A Tech Investment Frenzy in the Making

Are we in the middle of a tech bubble? Lately, anything labeled artificial intelligence – from chipmakers to software startups – has been soaring in valuation. In 2023–2025, AI-related stocks led a torrid market rally, pushing equity indices to new highs despite broader economic worries.

Over half of global fund managers recently told Bank of America that they see AI stocks in a bubble, yet most are still heavily invested in them.

Similar excitement surrounds robotics and quantum computing, two other frontiers of innovation. Quantum computing startups like IonQ and Rigetti, for example, have seen their stock prices skyrocket 700%+ (and in Rigetti’s case, over 6,000%) within a year – gains reminiscent of the craziest days of the dot-com mania.

Skeptics argue that this boom will end like prior bubbles – an inevitable bust. But unlike the dot-com crash or crypto collapse, this tech revolution may justify investor optimism. The world’s biggest companies are betting trillions on AI-driven infrastructure, robotics is addressing real-world problems, and quantum technology promises unprecedented computing power. Even if valuations are running hot, the potential long-term rewards have many believing that the risk of not investing is greater than the risk of a pullback.

In this blog, we’ll explore how AI, robotics, and quantum innovations are powering a market surge often called a “bubble,” why that bubble might keep inflating, and why – despite the risks – many see it as a wager worth making. Along the way, we’ll look at historical parallels, the progress and utility of these technologies, and real-world examples from publicly traded companies at the forefront of this revolution.

Bubbles Then and Now: Lessons from History

Rapid technological change has a habit of igniting financial bubbles. We saw it with 19th-century railroads, which raised enormous capital, overbuilt lines, then crashed – yet ultimately transformed commerce. We saw it with the 1990s internet boom: investors chased any company with a “.com” in its name, a severe bust followed, but the survivors (Amazon, eBay, etc.) went on to reshape the economy. As one analyst wryly notes, “Like the 19th century railroads and the 20th century broadband Internet build-out, AI will rise first, crash second, and eventually change the world.”

In other words, both the optimists and the skeptics may be right – there likely is a bubble, and it will pop, but the long-term impact of the technology could be enormous nonetheless.

The dot-com bubble offers both a cautionary tale and a hopeful precedent. Between 1995 and 2000, tech stocks surged on dreams of a web-enabled future. When reality fell short, the NASDAQ index plummeted 75% from 2000 to 2002, erasing trillions in paper wealth.

Yet by 2025, that same index had climbed more than 18-fold from its post-crash lows.

The excesses of the ‘90s – absurd valuations, lack of profits, even outright fraud in cases like WorldCom – eventually gave way to an internet-driven economy of genuine value.

The key insight: some bubbles do leave behind real assets and lasting innovation even if many investors get burned along the way.

What’s different about the current AI/tech boom? Compared to 1999, today’s hype is centered more on established firms and tangible breakthroughs than on flimsy startups. In 2000, a majority of tech companies going public had no profits at all. Now, only ~20% of tech firms are unprofitable, far fewer than the 36% share during the dot-com era.

 The main “AI plays” in public markets are giants like Nvidia, Microsoft, Alphabet, Amazon, and Meta, which have strong balance sheets and real revenues. These companies are investing heavily in AI from their own cash flows, not just burning venture capital. That makes the current wave somewhat more grounded – though not immune to over-exuberance.

Another difference is the funding structure. Classic bubbles often rely on heavy leverage or debt, which makes their collapse dangerous to the wider financial system (think of subprime mortgages in 2008). The AI boom so far is mostly equity-funded – investors are using cash, not excessive borrowing, to place their bets. The IMF’s chief economist recently pointed out that if an AI investment frenzy unwinds, it’s unlikely to trigger a 2008-style crisis precisely because it isn’t propped up by debt. Losses would hit equity holders, but banks would remain largely unscathed. Similarly, regulators seem content to “let the boom run” to avoid killing innovation, so long as bank credit isn’t fueling it. This dynamic resembles other innovation-driven bubbles in history: they can actually yield societal benefits (new railroads, fiber-optic networks, etc.) when the dust settles, especially if the speculative excess is confined to equity markets.

