HelloAI Executive
For decision makers and executives in healthcareThirteen short, self-paced courses on AI strategy, ownership, governance, the law, value and adoption. Coming soon.
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Why this module exists.
Adoption has outrun leadership. In a 2025 physician survey, 67% used AI in daily practice, yet 71% had little or no say in which tools their organization deploys.1 A review of 92 studies names inadequate leadership support among the top organizational barriers to healthcare AI.2
Built for the people who lead AI.
AI is already running across your organization, often with no one accountable: EHR risk scores, ambient scribes, imaging triage, and shadow tools staff use through personal accounts. The technology arrived ahead of the leadership. HelloAI Executive is built for the decision makers who have to catch up. It teaches leadership, with no coding: strategy, ownership, governance, ROI, and sustainable adoption across a health system.
Self-paced, about 7 hours
13 courses, 81 units
Strategy, governance, and ROI
Thirteen courses, from seeing the field to leading it.
Each course is short, self-paced, and grounded in 2026 evidence and real health-system case studies. Open any course to see what it covers.
01Start
The Executive Playbook
Where the module takes you: the board packet you build course by course, and a readiness pulse that shows where your organization stands today.
- What you'll build
- AI leadership readiness pulse
02Landscape
The AI Landscape in 2026
What AI in healthcare actually is right now, what is still hype, and the two shifts, multimodal and agentic, that change the next procurement wave.
- AI is already running in your organization
- What is real, what is hype
- The two shifts: multimodal and agentic
03Leadership
The Inflection Point: Why AI Is a Leadership Problem
AI has moved past pilots. This is the case for treating it as a leadership responsibility that sits above IT.
- The tool trap
- The digital leader's operating lens
- Build the leadership system around AI
- You cannot outsource transformation
04Strategy
The AI Strategy Loop
Vision, Impact, Risk, Adoption (VIRA). The spine of an executive AI strategy, run as a loop rather than started in the middle.
- Vision: the north star
- Impact: proving value
- Risk: governing across the lifecycle
- Adoption: from plan to practice
05Readiness
Data and Infrastructure: Is Your Organization AI-Ready?
Is your organization actually AI-ready? The data, integration, and infrastructure questions to answer before you buy.
- AI is only as good as the data under it
- The five layers of an AI-ready data foundation
- Build, platform, or point solution: own the layer that matters
- Build your AI-readiness audit
06People
The 10-20-70 Rule: Transformation Is Mostly People
Successful AI is 10% algorithms, 20% technology and data, and 70% people and process. Why most transformations fail, and what the leaders do differently.
- Why the 70% is where it is won or lost
- From human-in-the-loop to human-in-the-lead
- Five ways the 70% kills a project
- Where the freed capacity goes
07Ownership
Who Owns AI: Operating Models and the CAIO
Operating models and the Chief AI Officer. Which ownership model fits your organization, with the cases that ran each one.
- Shared ownership and the CAIO
- The three operating models
- From automation to orchestration
- The board's own job
08Governance
The AI Governance Operating Model
The PPTO model across the AI lifecycle. Risk-based governance that covers the tools that flag and the agents that act.
- Govern by risk, not uniformly
- The governance operating model (PPTO)
- Who sits on the committee, and who decides
- Govern across the lifecycle
- Keeping it alive: monitoring, drift, and decommissioning
09Oversight
Where Oversight Quietly Fails
The risks a sound governance plan can still miss: human review that can’t keep up, harm that never looks like an error, AI use your committee never approved, and security failures that reach patients.
- The limits of human oversight
- The harm that does not look like failure
- The iceberg below your governance
- When your patients bring their own AI
- Cybersecurity as a patient safety risk
10Law
AI, the Law, and Your Patients
Where the legal exposure from AI sits today, which US, EU and UK rules reach which tools, and what to tell patients and when. It isn’t legal advice.
- Telling patients about AI
- Where the legal exposure sits
- Know which rules reach which tool
- If you operate in the EU or the UK
11Value
From Priorities to Proof: ROI and Reimbursement
ROI, the value curve, and the reimbursement reality. How to prove value and defend the budget past year one.
- Choose first bets by value mechanism
- The 4% problem
- What the 4% built
- Ask for the denominator
- Read the study, not the headline
12Adoption
AI Fluency, Readiness, and Leading the Change
Building the skills and the trust to lead the change, and reading whether your organization is actually ready to move.
- Fluency fuels trust, adoption, and ROI
- A tiered approach to fluency
- Readiness and leading the change
13Deployment
From Decision to Deployment
Crossing the pilot-to-scale gap without stalling, then the capstone: your playbook pulled together into one board packet.
- Gate before you build
- Pilot, then cross the valley
- A plan, not a launch date
- Capstone: your board packet
By the end, you'll be able to:
- Design a healthcare AI strategy using a four-part framework: vision, impact, risk, and adoption.
- Compare centralized, federated, and hub-and-spoke operating models and assign clear ownership for AI in your organization.
- Apply a risk-based governance model across the full AI lifecycle, from problem definition through post-deployment monitoring.
- Find where oversight quietly fails, know which rules reach which tool, and decide what to tell patients about AI.
- Measure AI ROI across three dimensions: clinical outcomes, workforce outcomes, and financial outcomes.
- Plan and protect budgets through the 2-3 year ROI value curve, beyond year-one expectations.
- Evaluate build, buy, or blend procurement decisions and contract for measurable performance.
- Drive adoption by engaging clinicians early, building AI fluency across the workforce, and managing change at scale.
A playbook you take back to your institution.
Every course after the opening one ends with an Apply this step you run against your own organization. You finish with a working leadership playbook, pulled together into a board packet in the last course.
A starting AI inventory
Every AI tool already running in your system, where it sits, who owns it, and whether anyone governs it.
A board-ready question set
The diagnostic questions to put on your next leadership and board agenda, with the reasoning behind each.
An honest readiness read
Where you stand on strategy, ownership, governance, and readiness, with the gaps named plainly.
A go / no-go discipline
How to decide what to deploy, plus a Safe AI Plan to keep it safe, used, and worth its cost after launch.
Frameworks you’ll walk away using.
A certificate that stays current.
Finish the module to earn a HelloAI Certificate of Completion, signed by HelloAI partner institutions. It is valid for 12 months and renewable with a short recertification check, so it keeps pace with a field that changes monthly.
It is a Certificate of Completion. It is not accredited for CME, CPD, or CE.
A leadership module, coming soon.
HelloAI Foundations, Student, and Professional are available to the public at no cost. HelloAI Executive goes deeper, for the people leading AI across a health system.
It runs as a self-paced module, like the others. Health systems that want it delivered in person can run it as a workshop instead. Talk to us and we'll scope it with you.
Join the waitlist to be first in line when it opens, and to help shape it.
Sign in to join the waitlist