Three Months Later, the Future Arrived Ahead of Schedule

A Follow-Up to “My Reflections on the AI Revolution”

What a Difference Three Months Makes

In late January, I published an article titled “My Reflections on the AI Revolution—And What It Means for Your Wealth.” In it, I laid out a thesis: we’re entering a period of profound economic reorganization driven by artificial intelligence, the planning window is shorter than most people think, and the right response isn’t fear, it’s positioning yourself where the value is actually moving.

I described five scenarios for how this might unfold, from policy gridlock to abundance. I talked about timeline compression, meaning the possibility that what most economists expect to play out over 15 years might happen in seven or eight.

Three months later, I’m writing to tell you: timeline compression isn’t a scenario anymore. It’s the news cycle.

The Oracle Moment

On March 31st, thousands of Oracle employees opened an email at 6:00 a.m. from “Oracle Leadership.” No phone call. No meeting with their manager. By the time they finished reading, their system access had already been revoked. The email said their role had been eliminated. Today was their last day.

Estimates from TD Cowen put the number between 20,000 and 30,000 people—roughly 18% of Oracle’s global workforce. In a single morning. And here’s what makes this different from prior tech layoffs: Oracle is not struggling. The company posted $6.13 billion in net income last quarter, up sharply year over year. Its contracted future revenue stands at over $500 billion. This wasn’t a cost-cutting measure born of distress. It was a capital reallocation decision. Oracle calculated that replacing tens of thousands of workers with AI infrastructure would free up $8-10 billion in annual cash flow to fund its data center buildout.

A profitable company eliminated one-fifth of its workforce not because it was losing money, but because it decided machines would generate more value than people. That’s a sentence worth sitting with.

Oracle Is Not an Outlier

If Oracle were the only story, you could dismiss it as one company making an aggressive bet. But it’s not. It’s a data point in a pattern that has been building all year.

According to Challenger, Gray & Christmas, tech layoffs jumped 40% year-over-year in Q1, with over 52,000 U.S. tech workers cut in the first three months of 2026 alone. Global trackers put the number closer to 90,000. Amazon cut 16,000. Dell cut 11,000. Block cut roughly 4,000. Meta reduced its Reality Labs division. ASML, Atlassian, Ericsson, Epic Games—the list goes on. And the playbook is remarkably consistent: reduce headcount in execution roles, invest billions in AI infrastructure, hire smaller specialized teams to manage the machines.

In March, AI led all stated reasons for job cuts for the first time, accounting for roughly a quarter of all layoffs that month. Even allowing for the fact that some companies may be using AI as a convenient narrative—what some analysts have called “AI washing”—the underlying pattern is clear: companies are growing revenue while deliberately shrinking their workforces. This isn’t a correction. It’s a restructuring.

To be fair, the broader labor market has not collapsed. Yesterday’s jobs report showed the U.S. economy added 178,000 jobs in March, which is well above expectations, with gains concentrated in healthcare, construction, and transportation. The unemployment rate edged down to 4.3%. And AI is creating jobs too: LinkedIn data shows 1.3 million new AI-related positions globally over the past two years, with companies reporting a 92% increase in hiring for AI-specific roles.

But here’s the distinction that matters for planning purposes: the jobs being eliminated and the jobs being created are not the same jobs, in the same places, requiring the same skills, at the same compensation levels. The economy is not shrinking. It’s reorganizing. And the transition between what’s being lost and what’s being built is where the real risk and the real opportunity lives.

The Other Side of the Ledger

While those layoffs were unfolding, three AI-native companies were preparing what could become the largest public offerings in history. The contrast is worth understanding, not because these numbers are cause for celebration, but because they illustrate the sheer scale of capital flowing into AI and away from traditional labor.

OpenAI crossed $25 billion in annualized revenue as of February 2026—up from roughly $6 billion just fourteen months earlier. The company now serves over 900 million weekly active users and counts more than 9 million paying business customers.

SpaceX (which merged with Elon Musk’s AI venture xAI earlier this year) confidentially filed for an IPO this week. Bloomberg reports the company is now targeting a valuation above $2 trillion, with a potential $75 billion raise. Starlink alone now has over 10 million global subscribers.

Anthropic (the company behind Claude, which powers much of our internal AI infrastructure at Prosperity) reached $19 billion in annualized revenue by March—up from $9 billion at year-end 2025. The company is reportedly in discussions for an October 2026 listing at a valuation in the range of $400–500 billion.

