AI Bubble or Reset? 5 Signals That Tell You Which It Is

March 26, 2026

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The AI Investing Pulse

March 26th, 2026

In this Week’s Edition:

  1. Analysis - AI Bubble or Reset? 5 Signals That Tell You Which It Is

  2. Stock Ideas - Vertiv Is Quietly Powering Every AI Data Centre in America

  3. News - The AI Trade Is Splitting in Two. Which Side Are You On?

  4. Startups - Kleiner Perkins Raises $3.5 Billion for AI Startups

  5. Trends - AI and Energy Are Driving a 2026 M&A Megadeal Renaissance

  6. Other News - AI Content and Algorithms Are Coming for Your Kids

AI Bubble or Reset? 5 Signals That Tell You Which It Is

AI stocks have fallen 20–30% in 2026, with software names like Palantir, Adobe, and Salesforce leading the decline. The question is whether this represents a bubble bursting or a healthy repricing of valuations that had run ahead of fundamentals. Five measurable signals, earnings performance, infrastructure spending, analyst valuations, the gap between fear and reported results, and institutional capital flows, collectively point toward reset rather than collapse. Below, we walk through each of the five signals.

Is the AI sell-off supported by weak earnings?

The clearest test of whether a market theme has substance is whether the underlying companies are generating real revenue. On that measure, the AI trade is passing.

Oracle reported Q3 revenue of $17.19 billion, beating analyst expectations of $16.91 billion, with cloud revenue climbing 44% year on year. Management raised full-year 2027 guidance to $90 billion, well ahead of the $86.6 billion consensus. Nvidia delivered 73% year-on-year revenue growth in its most recent quarter. Microsoft's AI-driven cloud division continues to expand.

Deutsche Bank, after reviewing results across the software sector, found that US software earnings rose 29% in Q4 2025. Crucially, the bank found no software company expecting a negative revenue impact from AI in 2026. Bubbles are characterised by valuations detached from fundamentals. When fundamentals are advancing at this pace, a blanket bubble narrative requires scrutiny.

Is infrastructure spending slowing down?

In a genuine bubble, institutional capital begins to withdraw before the retail narrative catches up. The opposite is happening in AI infrastructure.

Hyperscaler capital expenditure, the combined infrastructure spend of Amazon, Microsoft, Google, and Meta, has been revised upward by approximately 70% to a projected $650 billion for 2026. Barclays forecasts Amazon Web Services (AWS) revenue growth of 34% in Q3 2026 on the back of agentic AI demand, with AI-related AWS revenue potentially reaching $75 billion by 2028.

Key infrastructure indicators:

  • Vertiv $VRT ( ▲ 1.95% ) , which supplies power and cooling systems for AI data centres, is guiding for $13.3–13.7 billion revenue in 2026, up 28%, with a $15 billion order backlog

  • Goldman Sachs forecasts a 15% surge in US M&A activity in 2026, driven largely by acquisitions of energy and utility companies to power AI compute capacity

  • Q1 2026 global M&A volumes hit a record $813.3 billion

Capital deployed at this scale, by institutions with direct visibility into demand, does not behave like speculative froth.

Are the major AI stocks actually overvalued?

In the dot-com bubble, valuations across the board were disconnected from any rational basis. The 2026 picture is more selective.

Morningstar's March 2026 analysis, which reviewed 132 technology companies — identifies three headline AI names as trading at significant discounts to fair value:

If these were bubble conditions, these names would be the most overvalued. Instead, they are among the most undervalued in Morningstar's coverage universe. Where Morningstar has flagged genuine risk is specific: six software companies, Adobe, Salesforce, ServiceNow, Shopify, Descartes, and Manhattan Associates, had their competitive moat ratings downgraded from wide to narrow. A moat is an analyst's term for a durable competitive advantage. These downgrades reflect a considered view that certain software business models are structurally weakened by AI. That is not a broad bubble signal; it is a targeted reassessment.

Is the fear being driven by data or by headlines?

The most recent leg of the software sell-off was triggered by a Bloomberg report on 24 March 2026 stating that AWS is developing an AI agent to automate the work of thousands of technical specialists in cybersecurity and server networking.

The technology described has not shipped. The commercial impact is speculative. Deutsche Bank's sector review found no evidence of AI-driven revenue disruption at any software company through the end of Q4 2025. The bank used the phrase "peak fear" to describe current sentiment, upgraded European and US software to overweight, and pointed to a sector with improving earnings but historically low valuations.

