# AI Readiness Assessment for Hospitals & Health Systems > Source: https://ibl.ai/solutions/hospital-health-systems/ai-readiness-assessment 5 Questions. 2 Minutes. ## Is Your Health System Ready for AI? Answer 5 quick questions and get a personalized AI readiness score for your health system. --- ### Question 1: Scale **How many staff need AI access across your facilities?** Total headcount who would use AI clinical, operational, and administrative tools. - **Under 500** — Single facility - **500 -- 2,000** — Small health system - **2,000 -- 10,000** — Regional health system - **10,000 -- 50,000** — Large health system - **50,000+** — Academic medical center or national system ### Question 2: Vendor **What's your current AI vendor situation?** Where your health system stands today with AI tools and platforms. - **No AI tools yet** — Starting from scratch - **Individual experiments** — Staff using personal AI accounts - **Single vendor** — One platform (DAX Copilot, Abridge, etc.) - **Multiple vendors** — Several tools across facilities ### Question 3: Concern **What's your biggest AI challenge?** The primary barrier your health system faces in scaling AI. - **Cost at scale** — Per-clinician licensing explodes across facilities - **HIPAA & Joint Commission** — PHI protection and accreditation compliance - **Vendor lock-in** — Tied to one provider's ecosystem - **Staff adoption** — Getting clinicians and staff to actually use AI tools ### Question 4: Deploy **Do you need on-premise deployment?** Some health systems require AI to run entirely within their own network. - **Yes, required** — PHI must stay in our network - **Preferred for compliance** — Joint Commission and HIPAA make it ideal - **Open to either** — Evaluating cloud vs. on-premise - **Cloud is fine** — SaaS deployment works for us ### Question 5: Timeline **What's your deployment timeline?** When do you need AI tools deployed across your facilities? - **This month** — Ready to start a pilot - **This quarter** — Within the next 90 days - **This year** — In the current fiscal year - **Just exploring** — Building a business case --- ### Your Results Your score out of 25 determines your readiness tier: **AI Pioneer (21 -- 25)** Your health system is ready to deploy AI at scale. You have the scale, urgency, and infrastructure awareness to move now. The biggest risk is waiting while competitors gain efficiency advantages. Recommended Next Steps: 1. Start a 30-day pilot with clinical and operational agents at one facility 2. Use the AI Cost Calculator to quantify TCO savings for your CFO 3. Schedule a technical architecture review for on-premise deployment **AI Ready (15 -- 20)** Strong foundation — ready to scale with the right platform. Your health system has clear AI needs and the maturity to execute. Addressing your top concern will unlock rapid system-wide deployment. Recommended Next Steps: 1. Run a single-facility pilot to build internal champions and prove ROI 2. Compare your current per-clinician vendor costs against ibl.ai flat-rate pricing 3. Engage clinical and IT leadership in a joint AI strategy session **AI Explorer (5 -- 14)** Early stage — but the opportunity is massive. You're building the case for AI at your health system. Starting with a focused pilot is the fastest way to prove value and get executive buy-in. Recommended Next Steps: 1. Start free with ibl.ai to demo AI agents to your leadership team 2. Identify one high-impact use case: nurse training, patient flow, or revenue cycle 3. Build a 1-page business case with our health system cost savings data --- ### Your Answers A summary of all your selections is displayed for review. **Calculate Your Savings** — Link to the AI Cost Calculator **Retake Assessment** — Start over --- ### Your Roadmap **Get Your Personalized Deployment Plan** Share a few details and our team will send you a custom AI deployment roadmap based on your assessment results. --- Trusted by 400+ institutions, 1.6M+ users University of Colorado | Columbia University | IBM | Kaplan | SUNY --- *[View on ibl.ai](https://ibl.ai/solutions/hospital-health-systems/ai-readiness-assessment)*