From the desk of Scott Covert  |  AI-Stocks Intelligence  |  April 2026

AI Isn't Just Changing the Stock Market.
It's Reshuffling Every Industry on Earth.

And the Tools Most Analysts Use Weren't Built for This.

I built something that is. Here's the story.

Dear Friend,

Let me say something that might surprise you, coming from a guy who's about to sell you an investment research report:

Most Wall Street analysts are smarter than me.

I mean that. Many of them have 20 IQ points on me, easy. They have Harvard MBAs. They have Bloomberg terminals that cost $24,000 a year. They have teams of researchers, decades of experience, and institutional knowledge that I will never match.

And yet...

In 2024, three of the most respected analysts in the world got spectacularly, publicly, career-damagingly wrong about what was happening in the market.

Not because they were stupid.

Because their tools weren't built for what's happening right now.

Three Brilliant Analysts. Three Spectacular Misses.

Now here's what I want you to understand:

I am not calling these people dumb. They are, by any measure, among the sharpest analytical minds in finance. Kolanovic was one of JPMorgan's most senior strategists. Wilson is one of the most-watched voices on Wall Street. Ferragu built his career on semiconductor analysis.

So what went wrong?

They're Using Rearview Mirrors to Navigate a New Road

Here's the structural problem, and it's not their fault:

Wall Street analysts are evaluated on 12-month price targets. Their bosses want quarterly earnings estimates. Their clients want to know what happens before the next fund rebalancing cycle. They're built to look 1 year out, max.

Their models are calibrated on historical patterns — interest rate cycles, earnings multiples, sector rotation data going back decades. Mean reversion. Regression to trend. The stuff that worked brilliantly for 50 years.

And then AI showed up.

Not as a product to analyze. As a force that changes how every other product, company, and industry works.

Kolanovic's quant framework couldn't account for AI as a deflationary force that extended the economic cycle. Wilson's valuation models flagged AI stocks as "overvalued" because they weighed P/E ratios — but AI capex creates its own demand in a self-reinforcing loop that traditional metrics label as a bubble. Ferragu applied the semiconductor cycle framework (demand peaks, supply catches up, margins compress) to an infrastructure buildout that doesn't follow semiconductor cycles at all — it follows a curve more like the internet backbone buildout of the late 1990s.

Same tools. Same frameworks. Same institutional pressures.

Completely different era.

And here's the part that really matters for your portfolio:

AI doesn't just give us better tools to analyze industries. AI is the reason those industries are reshuffling in the first place. The same technology that lets me build a cross-sector analysis engine is the technology that's rewriting the economics of every business on Earth.

The tool and the disruption are the same thing.

That's what I built my engine around.

What I Built (And Why It Starts With 25 28 Industries)

Over the last 8 months, I built a proprietary engine that models how AI redistributes the relative value of 28 industries across five timeframes: 1 year, 2 years, 3 years, 5 years, and 10 years.

Why 28? Because the standard 25-industry model that Wall Street uses lumps together businesses that AI affects in completely opposite ways.

Take semiconductors. TSMC builds the physical chips. Billion-dollar factories. The constraint is the laws of physics. Three to four years to build one new plant.

NVIDIA designs the architecture of those chips — using AI to design AI chips. Pure intellectual property. Software-like margins. NVIDIA is now 20 times more valuable than IBM was in 1985, with one-tenth the employees.

Treating those as "the same industry" is like averaging a sprinter and a marathon runner and calling the result useful.

So we split three industries into six:

• Semiconductors became Chip Foundries (TSMC, ASML) + Chip Designers (NVIDIA, AMD, Broadcom)
• Software/Cloud became Cloud Platforms (AWS, Azure, GCP) + Enterprise SaaS (Salesforce, ServiceNow, Palantir)
• Pharma/Biotech became Big Pharma (Pfizer, Roche) + Biotech-AI (Recursion, Insilico — companies born with AI at their core)

25 became 28. A small change that produced dramatically different investment conclusions.

Then we mapped 167 cross-sector cascade effects — the specific, documented mechanisms by which AI adoption in one industry ripples into others.

And then I wrote it all down in a book that any self-directed investor can read and use immediately.