Markets sometimes price feared outcomes that have not yet occurred and may not materialise at the assumed severity. This is an inefficiency, not evidence of a bubble.

Is institutional capital moving in or out of AI?

The final signal is directional: where is informed capital actually going?

  • Kleiner Perkins is raising $3.5 billion for AI startups: $1 billion for early-stage companies and $2.5 billion for growth-stage. This is 75% larger than its previous flagship raise

  • Venture capital AI-related funding reached record levels entering 2026 across multiple data providers

  • Citi has named Nvidia, Broadcom $AVGO ( ▲ 0.16% ) , Texas Instruments (TXN), and Monolithic Power Systems $MPWR ( ▲ 1.55% ) as its top chip picks, with price targets implying 40–52% upside

  • Yann LeCun's AMI Labs raised $1.03 billion in Europe's largest ever seed round, backed by Nvidia, Samsung, Bezos Expeditions, and Temasek

Analysts and fund managers operating with full information do not consistently increase exposure during a collapsing bubble.

Final Take

The current environment is not uniform. Parts of the AI market are being repriced, and in some cases that repricing is rational. Software businesses whose competitive advantages depended on workflow friction and application stickiness face genuine structural questions as AI capabilities improve.

But the infrastructure build-out, the earnings trajectory, the institutional capital flows, and the analyst valuations on leading AI names all point in the same direction: this looks considerably more like a reset than a bubble.

Resets are uncomfortable. Historically, reset periods have preceded recoveries in fundamentals-driven markets, though past patterns are not a guide to future outcomes.

IMPORTANT LEGAL DISCLAIMER

Not Investment Advice: This content is provided by AI Investing Pulse for informational and educational purposes only. It does not constitute investment advice, a personal recommendation, or an invitation or inducement to engage in any investment activity. Not Regulated: AI Investing Pulse is not authorised or regulated by the Financial Conduct Authority (FCA) in the United Kingdom, is not registered with the Securities and Exchange Commission (SEC) or any state securities regulator in the United States, and is not registered with the Canadian Investment Regulatory Organization (CIRO) or any provincial securities commission in Canada. Methodology Disclosure: The AIIP Index scores and rankings mentioned in this article are generated by a proprietary quantitative methodology based on publicly available financial data. Our full methodology is explained in the "About AIIP" section below. These scores are objective system outputs, not recommendations or endorsements. Risk Warning: Investing in stocks involves risk, including the potential loss of principal. Past performance of stocks, scores, or rankings is not indicative of future results. Stock prices can decline as well as rise, and you may lose some or all of your invested capital. Third-Party References: References to analyst opinions, bank research, media publications, or the term "picks" refer to third-party selections, not AIIP recommendations. We aggregate this information for educational analysis only. Seek Professional Advice: Always consult a qualified, regulated financial professional who understands your personal circumstances before making any investment decisions. Consider your individual financial situation, risk tolerance, investment objectives, and time horizon.

About AIIP - The AIIP Index tracks 173 AI-focused public companies across the full AI stack, serving as our benchmark for sector performance. All scores are proprietary and calculated using data from Finbox (powered by S&P Global Intelligence). AIIP Total Score (0–100) combines metrics for sales and EPS growth, financial quality, and valuation to assess overall business strength. AIIP Relative Strength (RS) Score measures a stock’s price performance relative to the AIIP 173 AI stocks. Ranking Status is based on score combinations: Fundamental: Total Score ≥ 70, RS < 80. Momentum: RS ≥ 80, Total Score < 70. Watchlist: Total Score ≥ 70 and RS ≥ 80

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TOP AI STOCKS PERFORMANCE

COMPANY

SECTOR

WEEKLY

Arm Holdings (ARM)

Technology

21.0%

Dell (DELL)

Technology

17.4%

Hewlett Packard (HPE)

Technology

17.3%

TOP AI ETFs PERFORMANCE

ETFs

SECTOR

WEEKLY

Roundhill (CHAT)

Gen AI & Tech

-0.3%

KraneShares (AGIX)

AI & Tech

-1.6%

Robo Global (THNQ)

Global AI

-1.8%

AI Stock Ideas

Vertiv supplies the power and cooling infrastructure behind every major AI data centre build-out. With partnerships with Nvidia and the hyperscalers, the thesis is simple: if AI spending holds, Vertiv captures a growing share of it at improving margins.

