How to choose AI for your medical practice: a decision framework

Step 1: Define what you are actually buying

Most failed AI deployments fail at this step. "AI for medical practice" is not one thing. The practice needs to decide which workflow surface it is buying for:

These are different categories with different vendors. Most practices need a combination over time, not one platform that does everything badly. Start with the workflow surface that is most painful right now.

For most practices in 2026, that surface is patient-facing voice + scheduling + intake — the front desk. That is the receptionist replacement category, and it is what this guide focuses on.

Step 2: Audit your current state honestly

Before evaluating vendors, document where you are. This becomes the baseline against which to measure pilot results:

Call volume baseline

• Total inbound calls/day (and seasonal variation)
• % answered within 30 seconds
• % dropped to voicemail (especially after-hours)
• Avg call duration
• Top 5 call reasons by volume

Staffing baseline

• Current receptionist FTE count + loaded cost
• Turnover in past 24 months
• Time-to-fill for most recent receptionist hire
• Hours/week front-desk staff spends on tasks they should not be doing (insurance argument escalations, etc.)

Operational baseline

• No-show rate (and trend)
• Same-day add-on capacity utilization
• Recall hit rate (% of due patients who got their visit)
• Patient satisfaction score (CG-CAHPS or your equivalent)
• Average days to third-next-available appointment

You cannot measure success without these numbers. Most practices do not have them — gather them before vendor demos begin.

Step 3: Build a vendor shortlist

Aim for 3 vendor evaluations. Fewer than 3 and you are not comparing; more than 3 and decision fatigue stretches the timeline. The standard shortlist categories:

1. One reasoning AI platform with strong EHR integration (Claire is in this category)
2. One alternative reasoning AI platform with different strengths (Hyro for health systems, Hippocratic for clinical AI focus)
3. One human-led service as the floor/comparison (Smith.ai or a medical answering service) — even if you end up choosing AI, knowing the human-led cost/quality benchmark is informative

Add or substitute based on specialty. For dermatology, derm-specific evaluations include ModMed Phreesia integration. For OB/GYN, evaluations include practice-management voice tools. Match the shortlist to your practice context.

Step 4: Run structured demos

Demo discipline matters enormously. Ask all vendors the same set of questions, on the same scoring rubric. Otherwise the most polished demo wins regardless of fit.

Pre-demo checklist

• Send vendor your top 5 call types in advance — they should be ready to demo on YOUR workflow, not their canned script
• Have your EHR sandbox or test environment available — ask vendor to integrate during demo
• Have your clinical escalation protocol available — ask vendor to configure to it during demo
• Invite 2-3 stakeholders (practice administrator + clinical lead + maybe one front-desk lead)

During-demo rubric

Score each vendor on the criteria from the buying guide (EHR depth, HIPAA, clinical escalation, workflow depth, multilingual, voice quality, deployment time, pricing). 1-5 scale per criterion. Total score is the comparison output.

Post-demo follow-up

• Reference customer calls (2 per vendor minimum)
• BAA review by your compliance counsel
• Pilot terms negotiation

Step 5: Run a 30-day paid pilot

Paid pilots are the right structure. Free trials get the demo deck; paid pilots get vendor attention.

Structure:

• 30-day duration
• Limited scope (e.g., after-hours only, or one provider only) to reduce risk
• Clear success criteria: e.g., "after-hours call answer rate >80%, no-show recovery rate >40%, patient satisfaction unchanged or improved"
• Money-back clause if criteria not met
• Defined transition plan (whether pilot succeeds or fails)

Most practices that follow this structure can make a defensible decision by day 30. Most that skip the pilot end up with 12-month contracts they regret.

Step 6: Deploy, measure, iterate

After signing, the first 90 days determine whether the deployment becomes "amazing" or "we are stuck with this." Things that distinguish successful deployments:

• Weekly review cadence for the first 90 days with the vendor — what is working, what is not, what to tune
• Monthly metrics review against the baseline numbers from Step 2
• Staff involvement — the front-desk lead participating in tuning, not just being replaced
• Patient feedback loop — explicit patient satisfaction tracking around AI interactions
• Quarterly business review with the vendor — strategic improvements, new workflows, expansion

Vendors that do not show up for these cadences are vendors that will let your deployment decay. Push for the cadence; if they push back, that is information.