Recently, I had the privilege of attending the AI HealthRush™ 2 Symposium in Miami, hosted by the Miami AI Club™. This event focused entirely on the application of Artificial Intelligence (AI or GenAI) in healthcare. I was also honored to attend the first AI HealthRush™ in September 2023 (link to full video below). Looking back, it feels like a decade ago. We all know about “dog years”—maybe it’s time we coined “AI years.” If I had to guess, an “AI year” is about 90 Earth days long… or maybe even shorter.
We’ve all heard of Moore’s Law by now. For those who haven’t (or just need a refresher), Moore’s Law was proposed by Intel® co-founder Gordon Moore in 1965. It predicted that the number of transistors on a microchip would double approximately every two years, leading to exponential gains in computing power and dramatic reductions in cost. While not a physical law, this prediction has largely held true for decades—fueling advancements across tech, and now, in AI. But the pace of AI may be outgrowing even Moore’s Law. The Wikipedia® chart below illustrates this progression through 2020.
AI’s Speed: Not Just Accelerating—Compounding
At the AI HealthRush 2 Symposium, the conversation centered on the remarkable progress AI has made—not just in theory, but in real-world impact. One standout example came from research at Florida International University (FIU), where AI is being used to identify compounds that can reduce tumors. And it works.
Today, AI is proving most valuable in areas like imaging, pathology, and genetics. But speakers also highlighted a major challenge: the difficulty in legally accessing HIPAA-protected patient health information (PHI). From inside the healthcare system, this issue looks very different than it does from the outside. The system is deeply siloed—and that complicates everything.
Back to the concept of “AI years”: by some estimates, the effective use of AI is doubling every 3 to 6 months. That’s 4 to 8 times faster than what Moore’s Law projected.
Bessemer’s Healthcare AI Adoption Index
A few weeks ago, Bessemer Venture Partners®, along with AWS® and Bain & Company®, released the Healthcare AI Adoption Index. As they put it: “We partnered with AWS and Bain & Company to learn from 400+ healthcare buyers on what’s driving AI experimentation—from proof-of-concept to production—and how this will impact startups and innovation partners.”
They say AI adoption is now “unfolding at warp speed.” To provide context, they compared this wave to the adoption of Electronic Health Records (EHRs). EHRs laid the groundwork for today’s AI data opportunity—but the rollout was expensive, bureaucratic, and slow. We were there. Now, with more than 500 EHR systems and over 3,000 exabytes of data, most of which large language models (LLMs) can’t and shouldn’t access, the landscape remains fragmented.
One strength of Bessemer’s report is that it draws insight from 400 leaders across payer, pharma, and provider sectors. I do wish they had included patient voices—but perhaps that’s the next phase of their research.
Their findings reveal a wave of internal and external GenAI proof-of-concept (POC) projects across the industry. Yet, only 30% of completed POCs make it into production.
The Key Challenges
The report outlines several major barriers to AI adoption:
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Security concerns (HIPAA compliance and cybersecurity)
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Lack of in-house expertise
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High integration costs (especially for payers)
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Difficulty in preparing AI-ready data
Each of these concerns affects about half of all respondents across payers, providers, and pharma. On top of that, AI is expensive—and the healthcare industry is highly risk-averse. Quality control and reputational risk must also be factored in.
We’ll dive deeper into this report and others in future posts. But one thing is clear: for sectors beyond payer, pharma, and provider, AI adoption will continue to face resistance from within the healthcare system.
What If the Consumer Were in Charge?
Here’s something many don’t realize: U.S. doctors are generally very well trained. I’ve seen how rigorous their education and preparation is. But about 70% of doctors are specialists. Even if you include primary care—family medicine, internal medicine, pediatrics, and, depending on the definition, OB/GYN—the majority of providers are highly focused. A pediatric pulmonologist, for example, probably doesn’t rely on AI daily. They might experiment with tools like OpenEvidence™, but they know their field inside out.
But what if consumers—who aren’t bound by HIPAA the way institutions are, yet suffer from those data silos—had full control?
Imagine a patient with their own Universal Health Record™ (UHR), powered by a specialized healthcare-only Special Language Model (SLM). They could review real-time health data, receive alerts on drug interactions, track open issues, and share data with trusted family members. That’s when AI begins to truly empower and improve personal health outcomes.
Consider this: The Wall Street Journal® has reported that insurance companies are already using AI to deny claims. Meanwhile, 850 million claims for care, services, or medications are denied every year—and less than 2% of consumers appeal.
Now imagine if every patient had an AI tool to help them draft an appeal letter, complete with clinical justification and research. How many more appeals would succeed?
How many of you reading this have had a claim denied in the past year or two—for yourself or a loved one? I know I have. Everyone I know personally has too.
Now you see why AI might ultimately be most powerful when it represents the consumer.
About HealthScoreAI ™
Healthcare is at a tipping point, and HealthScoreAI (HSAI) is positioning to revolutionize the industry by giving Consumers control over their health data and unlocking its immense value. U.S. healthcare annual spending has exceeded $5 trillion with little improvement in outcomes. Despite advances, technology has failed to reduce costs or improve care. Meanwhile, 3,000 exabytes of Consumer health data remain trapped in fragmented USA system of 500 EHRs, leaving Consumers and doctors without a complete picture of care.
HealthScoreAI seeks to provide a unique solution, acting as a data surrogate for Consumers and offering an unbiased holistic view of their health. With over 850 million medical claims denied annually in the U.S., HSAI intends on giving Consumers practical tools to respond to denial of care by insurers. We aim to bridge the gaps in healthcare access and outcomes. By monetizing de-identified data, HealthScoreAI seeks to share revenue with Consumers, potentially creating a new $100 billion market value opportunity. With near-universal EHR adoption in the USA, and advances in technology, now is the perfect time to capitalize on the data available, practical use of AI and the empowering of Consumers, in particular the 13,000 tech savvy baby boomers turning 65 every single day and entering the Medicare system for the first time. Our team, with deep healthcare and tech expertise, holds U.S. patents and a proven track record of scaling companies and leading them to IPO.
Noel J. Guillama-Alvarez
https://www.linkedin.com/in/nguillama/
+1-561-904-9477, Ext 355
https://youtu.be/ZBK6iEBezH8?si=ZKpJzIIBeKPXoWow
https://en.wikipedia.org/wiki/Moore%27s_law
https://en.wikipedia.org/wiki/Health_Insurance_Portability_and_Accountability_Act
https://www.bvp.com/atlas/the-healthcare-ai-adoption-index#Introducing-the-AI-Dx-Index