician private practice.

Step 3: Understand the Integration Architecture

The most common source of AI tool failure isn't the AI — it's the integration. A brilliant AI engine that can't connect to your EHR is useless.

Integration models, ranked by reliability:

Questions to ask: "What happens when Epic/Cerner updates their API?" If the vendor doesn't have a clear answer, they'll break on the next EHR update. "What's your uptime SLA?" Healthcare needs 99.9% minimum. "What's the failover plan?" When the AI is down, what does the workflow look like?

Step 4: Analyze the Pricing Structure

Healthcare AI pricing is opaque by design. Vendors use different units — per provider, per encounter, per minute of audio, per API call — making comparison difficult.

Common pricing traps:

• •Per-encounter pricing that scales faster than value. A tool that costs $3 per encounter sounds cheap until you multiply by 25 encounters per day, 5 days per week, 50 weeks per year. That's $18,750 per provider per year. Does it actually save that much?
• •Annual commitments with 60-day cancellation windows. You sign a 2-year contract, discover the tool doesn't work for your specialty in month 3, and can't exit until month 24.
• •"Free" tiers that limit critical features. The free tier handles simple encounters. Complex encounters, the ones where you actually need help, require the premium tier.
• •Implementation fees that exceed the first year of licensing. Some vendors charge $10,000-$50,000 for "implementation and training" on top of recurring fees.

The ROI test: Calculate the actual time saved per provider per day in minutes. Multiply by your loaded cost per minute (total compensation divided by annual minutes worked). If the tool costs more than the time it saves, it's a bad deal regardless of how impressive the technology is.

Step 5: Check for Regulatory Readiness

The regulatory landscape for clinical AI is tightening. Tools that are compliant today may not be compliant in 12 months.

Key questions:

• •Is this tool classified as a medical device by the FDA? If it provides clinical decision support that physicians are not expected to independently review, it likely requires FDA clearance under the 21st Century Cures Act.
• •Does the vendor have a plan for the EU AI Act? Even if you're US-only, the EU AI Act is influencing US regulatory thinking. Vendors with EU compliance roadmaps are more likely to be ahead of US regulations.
• •How does the vendor handle state-specific AI disclosure requirements? California, Colorado, and Illinois have AI transparency laws that may apply to your patient interactions.

The Vendor Evaluation Scorecard

Score each vendor on a 1-5 scale across these dimensions:

• •BAA quality and coverage (1-5)
• •Clinical validation strength (1-5)
• •Integration reliability (1-5)
• •Pricing transparency and ROI (1-5)
• •Regulatory readiness (1-5)

Any score below 3 in BAA or clinical validation is a disqualifier. Total score below 18 means the vendor isn't ready for clinical deployment.

The AI healthcare market is growing 40% annually. Most of that growth is marketing budgets, not clinical value. Use this framework to find the vendors that are actually building tools worth your time and your patients' trust.