None of this guarantees that AI/tech stocks can’t crash – they certainly can. But it suggests that a bursting bubble in this arena, while painful for investors, might be less catastrophic economically and might sow the seeds for future growth. Even Amazon’s Jeff Bezos, who rode out the dot-com bust, notes that speculative booms in emerging tech are “not nearly as bad” as financial bubbles: “when the dust settles and you see who are the winners, society benefits from those inventions.” In short, the stage may be set for a cycle of boom, bust, and long-term boom – with savvy investors hoping to survive the volatility and be holding the winners at the end. The AI Gold Rush: Hype with a Kernel of Truth

If one thing defines the current market, it’s the frenzy around Artificial Intelligence. Ever since generative AI (like OpenAI’s ChatGPT) burst onto the scene, companies have been scrambling to invest in AI capabilities – and announcing those investments loudly. In fact, just the announcement of multi-billion-dollar AI spending is sometimes enough to send a stock higher. The result: an arms race among tech giants and a stampede of investors trying not to miss out on “the next big thing.”

Consider some jaw-dropping numbers. Big Tech’s AI spending is unprecedented in scale. In 2025, Alphabet (Google’s parent), Microsoft, Amazon, and Meta are on track to spend over $400 billion combined in capital expenditures – primarily to build AI data centers and infrastructure. That annual AI investment is larger than what the entire European Union spends on defense. Morgan Stanley predicts nearly $3 trillion more will be spent on AI-related hardware and data centers from 2025 to 2028. This surge in capex is so large that it’s contributing about 0.5% to U.S. GDP growth all by itself. One asset manager noted that roughly 40% of U.S. GDP growth in 2023-24 is coming from AI investments, akin to the economy-wide impact of railroad booms or the early internet build-out. In other words, AI isn’t just a tech story – it’s now a macroeconomic force. Wall Street has quickly rewarded these bets. When Microsoft told analysts it would boost AI spending even more, its stock jumped, briefly propelling Microsoft’s market capitalization to $4 trillion in 2025. Meta (Facebook), after years in the doldrums, saw its shares nearly triple off 2022 lows as it refocused on AI for advertising and efficiency. And then there’s Nvidia, the poster child of the AI boom. Nvidia produces the advanced GPUs that train AI models, and demand is through the roof. The company stunned the market with a 170% jump in quarterly profit in mid-2023 thanks to AI chip sales, leading analysts to constantly revise estimates upward. Nvidia’s stock price surged so much that it became one of the world’s most valuable companies – crossing the $1 trillion mark – and at one point traded at over 25 times annual sales. Bulls argue this is justified by Nvidia’s near-monopoly in AI chips and multi-year growth runway, while bears see classic bubble behavior. But crucially, Nvidia’s rise has been driven by real earnings growth, not just hype, which distinguishes it from many dot-com era darlings. As investment firm Janus Henderson noted, “a sign of a market bubble is when valuation expands without profit growth – something we have yet to experience in the current AI wave.” The AI revenue is indeed materializing for some players.

That said, warning signs of excess abound in the AI gold rush. One issue is the disconnect between current economic returns and future expectations. While hundreds of billions are being poured into AI, the immediate monetization remains slim. Consumers worldwide spend only about $12 billion/year on AI services right now (think cloud AI, subscription APIs, etc.), a tiny fraction compared to the half-trillion dollars in annual AI infrastructure spend that companies are projected to reach. This is the classic pattern of a speculative boom: massive investment based on anticipated future usage that hasn’t arrived yet. Some reports even indicate that AI usage within enterprises is below expectations – companies are still figuring out how to deploy advanced AI effectively, leading to under-utilized capacity. In plain terms, there’s a lot of expensive “AI horsepower” being built that hasn’t found enough work to do yet. That gap between vision and reality is what keeps skeptics up at night.

Another hallmark of the mania is investor behavior. A recent analysis suggests stock prices in 2023–24 have been driven far more by momentum and FOMO (fear of missing out) than by fundamentals.

Stocks of anything vaguely AI-related have spiked as retail traders pile in, reminiscent of meme-stock behavior.

There have been absurd anecdotes, like a startup founded by a former OpenAI executive raising $2 billion in seed funding at a $10 billion valuation – despite having no product and refusing to even explain its plans (their pitch was essentially “trust us, we have the best AI people”). When seasoned investors start throwing money at such black-box ventures, it’s a classic bubble signal. Even Sam Altman, CEO of OpenAI, admitted in mid-2025 that “investors as a whole are overexcited about AI… Someone is going to lose a phenomenal amount of money”. Tellingly, though, Altman added that many others will make a phenomenal amount – the tricky part is picking the winners. This encapsulates the vibe in Silicon Valley and Wall Street: everyone knows there’s froth, but no one wants to sit out and risk missing the next Microsoft or Google. Indeed, UBS strategists found that 90% of investors who labeled AI a bubble were still invested in AI-related areas, believing we’re “far from the apex” of the bubble’s peak.

