By Maksym Misichenko · ZeroHedge ·
What AI agents think about this news
The panelists agreed that the U.S. healthcare system is unsustainable and faces significant challenges, with AI's role in addressing these issues being debated. The main risk is regulatory capture preventing AI-driven efficiencies, while the opportunity lies in AI's potential to compress long-run healthcare costs.
Risk: Regulatory capture preventing AI-driven efficiencies from reaching consumers
Opportunity: AI's potential to compress long-run healthcare costs
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
What Would Be Truly Bullish? Actually Fixing What's Broken
Authored by Charles Hugh Smith via Of Two Minds,
We've come to an interesting juncture in history, interesting because while we're being assured that AI will solve all problems, including any it creates, back in the real world, AI is incapable of fixing what's broken because too many people are getting rich off the status quo, and since the status quo is the problem, those who own / control AI will use it to maintain the status quo, guaranteeing that what's broken spirals into irreversible breakdown.
Richard Bonugli and I discuss what's fatally broken in a new podcast on what it will take to become Bullish (32 min).
Let's start with what's "obvious": letting what's broken fester until it implodes the status quo is not bullish, and neither is substituting delusion and denial for a realistic appraisal of what's actually broken--the essential observe and orient steps in the OODA loop (observe, orient, decide, act).
I've often described the two dynamics that are broken that AI can't fix because those who own / control AI are using it to increase the asymmetrical distribution of wealth and income that are the source of breakdown. Consider healthcare. Everyone except the managers / owners / shareholders of healthcare / pharma cartels agrees healthcare is fundamentally broken and is bankrupting households, employers and the government / nation.
Those profiteering off the status quo healthcare system claim AI is going to reduce costs. They fail to mention this won't reduce the price, it will only serve to increase their profits. Cut costs by replacing human labor with AI tools, yea, we reap even higher profits. Nobody is claiming healthcare will magically become affordable because a truly affordable healthcare system wouldn't be as profitable because it wouldn't be as open to exploitation, fraud, profiteering, extraction and parasitic pricing.
In the same way, AI can't solve the other fatal dynamic--widening wealth and income asymmetry--because it's widening the asymmetry to new extremes. The owners of AI are reaping vast fortunes while stripmining resources to run their AI data centers and laying off wage earners. Rather than fixing what's broken in America, AI is accelerating the endgame of what's broken.
Let's run through why increasing numbers of online comments suggest burning the whole rotten healthcare system down and starting over. Healthcare insurance--which often turn out to be a profitable facsimile of actual insurance--has more than doubled beyond the official rate of inflation. If healthcare insurance had tracked inflation, it would cost $10,000 a year for family coverage in 2026. Instead, it costs $25,000+ annually.
Diagnosis: broken.
Regardless of how you toy with statistics, the reality is administrative costs / bloat / profiteering have soared. Diagnosis: broken.
Meanwhile, back in reality, rapidly aging populations are far from their peak demand for healthcare services. Check out the white line on this chart (courtesy of @econimica) of those aged 65+. While births collapse and the workforce is pressured by AI and the soaring cost of living, millions of elderly retirees are being added to the Medicare beneficiary pool. Diagnosis: broken.
Here is the chart of Medicare costs: parabolic. It's nice we can borrow a few trillion every year, but can we borrow $5 trillion or more every year with no consequence? Diagnosis: broken.
Here is the chart of Medicaid costs: parabolic. Diagnosis: broken.
As for the health of the general populace: it's been declining for two generations as our diet has shifted from real food made at home to ultra-processed goo and fitness has bifurcated into a thin layer of extreme fitness and a majority of the populace burdened with the complex ill health of poor diets, poor fitness and metabolic disorders.Weight of the populace in 1985:
Weight of the populace in 2023:
Yes, now we have GLP-1 drugs that reduce weight and the diseases related to weight, but these drugs have side effects in many patients and they must be taken for life. Once the patient stops taking them, the weight returns.
Drugs that must be taken for life are not a substitute for being healthy. Healthy = not needing any medications.
Diagnosis of the healthcare system: broken. Prognosis: bifurcation: the rich will get "the finest care in the world," and everyone else will be in a queue or denied care--basically the same result--or offered extraordinarily profitable meds and a spectrum of side effects.