Introducing: The 28-Sector AI Playbook

This is a 23,000+ word research report that covers every industry AI will touch — and explains exactly what AI does to each one, when it hits, and what it means for stock valuations.

For each of the 28 industries, you get:

• The One-Sentence Verdict — where this industry lands in the AI revolution, in plain English
• What AI Actually Does Here — specific use cases with real companies, real applications, real numbers. Not "AI improves efficiency" hand-waving.
• The Bull Case — why this sector could outperform, with specific data
• The Bear Case — what could go wrong, with honest specifics. (Most research conveniently leaves this part out.)
• The Labor Impact — what percentage of work is cognitive, routine, and physical... what gets automated... and the projected margin impact in percentage points
• Cross-Sector Connections — how this industry's AI adoption affects 3-5 other industries in ways nobody talks about
• Year-by-Year Timeline — what happens at 1 year, 3 years, 5 years, and 10 years
• The Bottom Line — a clear, memorable conclusion you can act on

The 167 Cross-Effects That Change Everything

This is the part that tends to change how people think about their portfolio.

Most analysis looks at each industry in isolation. "AI is good for software. AI is bad for media." End of story.

That's like saying a hurricane only affects the beach it hits.

In reality, every AI disruption in one industry cascades into others. Our engine maps 167 of these connections. Here are some that will make you rethink your holdings:

• When AI transforms insurance companies' ability to price risk in real time, that directly reshapes the auto industry — because usage-based insurance shifts vehicle value away from brand prestige toward real-time safety data
• When AI-powered retail media networks capture advertising dollars that used to flow to television, that's not a retail story OR a media story. It's both. Simultaneously.
• The only pair in our entire 167-effect matrix that scores a perfect 1.0 strength: Semiconductors to Cloud Platforms. Hardware breakthroughs in computing power per watt directly enable the shift from static software to AI that acts on its own.
• AI cures for chronic disease could devastate hospital revenue — because hospitals make money from sick people, not healthy ones
• The most valuable real estate asset in 2030 may be a power line, not a building — because AI data centers consume 10+ megawatts each, and land with guaranteed power access is becoming the scarce resource
• Cloud platforms don't just help banks — they destroy professional services. AI agents automate legal, accounting, and consulting tasks, devaluing the human-hour billing model that generates $200 billion a year

You cannot make intelligent investment decisions without understanding these connections.

And this is exactly where traditional analysis falls short. The analysts aren't tracking cross-sector cascades because their coverage is siloed: the semiconductor analyst covers semiconductors, the healthcare analyst covers healthcare. Nobody's job is to model how a chip breakthrough in Taiwan reshapes hospital economics in Ohio.

That's what the engine does. And that's what this book explains.

Here's What You'll Discover Inside
the 28-Sector AI Playbook:

• Why Cloud Platforms have the highest AI ceiling (1.00) and highest velocity (0.95) in our 28-industry model — and why they win regardless of which AI company wins (Chapter 1)
• The 19.25 percentage-point margin expansion that AI creates for software companies — nearly double the second-highest industry. The specific mechanics of how AI eats its own workforce. (Chapter 1)
• Why Tencent's 2-bit compressed model is the single biggest bear signal for chip designers — and exactly how "software efficiency" threatens the "insatiable compute demand" narrative (Chapter 2)
• The $2.6 billion drug discovery that took 18 months instead of 10 years — and why Biotech-AI firms have a 0.97 ceiling but a 0.90 resistance score. What that gap means for investors. (Chapter 3)
• Why Enterprise SaaS is simultaneously the biggest opportunity AND the biggest existential threat in tech — the "AI Premium" could save it or the "build-it-yourself" revolution could kill it (Chapter 4)
• The specific reason Fintech is rated "Lean Bear" while Banks are "Lean Bull" — and why that surprises most people (Chapters 5 & 9)
• How parametric insurance — AI-triggered automatic payouts with no human claims adjuster — opens an entirely new category of risk that was previously uninsurable (Chapter 7)
• The sobering math on Media/Entertainment: AI ceiling of 0.95, velocity of 0.90, and a "Strong Bear" direction. What "unrecognizable by 2036" actually means for studio stocks (Chapter 17)
• Why Utilities — the most boring sector in investing history — may be the sleeper play of the entire AI revolution. Data center power contracts are turning them from commodity pipes into strategic infrastructure. (Chapter 24)
• The 3 industries to overweight right now, the 3 to underweight, and the "sleeper sectors" nobody's watching (Conclusion)
• A complete 28-industry reference table with every score, direction, and 1yr/5yr/10yr outlook on a single page you can pin to your wall (Appendix A)

The Timeline Question Every Investor Asks

The #1 question isn't "will AI affect my industry?" Everyone knows the answer is yes.

