At the HLTH conference, I watched established market leaders execute their predictable playbook. As Agentic AI and sophisticated healthcare applications generated buzz, the incumbents circled their wagons.
They delivered their message: "Fear the startups. Fear the algorithms. Fear the disruption." They weaponized generic safety, privacy, and data quality concerns, valid issues, yes, but they deployed them transparently to preserve their immense investments in aging technology.
I've worked in healthcare innovation since 1998. This isn't new. It's the Incumbent's Playbook: Fear, Uncertainty, and Doubt (FUD). They've run this same play against every transformative shift for 25 years.
My Career Timeline: The Ghosts of Disruptions Past
Large, established companies struggle to retool billion-dollar platforms for new paradigms. The current AI fear simply manifests this fundamental business challenge. I've watched this pattern repeat at every stage of my career:
1. The .Com Era: Fear of the Digital Patient (1998 – Early 2000s)
I was part of the team that developed empower health, one of the earliest scalable care management solutions using .com technology to scale chronic disease management. Incumbents didn't resist the technology itself—they resisted trust and access. They claimed patients getting health information online would:
- Bypass their trusted physicians
- Misdiagnose themselves
- Destroy the hallowed "doctor-patient" relationship
The Reality: These platforms democratized care instead of destroying it. Today, 90% of hospitals offer patient portals, and 73% of patients access their health information online. These "dangerous" innovations became the foundation for appointment scheduling, health literacy, and patient engagement.
2. Mobile and Personalized Journeys (Mid-2010s to Present)
My team developed mobile health at Verizon Wireless and pioneered early AI at Onlife Health to craft hyper-personalized member journeys. Incumbents ran the same script: they warned about device security, data ownership, and algorithmic influence.
The Reality: The industry overcame every resistance point by building stronger, auditable, transparent solutions. Mobile health now reaches 90% of Americans through their smartphones, driving massive advancements in population health management and patient access. The digital health market reached $220 billion in 2024, proving the "dangerous" innovation delivered undeniable value.
The Incumbent's AI FUD Protects Yesterday's Revenue
HLTH didn't showcase genuine warnings about AI's future. It displayed desperate tactics protecting yesterday's revenue streams.
Legacy vendors invest decades and billions into platforms built on manual processes, closed data systems, and rigid architecture. They cannot simply "bolt on" modern AI. AI-native solutions—like the Agentic AI we pioneer at Grokker—fundamentally invalidate their core offerings.
FUD becomes their only recourse:
- Delay the Buyer: Slowing your purchasing decision by one year grants them another year of contract lock-in.
- Shift Focus from Value to Risk: They redirect conversations from "How much value delivers this solution?" to "How risky is this technology?"
- Exploit the Unknown: They leverage real but addressable concerns (bias, security) and inflate them to equation: New = Unsafe.
The Numbers Tell a Different Story
While incumbents spread fear, the data reveals opportunity:
- Healthcare AI market growth: Projected to reach $188 billion by 2030, growing at 37% annually
- Clinical error reduction: AI systems reduce diagnostic errors by up to 85% in radiology and pathology
- Administrative efficiency: AI automation saves healthcare organizations $150 billion annually in administrative costs
- Clinician burnout: 46% of physicians report burnout, largely from administrative burden—exactly what AI addresses
- Legacy system costs: Healthcare organizations waste $8.3 billion annually maintaining outdated IT systems
Choose Between Two Risks, Not Safety and Danger
Healthcare leaders face a choice between "AI Risk" (managed, auditable, constantly improving) and "Status Quo Risk" (pervasive, systemic, accepted):
|
Risk Category |
Status Quo (Legacy Systems) |
Agentic AI (Modern Solutions) |
|
Patient Safety |
Human error causes 250,000+ deaths annually in US hospitals (Johns Hopkins). Fatigue, manual processes, and diagnostic variance drive preventable harm. |
Algorithmic systems reduce diagnostic error rates by 85%. Explainable AI and human-in-the-loop validation mitigate risks while improving accuracy. |
|
Privacy |
Insider threats cause 58% of healthcare data breaches. Manual compliance fails, unsecured access persists, human error exposes data. |
Privacy-by-Design architecture, end-to-end encryption, and automated de-identification reduce breach risk by 95%. AI systems audit themselves continuously. |
|
Personalization |
"One-size-fits-all" programs achieve 12-18% engagement rates. Generic approaches fail patients and waste resources. |
Hyper-personalized journeys drive 60-75% engagement rates, improving clinical adherence by 40% and delivering measurably better outcomes. |
|
Efficiency |
Clinicians spend 2 hours on administrative tasks for every 1 hour of patient care. Manual workflows burn $1 trillion annually in waste. |
AI automation eliminates 70% of administrative burden, returning time to patient care and reducing operational costs by 30-40%. |
The Greatest Risk Lives in Inertia
The gravest threat to patient safety, clinical efficacy, and operational efficiency isn't AI—it's inertia. Organizations choose systems they know are broken because those systems feel familiar.
Consider this: Medical errors are the third leading cause in American deaths, ahead of car accidents, breast cancer, and AIDS. Manual processes, outdated systems, and human limitations drive this tragedy. Yet incumbents demand you fear the solution instead of the problem.
Retire the Incumbent's Playbook
Stop fearing AI. Start demanding responsible, transparent, audited AI that finally addresses the status quo's inherent risks.
The question isn't whether AI introduces risk. Every technology does. The question is: which risk profile serves your patients better?
Legacy systems guarantee continued failure at massive scale. AI-native solutions offer continuous improvement, transparency, and measurably better outcomes.
What risks are you solving for your organization?
Let's discuss a more responsible path forward with Agentic AI—one that acknowledges real concerns while embracing transformative opportunity.
The future doesn't wait for permission from the past.