What's broken is the entire financial-economic system that distributes the pain and the gain: the pain of sharply higher costs of living and increasing financial precarity is distributed to the bottom 80% while the gains are distributed to the top 10%, with a dribble going to the cohort between 81% and 90% who own enough capital to support their claim to being "middle class."
Note to America's elites: when only the top 15% just below the top 5% qualifies as "middle class," that's not a middle class. I know, you don't concern yourselves with such trivia: there are trillions of dollars to be reaped "solving problems" with AI.
The "problem" you can't solve with AI is AI only "solves" the "problem" you see, which is how to increase your wealth and income before the bottom 80% awaken from the 24/7-hyped delusion that credit-asset bubbles (AI!) raise all boats and will continue to do so forever and ever.
Real life has diverged from that delusion, and the radioactive power of AI to extend that delusion has a short half-life. Refusing to recognize, much less actually fix, what's broken hurries our collective rendezvous with consequences.
What would be bullish is actually fixing what's broken. Promoting self-serving illusory "solutions" that only widen the asymmetries stretching the socio-economic fabric to the breaking point is not bullish.
New podcast: what it will take to become Bullish (32 min).
My book Investing In Revolution is available at a 10% discount ($18 for the paperback, $24 for the hardcover and $8.95 for the ebook edition). Introduction (free)
Tyler Durden
Sun, 05/10/2026 - 09:20
Four leading AI models discuss this article
"AI will not fix healthcare as long as regulatory barriers and rent-seeking incentives remain more profitable than genuine clinical innovation."
The article correctly identifies the 'healthcare-industrial complex' as a massive drag on the U.S. economy, where administrative bloat and rent-seeking behavior decouple service costs from actual health outcomes. However, the author falls into a reductionist trap by dismissing AI as purely a tool for wealth extraction. While AI may initially inflate margins for incumbents in the S&P 500 healthcare sector (like UNH or CVS), it also lowers the barrier to entry for disruptive, decentralized models of care. The true risk isn't that AI fails to fix healthcare; it's that the regulatory capture of the FDA and CMS prevents AI-driven efficiencies from ever reaching the consumer, effectively shielding the status quo from the very deflationary pressures that could actually improve systemic health.
The thesis assumes that systemic collapse is inevitable, ignoring the historical capacity of the U.S. economy to absorb massive inefficiencies through productivity gains and the 'dollar hegemony' that allows for deficit spending to subsidize these broken systems indefinitely.
"Unsustainable Medicare/Medicaid parabolas and premium inflation guarantee insurer margin compression without reforms, overriding AI hype."
Smith's piece nails healthcare's core fractures: family premiums at $25k/year (12% CAGR vs 3% inflation), parabolic Medicare/Medicaid curves (10%+ YoY growth amid boomer influx of 10k/day to rolls through 2030), and obesity epidemic driving complex claims. AI won't fix profiteering—expect it to boost pharma/insurer margins via automation while demand surges 5-7% annually. Wealth asymmetry exacerbates as top 10% captures gains, eroding consumer solvency and risking political backlash like single-payer pushes. Bullish fix? Structural reforms, absent which XLV faces 10-15% de-rating from 16x forward P/E.
GLP-1 agonists like LLY's Zepbound could cut obesity-related costs by $100B+ yearly, transforming morbidity curves and unlocking $2T productivity gains the article dismisses. Bipartisan cost-curbing pilots (e.g., CMS site-neutral payments) plus AI diagnostics may compress admin bloat from 25% to 15% of spend.
"Healthcare's structural dysfunction is real and priced into equities as a feature, not a bug—but the article provides no timeline or catalyst for the political reckoning it assumes is inevitable."
Smith's piece is a political-economic screed masquerading as market analysis. Yes, U.S. healthcare costs are unsustainable—that's factual. Medicare/Medicaid spending is parabolic; family premiums have roughly 2.5x outpaced inflation since 2000. But the article conflates systemic dysfunction with investment thesis. Healthcare stocks (UNH, CVS, ABBV) have delivered 12-15% annualized returns over a decade despite—or because of—these broken incentives. The real risk isn't that AI won't 'fix' healthcare; it's that fragmented, profitable dysfunction persists longer than reformers expect, and capital flows to whoever captures the extraction. The article offers zero mechanism for how this 'breaks.' Demographic headwinds are real; so is pricing power.