NerdWallet's monthly ranking of the top-performing AI stocks from the Indxx Global Robotics and Artificial Intelligence Index covers Palantir, Nvidia, Alphabet, and Oracle among the standouts.

IBM fell 20% from its 52-week high after news broke that Anthropic's AI tools can now handle COBOL coding tasks a direct threat to IBM's legacy services business. The counter-argument is that IBM's hybrid cloud infrastructure becomes more valuable, not less.

AI Stocks News

The market is drawing a clear line between AI hardware and infrastructure names, which continue to advance, and AI software stocks, which are being sold down on disruption fears.

Barclays reiterated its $300 price target on Amazon with an Overweight rating, forecasting AWS revenue growth of 34% in Q3 2026 as agentic AI workloads drive demand. The bank estimates AWS AI-related revenue could exceed $10 billion by end of 2026 and reach $75 billion by 2028.

Morningstar's March 2026 update flags three major AI names as trading at significant discounts to fair value. Nvidia, Microsoft and Meta.

Reports that AWS is developing an AI agent to automate the work of thousands of technical specialists in cybersecurity and server networking sent software stocks lower. The question for investors is whether this is rational repricing or an overcorrection on companies with resilient earnings.

AI Startups

Kleiner Perkins is raising $3.5 billion split across two funds: $1 billion for early-stage AI bets through its KP22 vehicle and $2.5 billion targeting growth-stage companies. This signals that top-tier VC firms are scaling up conviction on AI at both ends of the company lifecycle.

Strategic buyers are outpacing private equity in cybersecurity M&A, with AI-native security startups attracting large early-stage capital at a pace not seen before.

Goldman Sachs forecasts a 15% surge in US M&A activity in 2026, with Q1 already hitting a record $813.3 billion. The driving force is not low interest rates but a structural race for AI capability and energy security.

AI agents that autonomously discover, compare, and purchase products on behalf of consumers are moving from concept to deployment. Meta, Google, and OpenAI are all building agent-enabled transaction platforms, while traffic from generative AI platforms to retail sites surged 693% year-on-year in 2025.

Others

Harvard Law's analysis argues that child-safety regulation is becoming the primary legislative vehicle for broader AI content controls, with political pressure building at federal and state levels across the ideological spectrum.

Answer Engine Optimization, the practice of structuring content so AI systems cite your brand in generated answers, is becoming a distinct discipline from traditional SEO. AI Search Engineers has been recognised as a leading certified AEO agency.

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IMPORTANT LEGAL DISCLAIMER

Not Investment Advice: This content is provided by AI Investing Pulse for informational and educational purposes only. It does not constitute investment advice, a personal recommendation, or an invitation or inducement to engage in any investment activity. Not Regulated: AI Investing Pulse is not authorised or regulated by the Financial Conduct Authority (FCA) in the United Kingdom, is not registered with the Securities and Exchange Commission (SEC) or any state securities regulator in the United States, and is not registered with the Canadian Investment Regulatory Organization (CIRO) or any provincial securities commission in Canada. Methodology Disclosure: The AIIP Index scores and rankings mentioned in this article are generated by a proprietary quantitative methodology based on publicly available financial data. Our full methodology is explained in the "About AIIP" section below. These scores are objective system outputs, not recommendations or endorsements. Risk Warning: Investing in stocks involves risk, including the potential loss of principal. Past performance of stocks, scores, or rankings is not indicative of future results. Stock prices can decline as well as rise, and you may lose some or all of your invested capital. Third-Party References: References to analyst opinions, bank research, media publications, or the term "picks" refer to third-party selections, not AIIP recommendations. We aggregate this information for educational analysis only. Seek Professional Advice: Always consult a qualified, regulated financial professional who understands your personal circumstances before making any investment decisions. Consider your individual financial situation, risk tolerance, investment objectives, and time horizon.

About AIIP - The AIIP Index tracks 173 AI-focused public companies across the full AI stack, serving as our benchmark for sector performance. All scores are proprietary and calculated using data from Finbox (powered by S&P Global Intelligence). AIIP Total Score (0–100) combines metrics for sales and EPS growth, financial quality, and valuation to assess overall business strength. AIIP Relative Strength (RS) Score measures a stock’s price performance relative to the AIIP 173 AI stocks. Ranking Status is based on score combinations: Fundamental: Total Score ≥ 70, RS < 80. Momentum: RS ≥ 80, Total Score < 70. Watchlist: Total Score ≥ 70 and RS ≥ 80