Behind the hype, AI’s transformative potential is real – which is precisely why people are excited. Unlike some past fads, AI is already delivering practical benefits across industries. For example, generative AI has dramatically sped up tasks like coding and content creation. A McKinsey study found that software developers can complete coding tasks up to 2× faster with AI assistance.

In another experiment, office workers using ChatGPT were 40% more productive on certain writing tasks, with higher output quality additional to that.

Companies are reporting tangible efficiency gains: one manager noted that creating a prototype of a new product used to take weeks, but with AI tools (for generating design mockups, code, etc.), they prepared a presentation in just 4 hours. These kinds of anecdotes are piling up in sectors from marketing to pharmaceuticals. AI-powered chatbots are handling customer service queries, saving companies millions in call center costs. In finance, AI algorithms are optimizing portfolio strategies and risk management. And in healthcare, AI systems are helping with everything from radiology image analysis to drug discovery.

Crucially, the big productivity gains from AI may still lie ahead – which bolsters the bull case that today’s investments will pay off. Just as the benefits of broadband internet (e.g. video streaming, cloud computing) took years after the fiber-optic build-out, the most valuable applications of AI may not even be clear yet. Optimists draw parallels to the internet: in the late ’90s, huge sums were spent on laying fiber cables and server farms that seemed underutilized after the crash, but a few years later they enabled the explosion of Google, YouTube, e-commerce, and social media. Likewise, the AI infrastructure being built now could be the foundation for ubiquitous AI in daily life a few years hence. It’s even been said we probably “cannot yet comprehend how pervasive AI will become and the value it will add to our lives” – much as few in 1999 envisioned smartphone apps or cloud services. This thinking keeps investors and companies plowing capital into AI despite the lack of immediate ROI.

In summary, the AI sector in 2025 exhibits a mix of bubble-like excess and genuine promise. Yes, there is froth – sky-high valuations, questionable startups getting funded, and a disconnect between current profits and stock prices. But unlike a pure speculative bubble, there is also substantive progress and revenue growth underpinning parts of it (especially for the established players). AI technology is advancing rapidly and proving its worth in many domains. This dual reality – exuberance plus real progress – is why the AI bubble (if that’s what it is) has so far been more durable than, say, the cryptocurrency bubbles of recent years. The big question is whether the eventual shakeout will resemble the healthy pruning of the early 2000s (where a few giants emerged stronger than ever), or something more painful. We’ll return to strategies for managing that risk-versus-reward tradeoff. First, let’s look at the other two pillars of this tech revolution: robotics and quantum computing.

Robotics Renaissance: From Assembly Lines to Autonomous Helpers

Often mentioned in the same breath as AI is the resurgence of robotics. In many ways, robotics is the physical twin of AI – one provides the “brains” (software intelligence) and the other the “brawn” (machines that act on the world). Robotics hasn’t had a headline-grabbing bubble of its own recently, but it is riding the AI wave and seeing accelerating adoption across industries. Investors are keen on robotics as part of the broader automation trend, and several public companies in this space have been strong performers.

Real-world progress in robotics is tangible. The International Federation of Robotics reports that the global market value of industrial robot installations hit an all-time high of $16.5 billion last year. Factories worldwide are deploying more robots than ever, especially in automotive and electronics manufacturing. Companies like ABB and Fanuc, two of the largest industrial robot manufacturers, have each installed hundreds of thousands of robots at client sites around the globe. These are the robot arms tirelessly assembling cars, appliances, and smartphones with precision and speed. The adoption is no longer limited to big corporations; smaller manufacturers are also jumping in, aided by falling costs and new financing models like Robots-as-a-Service (renting robots instead of buying).

An exciting sub-segment is collaborative robots (“cobots”) – smaller, safer robots that can work alongside humans. Universal Robots, a pioneer in cobots (now owned by Teradyne[gotta love that Terminator-esque name]), has sold over 50,000 such robots, commanding more than 50% of the global cobot market.