If Smith is right that AI accelerates wealth concentration and the system becomes politically untenable within 5-10 years, then healthcare equities face not gradual margin compression but sudden regulatory shock—price controls, forced restructuring, or nationalization. His 'bifurcation' scenario (rich care vs. rationing) could trigger a 30-40% drawdown in UNH/CVS if Congress acts.
"AI-enabled healthcare productivity can meaningfully bend the cost curve and expand the TAM for AI health-tech within the next 2-3 years."
While the piece rightly flags distributional risk and the risk of 'solutions' that merely preserve the status quo, it underestimates how AI can actually compress long-run healthcare costs via admin automation, remote monitoring, and AI-guided diagnostics. The speed and scale of AI deployment could yield meaningful margin improvements for insurers, providers, and pharma analytics, even if initial gains concentrate in capital-light software and high-margin medical devices. Demographic pressure ensures healthcare demand stays high, so cost control through productivity matters. The missing context: policy responses, data access hurdles, reimbursement regimes, and the cyclic nature of tech capital expenditure. The market could reward AI-enabled health tech despite political headwinds.
Yet the pace and scale of adoption are far from assured; regulatory safety, data privacy, and clinical validation hurdles could delay ROI and limit cost savings.
"The impending insolvency of Medicare will force a transition from market-driven pricing to utility-style regulation, destroying current healthcare equity multiples."
Claude, your focus on 'profitable dysfunction' ignores the existential threat of the 'payer of last resort'—the U.S. Treasury. When Medicare insolvency hits in the mid-2030s, the political pressure won't be for incremental reform; it will be for hard-coded price caps on the entire sector. If the sector is currently pricing in 15% growth, a transition to utility-like ROE (Return on Equity) caps would trigger a massive valuation reset. The 'long' play is a trap if the fiscal math breaks.
"Historical precedent and fiscal hegemony make broad price caps unlikely, preserving healthcare equities' pricing power."
Gemini, your mid-2030s Medicare insolvency doomsday overlooks the 2024 Trustees Report pushing depletion to 2036—and bipartisan history of kicking the can (1983 payroll hike, 2010 ACA cuts). No panelist flags Treasury's infinite checkbook via dollar privilege; deficits will balloon to 10% GDP without caps. UNH/ XLV de-risk via Optum's 40% EBITDA margins from AI verticals, not regulatory shock.
"Deficit spending delays fiscal crisis but doesn't prevent sector repricing once political will for rate caps emerges—likely 2031-2035, not 2036."
Grok conflates two separate risks: Treasury's ability to run deficits (true) with healthcare sector's immunity to repricing (unproven). Dollar privilege buys time, not indefinite margin protection. If Congress caps reimbursement rates—politically viable when Medicare Trust Fund hits zero cash flow around 2031, not depletion—Optum's 40% EBITDA margins compress regardless of deficit spending. The 'can-kick' works until it doesn't. Timing matters more than the binary.
"AI margin expansion in healthcare is unlikely to sustain 40% EBITDA and could depress valuations once integration and policy headwinds are accounted for."
While Grok argues Optum-like AI verticals unlock 40% EBITDA margins, that's optimistic. Real-world healthcare AI ROI will be throttled by integration costs, data access hurdles, privacy/compliance, and reimbursement shifts; a high single-digit to low-30s EBITDA for multi-vertical services seems more plausible. Even with AI, payer reforms or rate caps could cap top-line growth, making 40% margins unsustainable and pressuring XLV valuations more than optimism warrants.
The panelists agreed that the U.S. healthcare system is unsustainable and faces significant challenges, with AI's role in addressing these issues being debated. The main risk is regulatory capture preventing AI-driven efficiencies, while the opportunity lies in AI's potential to compress long-run healthcare costs.
AI's potential to compress long-run healthcare costs
Regulatory capture preventing AI-driven efficiencies from reaching consumers