The question is: "WHEN?"

Chapter 27 walks you through what happens at each timeframe:

• Year 1: Which industries are already being repriced RIGHT NOW — and which ones Wall Street hasn't caught up to yet
• Year 3: The "adaptation window" — who's transforming versus who's in denial
• Year 5: The bifurcation point — winners and losers become permanent
• Year 10: The new normal — which industries are unrecognizable and what replaced them

This is where the 1-year analytical horizon becomes a real liability. If your research only tells you what happens this quarter, you're flying blind on the structural shift that determines whether an entire sector exists in ten years.

Why This Approach Is Right for This Moment

Look, I'm not pretending to have invented investment analysis. What I did was something specific:

I used AI — the same force that's reshuffling every industry — to build an analysis engine that models the reshuffling itself.

Traditional analysts are stuck in a structural bind:

• They're evaluated on 12-month price targets. AI's biggest effects play out over 3-10 years.
• They're focused on quarterly earnings and year-end fund rebalancing. AI creates structural shifts that don't fit neatly into quarters.
• Their coverage is siloed by sector. The semiconductor analyst doesn't model healthcare impacts. But that's exactly where the cross-effects live.
• They answer to "what have you done for me lately" bosses and clients who want this quarter's call, not a 5-year structural thesis.
• Their models are calibrated on 50 years of historical patterns. AI is a pattern-breaker.

None of that makes them wrong or dumb. It makes them structurally constrained for exactly this kind of moment.

My engine doesn't have a boss asking for a quarterly call. It doesn't have a coverage silo. It doesn't have a 12-month evaluation window. It tracks 28 industries across 8 analytical dimensions with 167 cross-sector effects over five timeframes from 1 year to 10 years.

Is it perfect? No. But it was built for this.

And If You Order Today, You Also Get This Free Bonus Report...

Why $27?

I'll be straight with you.

I built an AI disruption engine that models 28 industries across 8 analytical dimensions with 167 cross-sector effects. It calculates Relative Valuation Scores across five timeframes. It runs what-if scenarios. It's at aistockmarketimpacts.com and it costs $279 a year.

This book is a sample of what that engine produces.

I figure if you read 23,000 words of our research and think "this person actually knows what they're talking about" — some percentage of you will want the live engine, the monthly updates, and the scenario modeling that the subscription includes.

And if you don't? You still got a damn good book for twenty-seven dollars.

I'd rather have 10,000 people reading my research at $27 than 100 people wondering whether $279 is worth it.

That's the whole strategy. No tricks.

Here's Exactly What You Get:

Who Is This For?

This book is for self-directed investors who call their own shots.

People who:

• Own stocks in industries that AI will affect — which is all of them
• Want to understand specifically how AI changes the economics of each sector — not platitudes
• Are tired of research that either costs $24,000/yr from Bloomberg or comes free from cable news and is worth exactly what you paid for it
• Want the bear case alongside the bull case — because people who only show you one side are selling you something
• Need a timeline — not just "AI will be big someday" but specifically which sectors move at 1 year versus 10 years and why
• Care about cross-sector effects — because your semiconductor stocks are affected by energy policy, your insurance stocks are affected by self-driving vehicles, and your retail stocks are affected by AI-generated media. Nothing trades in a vacuum.

This is NOT for people who want stock tips. We don't do stock tips. We model the structural forces that move entire sectors — and let you make your own decisions like a grown adult.

Let Me Summarize:

Bloomberg Terminal: $24,000/yr.

Goldman Sachs sector report: not for sale to you at any price.

This: $27.

GET BOTH BOOKS NOW — $27