Cobots are helping automate tasks for small and mid-sized businesses that traditionally couldn’t justify industrial robots – like assisting workers on assembly tasks, packing goods, or performing quality inspections.

Meanwhile, medical robotics is booming: Intuitive Surgical’s renowned da Vinci surgical robots have performed over 10 million procedures in hospitals worldwide, demonstrating how robots can enhance precision in surgery and expand the capabilities of doctors. This mix of manufacturing, collaborative, and medical robots shows how far the field has come. It’s not just science fiction or research projects – robots are already embedded in our economy’s fabric.

Even consumer-facing robotics are inching closer to reality. Warehouse and logistics automation is a hot area: retail giants like Amazon now use over 1 million mobile robots in their fulfillment centers to move shelves and packages. In July 2025, Amazon deployed its one millionth warehouse robot and simultaneously rolled out a new AI system (“DeepFleet”) to coordinate these machines more efficiently across 300+ facilities. These robots, essentially autonomous carts and robotic arms, have helped Amazon handle the explosive growth of e-commerce while keeping costs in check. Notably, Amazon says their most advanced automated warehouses still hire more human workers in technical roles – maintaining and programming robots – even as robots handle the grunt work. This underscores a broader point: far from rendering humans obsolete, the current wave of robotics is often about humans and machines working together, each doing what they do best.

On the more futuristic side, there’s been lots of buzz around humanoid robots – machines that walk on two legs and mimic human actions. Several startups (and at least one famous EV company, Tesla, with its prototype “Optimus” robot) are developing humanoids aimed at general-purpose work. Media hype aside, experts are cautious about how soon humanoids will be practical. The IFR notes that “it remains to be seen whether humanoid robots can represent an economically viable and scalable business,” especially compared to more specialized machines. For now, most humanoid projects target single-purpose tasks in controlled environments (like moving materials in a factory). It may be a while before a bipedal robot is loading your dishwasher or delivering packages on the street. Still, the fact that serious money is going into such projects speaks to the long-term vision – and yes, a bit of sci-fi dream – that robots could someday be as commonplace as today’s automobiles or computers. That vision, even if distant, contributes to investor enthusiasm for the robotics/automation sector.

From an investment standpoint, many robotics-focused companies are publicly traded and have seen strong performance, albeit less dramatically than the AI pure-plays. Established firms like ABB Ltd. (traded in Zurich and New York) or Fanuc (Japan) are often considered “ picks-and-shovels” plays on automation – they profit as more industries automate, regardless of which end-customer wins. Their stocks have generally trended up in recent years as order books for robots hit records. Tech conglomerates like Alphabet and Amazon are also in the fray, acquiring robotics startups or developing their own in-house robots (for example, Google’s early acquisition of Boston Dynamics, or Amazon’s purchase of Kiva Systems a decade ago that jump-started its warehouse robot fleet). And for thematic exposure, some investors turn to ETFs like Global X Robotics & AI ETF (BOTZ) or ARK Innovation’s Autonomous Technology & Robotics ETF (ARKQ), which hold baskets of these names. These funds have attracted inflows amid the automation hype, although they also hold AI stocks, given the overlap.

What’s fueling the robotics renaissance is not just hype but also compelling economic drivers. One is the chronic labor shortage in many countries and industries. As populations age (in the U.S., Europe, China, Japan, etc.), there simply aren’t enough young workers to fill certain roles – from manufacturing and warehousing to eldercare. Robots are stepping into the gap by performing the “3 D’s”: tasks that are dirty, dull, or dangerous. They paint cars, inspect sewers, sort recycling, and take on repetitive assembly tasks, which helps businesses cope when human labor is scarce or expensive. Another driver is supply chain resilience: recent global crises (pandemics, trade disputes) taught companies the value of automation to maintain operations and the benefit of producing closer to home. Robotics enables manufacturing to be “reshored” to higher-wage countries by keeping it cost-competitive through automation. Governments too see robotics and AI as strategic technologies to maintain economic growth. All these factors mean the demand for robots is likely to keep rising. In fact, one market forecast expects the advanced robotics market to grow from about $50 billion in 2025 to $280 billion by 2034 – a more than fivefold increase. Such growth projections feed the narrative that investing in robotics now could be like investing in computing in the 1980s – an oncoming tidal wave of opportunity.

