It’s no secret that Medicaid & Medicare — a cornerstone of America’s health care safety net — is buckling under the weight of inefficiency, bureaucracy, and outright abuse. Fraud is expected. Waste is routine. And innovation, when it shows up at all, is too often treated with suspicion rather than urgency.
The public sees it. And so, increasingly, does the federal government. The recent creation of the Department of Government Efficiency — DOGE — by President Trump, with Elon Musk appointed as a special government employee, marks a new chapter in the national conversation about waste, fraud, and abuse. However unconventional the appointment, the mission is serious: identify systemic failures and drive accountability. And nowhere is the need more glaring than in Medicaid.
The question isn’t whether fraud exists — it’s how long we’ll keep pretending our current systems can catch it. The GAO admits there is at least $50.3B in Fraud, Waste and Abuse, potentially over $100B with Medicare included. The bigger question is whether CMS is getting the bang for the buck that it pays. Are patients getting better from year to year? I would conjecture to say no, but the scary fact is that CMS does not know what it does not know. CMS is very good at the carrot - rewarding administering companies but very POOR at the STICK - holding vendors and administrators accountable to the quality of care produced.
Artificial intelligence isn’t a future solution waiting in the wings. In health care, it’s already here — and already working. The real question is whether we’re ready to let it help.
As someone who has advised Fortune 500 companies, federal agencies, and international institutions on AI’s role in transforming care and curbing fraud, I see the impact daily, not in theory, but in practice. At DeLorean AI, one provider I’ve worked with used predictive models to flag individuals that had a high probability of hospitalization, not after the damage was done but in near real time. The result? A 27% reduction in unnecessary hospitalizations within 90 days - $250M cost avoidance to the CMS as well as healthier patients. In another instance, we identified a handful of providers responsible for an outsized share of suspicious claims, leading to targeted reviews and millions in prevented losses.
That kind of intervention isn’t just a technical achievement. It’s a policy necessity. If the technology exists to predict chronic disease onset and progression, then we as a society have a moral obligation to do so.
Right now, most Medicaid systems rely on static audits and outdated rules to detect fraud. It’s like fighting cybercrime with a filing cabinet. The pace and sophistication of bad actors demand tools that can adapt as quickly as the fraud evolves — and that’s exactly what AI, when used responsibly, can offer. Concomitantly, being able to predict which patients need what care before an acute event happens allows for extension of life, better quality of care as well as decreased costs. For example, saving the federal government $4B in hospitalizations for dialysis patients could occur within ninety days (90).
But we won’t get there without reform. Congress and the states need to modernize procurement rules to allow partnerships with AI and data science firms. They need to create regulatory sandboxes so innovations can be tested under oversight, not buried under bureaucracy. And they need to treat data as a public utility — protected but not paralyzed by fear of misuse.
Of course, the power of prediction comes with ethical risk. AI cannot be allowed to function as an engine of exclusion, denying people care based on biased assumptions or opaque models. We must be vigilant in building, deploying, and regulating these tools. But that’s an argument for better governance and enforcing current data privacy laws that are currently on the books, not for standing still.
As a data scientist who has served as a national policy advisor and consulted for organizations like the World Health Organization and the United Nations, I’ve seen what’s possible when governments act boldly — and what’s lost when they don’t. We’re at an inflection point. If DOGE is serious about its mandate, this is the moment to integrate AI not as a novelty but as a core part of reform.
Let’s not wait for another headline to remind us of what’s broken. The waste is real. The tools are ready. And the stakes are far too high to keep doing nothing. We have an opportunity to drive a better way to better care, driving more hugs for CMS members and patients.
Dr. MacLaughlin is a nationally recognized data scientist and blockchain strategist. He is also a trusted advisor to the United Nations (UN) and World Health Organization (WHO) on AI and blockchain's role in public policy and governance.