Three potential mega-IPOs. Combined targeted valuations north of $3 trillion. In a single year.

Tens of thousands of jobs eliminated on one side. Trillions in new enterprise value created on the other. The economy isn’t shrinking. But it is reorganizing—rapidly and unevenly—and the gap between the people who understand what’s happening and those who don’t is becoming one of the defining economic divides of this decade.

What This Validates from January

When I wrote the original piece, several of these dynamics were still largely theoretical. They aren’t anymore. Let me connect the dots to the scenarios I outlined:

The labor tax base erosion is happening now. I wrote that each displaced $150,000 professional represents roughly $40,000 in lost federal revenue; income tax plus payroll tax. Oracle alone, at 30,000 positions, represents a potential $1.2 billion annual reduction in federal tax revenue from a single company’s restructuring. Multiply that across the industry and the fiscal pressure I described isn’t a five-year-out concern. It’s a this-year concern.

The behavioral cliff effects are playing out in real time. I warned that as displacement becomes visible, political pressure for tax incentives on automation would intensify. The One Big Beautiful Bill (OBBB), passed last year, restored 100% bonus depreciation, meaning Oracle can immediately deduct the full cost of every server, GPU, and networking switch it buys to replace those workers. The government is effectively subsidizing the automation that erodes its own tax base. This is exactly the dynamic I flagged.

Capital gains concentration is accelerating. The productivity gains from AI aren’t flowing to wage earners. They’re flowing to shareholders, founders, and early investors in AI-native companies. Three potential IPOs creating trillions in shareholder value while the labor market absorbs tens of thousands of displaced workers is the capital-labor divergence I described, but it’s happening faster than I expected.

Timeline compression is confirmed. I suggested that the disruption phase many economists expected to stretch through 2030 could compress into a much shorter window. Q1 2026 data suggests we’re well into that phase already. The gap between early action and delayed action for individuals, companies, and policymakers is widening by the month.

How We’re Responding at Prosperity Capital Advisors

I want to be transparent about something: we’re not just writing about this. We’re acting on it, both in how we serve our clients and how we think about investing their wealth.

At Prosperity Capital Advisors, we’ve been integrating AI across our practice—not to replace our advisors, but to deliver a better experience for our clients. What does that mean in practice?

It means deeper research and due diligence on the opportunities and risks in your portfolio. It means more personalized and rigorous scenario planning, stress-tested against the kinds of futures we’ve been discussing. It means faster, more thorough responses when you have questions or need guidance on a complex decision. And it means our advisors are spending more of their time on the work that matters most: the conversations, the judgment calls, the relationship-driven guidance that no technology can replicate.

This is what I meant in January when I talked about the “red pill” effect. The firms that are integrating AI thoughtfully into their operations aren’t just marginally better at serving clients. They’re operating in a different category. And that’s where we intend to be—not because it’s trendy, but because our clients deserve advisors who are leveraging every available tool to protect and grow their wealth.

Foundations Over Applications: The Valor AI Foundations Portfolio

But we’re not just changing how we operate. We’re also rethinking how we approach investing in this transition.

Earlier this year, we launched the Valor AI Foundations Portfolio, an investment strategy built around the thesis that the biggest beneficiaries of AI adoption may not be the software applications that grab the headlines, but rather the foundational layers that make AI possible in the first place.

Here’s the thinking: Oracle’s story is a useful illustration: the company didn’t just cut 30,000 jobs. It redirected that capital into data centers, servers, GPUs, networking equipment, and power infrastructure. SpaceX needs $75 billion to build AI-capable satellite infrastructure. OpenAI has committed over $500 billion in cloud capacity deals across multiple providers. Anthropic is spending $19 billion on training and inference this year alone. Whatever you think about the pace or ultimate impact of AI, the capital flowing into physical infrastructure is enormous and accelerating.

Consider what every AI system requires to function: advanced semiconductors and compute to train and run the models. Enormous amounts of energy—data centers are already straining power grids, and new generation capacity can’t come online fast enough. Data centers and digital infrastructure to house the hardware. Critical materials like copper and rare earth metals that go into every chip and every cable. Defense and national security applications that are driving government spending on AI capability. And healthcare data and diagnostics where AI is beginning to change how care is delivered.

These are the foundations. And the key insight is this: demand for these foundational layers may remain strong regardless of which specific AI applications or companies ultimately win. It doesn’t matter whether Oracle or Amazon or a startup you’ve never heard of dominates the AI application layer. They all need chips. They all need power. They all need data centers. They all need copper in the ground.