Of course, robotics isn’t free of hype. Investors must be discerning. Some robotics startups with flashy demos may not have a sustainable business (we’ve seen crowd-pleasing robot dogs and humanoids that make great YouTube videos but not profits). Also, robotics as a field moves in iterative engineering advances, not just Moore’s Law leaps, so progress can be slower than the software world. Nonetheless, when paired with AI, robotics is entering a virtuous cycle: better AI makes robots smarter and more useful, while better robots extend AI’s reach into the physical world. This synergy is a core reason many analysts believe we’re at the start of a multi-year automation wave rather than a short-lived fad. And unlike the pure digital realm, here it’s less about speculative startups and more about industrial leaders – making the “bubble” aspect a bit more subdued, even as growth prospects are bright.

The Quantum Quest: Speculation at the Frontier of Computing

Of the three areas discussed, quantum computing is arguably the furthest from everyday impact – and yet it has incited some of the wildest market speculation.

Quantum computing involves harnessing the counterintuitive properties of quantum physics to perform calculations exponentially faster than today’s computers can. It’s an utterly transformative idea: fully realized quantum computers could potentially break current encryption, revolutionize drug discovery and materials science, optimize complex systems in minutes that would take classical computers millennia, and more. But the technology is fiendishly difficult; current quantum processors have only tens or hundreds of fragile qubits (quantum bits) and can only run very specialized algorithms under lab conditions.

It’s the ultimate high-risk, high-reward field – and investors have been piling in despite the long timeline.

Nowhere is the bubble-like enthusiasm more evident than in the stock market performance of the handful of pure-play quantum companies.

Take Rigetti Computing (RGTI), a startup specializing in superconducting quantum processors. In the 12 months through October 2025, Rigetti’s stock rocketed an astounding 6,629% higher. Yes, you read that right – a nearly 67× increase. Rival D-Wave Quantum (QBTS) jumped over 4,000% in the same period, and IonQ (IONQ)[One of my personal favourites and in holdings since $7 per share for a 10 year hold -$65 at time of writing], which uses trapped-ion quantum tech, climbed about 670%. These are stratospheric gains usually reserved for penny-stock pump-and-dump schemes, yet they occurred in companies that are ostensibly on the cutting edge of science. A major catalyst came when JPMorgan Chase announced a new $1.5 trillion tech initiative with an emphasis on “frontier technologies” like quantum, including up to $10 billion earmarked directly for quantum computing projects. That kind of endorsement from a Wall Street institution sent the quantum stocks into overdrive, as it signaled serious belief (and funding) in the sector’s future. It’s reminiscent of the dot-com days when a single analyst upgrade or telecom partnership announcement could double a stock overnight.

But as with all bubbles, it’s crucial to peek under the hood. Do these valuations make sense? In most cases, not by traditional metrics.

Rigetti, for example, had a market cap of around $17.8 billion in late 2025 – despite trailing 12-month revenue of less than $8 million.

In Q2 2025, Rigetti’s sales declined to a mere $1.8 million, while operating losses swelled to $20 million as they poured money into R&D. In short, this company (like many quantum startups) is pre-revenue, let alone pre-profit, yet is being valued like a successful mid-cap tech firm on hopes of future breakthroughs. One analyst flatly called Rigetti’s valuation “divorced from reality,” noting its price-to-book ratio was 25× (versus ~3× for the semiconductor industry average). To cap it off, even Rigetti’s CEO cashed out some shares during the frenzy, a move often seen as a red flag about exuberant pricing. This pattern is not unique to Rigetti – IonQ and others also trade at lofty multiples relative to their modest early revenues.

So why are smart people, including heavy-hitter investors (some billionaires have indeed been “piling into” IonQ and peers), willing to pay such prices? The answer is the potential TAM (Total Addressable Market) and the fear of missing a paradigm shift. A widely cited projection estimates the quantum computing market could grow from about $1.3 billion in 2024 to $170 billion by 2040. That’s a 130× increase in market size, reflecting an assumption that by 2040 quantum computers will be a mainstream tool for cloud computing, national labs, and large enterprises. If that comes true, the leading quantum players of today could be the Googles and Amazons of the future, and their current valuations would seem trivial in hindsight.

It’s a huge “if,” of course – a lot needs to happen, scientifically and commercially, to reach that point. But the mere possibility is enough to draw speculative capital. With governments viewing quantum computing as strategically critical (the U.S., EU, and China are all funding national programs in the billions), there’s a sense of inevitability that this tech will mature, even if it takes a decade or more.

