6 things Medicaid stakeholders can remind the world to always do with healthcare AI
U.S. healthcare will know it’s gotten AI right when the technology demonstrably improves care access, attentiveness and outcomes for the least financially healthy among us.
That goal is within reach, according to report published March 24 by Cityblock Health, a provider organization based in New York City and serving Medicaid enrollees in seven states plus Washington, D.C.
“If we as leaders and innovators can get this right, Medicaid can be the proving ground for effective and responsible AI in healthcare,” writes Cityblock CEO Toyin Ajayi, MD, in introducing the report, Medicaid + AI: A New Standard for Innovation.
“We can show that the latest and greatest technologies can serve the most vulnerable among us,” Ajayi adds. “We can build a healthcare system that is made more efficient by being more human and compassionate.”
Cityblock Health currently serves more than 100,000 members, partnering with national and regional Medicaid health plans and health systems.
Aiming to guide anyone involved in deploying AI for any swath of the nation’s 90 million Medicaid enrollees, the report’s authors offer six pointers. What these imperatives all have in common is a focus on “putting the people who rely on Medicaid and their care teams at the center of [AI] design and development.”
1. Prioritize equity first and always.
Equity is the objective, not a guiding principle or an afterthought.
“Any AI tools that the industry builds must start by identifying who the system leaves behind and be designed to reach them,” Cityblock writes. “That requires proactive bias testing, representative data and programmatic approaches that prioritize historically excluded groups.”
2. Solve the most pressing problems first.
Trust is earned by easing what hurts now.
“Start with the problems that are known to cause immediate harm,” the authors write. “Quick wins that demonstrably eliminate or reduce pain points will open the floodgates for broader system innovation.”
3. Put trust before data.
Data without trust is noise.
“Build systems that preserve and deepen human relationships rather than substituting for them,” Cityblock urges. “Privacy, consent and clear explanations of how data will be used are non-negotiable. Trust must be earned before models act on behalf of clinicians or members.”
4. Treat AI as a relationship engine.
AI should stitch together fragmented care experiences into continuous and meaningful relationships and desired behaviors.
“The goal is to make every touchpoint in the care journey reinforce trust, improve engagement and encourage progress—from the first outreach call to long-term chronic disease management.”
5. See behavior change as the goal.
Success is measured not in model accuracy alone but in changed behavior and improved outcomes.
“Design AI to nudge, coach and support sustainable behavior change,” the authors write. “Achievable, human-centered interventions stack over time to become previously unthinkable transformations.”
6. Memorize this equation: Human + AI = Scalable Compassion.
Technology should scale empathy, not substitute for it.
“AI should handle repetitive tasks and surface insights so human teams can do what machines cannot: listen, analyze and treat with dignity.”
Dave P. has worked in journalism, marketing and public relations for more than 30 years, frequently concentrating on hospitals, healthcare technology and Catholic communications. He has also specialized in fundraising communications, ghostwriting for CEOs of local, national and global charities, nonprofits and foundations.