Meanwhile, at the application layer, something counterintuitive is happening. As AI makes it easier and cheaper to build software, the supply of software creation is expanding rapidly, which means pricing and margin pressure on traditional software business models may increase over time. Larry Ellison himself has referred to this as the “SaaSpocalypse.” The very AI tools these companies are building could put pressure on the business models of the software companies that sell them. That’s a risk worth considering for portfolios with heavy exposure to conventional technology stocks.

The Valor AI Foundations Portfolio is designed around this distinction. It emphasizes the infrastructure, data, and physical capacity that enable AI while deliberately underweighting or avoiding broad exposure to traditional application-level software models that may face disruption. It’s implemented through diversified ETFs across the six foundational layers I mentioned, and it’s constructed with a long-term horizon in mind, recognizing that AI adoption will unfold across multiple investment cycles.

This isn’t about chasing the latest AI stock. It’s about asking a more fundamental question: If AI does transform the economy over the next decade, what are the physical and structural assets that every version of that future requires? And then building a portfolio around those answers.

What This Means for You

If you’ve read both the January piece and this one, the message should be clear: the planning window I talked about three months ago has gotten shorter, not longer. The strategies we outlined—tax diversification, Roth positioning, scenario-based stress testing, protection against concentration risk, legacy structures that account for a rapidly changing world. All of these are more urgent now than they were in January.

A few specific considerations worth highlighting as we move into Q2:

Roth conversion opportunities remain open, but the window may narrow. If federal revenues come under the kind of pressure this data suggests, tax rate increases become a matter of when, not if. Converting traditional IRA assets to Roth at today’s known rates continues to be one of the most powerful moves available.

Portfolio positioning matters more than ever. The companies creating value in an AI-driven economy are not the same companies that led the last cycle. Broad diversification remains important, but so is making sure your portfolio has thoughtful exposure to the foundational layers of AI adoption while managing the real risk that application-level companies could face margin compression even as AI spending accelerates. If you’re interested in how the Valor AI Foundations Portfolio might fit within your broader wealth strategy, that’s a conversation worth having with your advisor.

Protection planning isn’t optional. Periods of rapid technological transition are inherently volatile. For every company that will thrive in this environment, others will fail to adapt and lose significant value. If you’re concentrated in any single company or sector, especially one facing AI-driven disruption, now is the time to address that exposure.

Your career and income are part of the equation. If your industry is in the path of AI disruption, your human capital is a financial asset that just changed in value. That affects everything from savings rates to insurance needs to retirement timelines. We should be talking about that.

The Abundance Case Is Still Real

I want to end where I ended in January: with optimism grounded in realism.

Yes, tens of thousands of people lost their tech jobs in Q1. That’s painful and real, and I don’t want to minimize it. But the same forces driving that displacement are also creating new categories of work that didn’t exist a few years ago. The World Economic Forum projects that by 2030, AI-driven transformation will create 170 million new roles globally while displacing 92 million; a net gain of 78 million positions.

Workers with AI skills are already commanding wage premiums of over 50% compared to peers in similar roles without those skills. The demand for AI engineers, data scientists, and infrastructure specialists is growing faster than the talent pipeline can fill it.

The question isn’t whether the future economy will have enough jobs. It’s whether the people who are being displaced today will have the skills, the resources, and the planning runway to reach those new opportunities. That’s a transition problem, not a scarcity problem and transitions are exactly what thoughtful wealth management is designed to navigate.

The abundance scenario I described in January where AI productivity gains expand the economic pie so dramatically that real living standards rise even as the nature of work transforms is still very much in play. But it’s not automatic. It requires thoughtful positioning, disciplined planning, and the willingness to act before the transition is obvious to everyone.

If you’re a client, your Bucket Plan was built for exactly this kind of uncertainty. Let’s revisit it together and make sure your strategy reflects what we’ve learned in the past three months. If you’re not yet a client, I’d encourage you to reach out to one of our advisors across the United States. The conversation about how to position your wealth for this transition is one of the most important financial conversations you can have right now.

And if you’re an advisor watching this unfold and thinking, “This is how I want to serve my clients,” we’re building something special at Prosperity Capital Advisors. We’d love to talk.

The future didn’t wait for us to get ready. But it’s not too late to get positioned.

— Dave