In the meantime, the sector’s news flow oscillates between breakthroughs and setbacks. On one hand, companies keep announcing incremental advances: Rigetti recently demonstrated a 36-qubit system with improved fidelity (99.5% two-qubit gate fidelity, a key performance metric). They also won contracts like a $5.8 million Air Force deal to work on quantum networking, suggesting real interest from government clients. IonQ has been touting progress in stabilizing its trapped-ion qubits and signing partnership deals with firms like Dell and Airbus to explore quantum use-cases. D-Wave continues to carve a niche with its quantum annealing systems used for specific optimization problems in industry. These are meaningful steps forward. On the other hand, practical, error-corrected quantum computing that outperforms classical computers on versatile tasks is still out of reach. Every company in this space faces enormous technical hurdles in scaling up qubit count and reducing error rates. It’s entirely possible that some of today’s leaders will hit a wall or be leapfrogged by a new approach (remember, early PC makers like Commodore and DEC didn’t end up dominating the computing industry). The current “quantum bubble”, as some call it, means that if any bad news hits – say, a failure to meet a milestone or a funding shortfall – these stocks could implode just as fast as they exploded. For now, though, the external validation keeps coming. Big Tech is also in the quantum race: IBM, Google (Alphabet), Microsoft, Amazon – all are investing heavily in quantum R&D (IBM already offers cloud-accessible quantum processors; Google famously demonstrated a “quantum supremacy” experiment in 2019). These incumbents have deep pockets and existing cloud customer bases, which could allow them to dominate once the tech is viable. That’s a competitive threat to pure startups, but many optimists see it differently: if the tech giants are pouring money in, it legitimizes quantum computing’s promise and could spark acquisitions of the smaller players at high premiums. It’s somewhat reminiscent of the early internet era, where a bunch of small web companies rose and fell, but ultimately giants (some existing, some newly formed) took the lead. Importantly, the public market speculation in quantum is a sideshow to the strategic race among nations and companies to actually achieve quantum capabilities. In this sense, a boom-bust in quantum stocks wouldn’t kill the field; the investments (from governments, VCs, and corporations) will likely continue, given the stakes involved. As with AI, it might be a case where a bubble usefully “over-finances” the sector, funding lots of research, out of which a few winners emerge who justify the collective spend.

In summary, quantum computing investments today are a high-risk bet on a possibly revolutionary payoff. They epitomize the theme of this blog: even if there is a bubble, many believe it’s worth it. The rationale is that the upside of getting in early on a world-changing technology outweighs the downside of some (perhaps many) false starts. Investors just need to be prepared for extreme volatility and the real possibility that some companies won’t survive the long winter that likely precedes spring in quantum tech. Why This Bubble Might Keep Inflating

By now it’s clear that there are bubble-like characteristics in AI, robotics, and quantum markets – yet there are also strong arguments that we’re in a long-term innovation cycle that is still in its early to middle innings. What could allow the current tech investment boom to continue rather than imploding imminently, as past bubbles have? Here are a few key reasons experts and investors cite for believing the “bubble” still has room to run:

Unprecedented Technological Potential: The technologies in question – AI, automation, quantum – genuinely promise to reshape the world economy. We’re not talking about Beanie Babies or tulips; these are general-purpose technologies. AI, in particular, is often called the “fourth industrial revolution” or the next electricity. Its impact could be ubiquitous across industries. Because the upside is so enormous, investors are willing to pay forward years of growth. As Google’s CEO Sundar Pichai put it, “The risk of overinvestment is less than the risk of underinvesting” in AI. In other words, missing out is seen as the bigger mistake. This mindset means capital will likely keep chasing these tech themes, even at the cost of short-term bubbles, to ensure one is not left behind.

Strong Economic and Policy Tailwinds: Unlike 1999, when the Fed was raising interest rates and trying to cool things off, the current macro backdrop is turning supportive. Inflation has been moderating and many expect interest rates to stabilize or even fall, which is generally favorable for growth stocks. Moreover, governments themselves are spurring the tech boom: AI is a national priority in many countries. For instance, the U.S. government has been investing in AI research and considering subsidies for AI chip manufacturing; China’s government is famously pouring money into AI and robotics to lead the next tech era. The geopolitical competition (and fragmentation) is actually increasing spending – nations and companies feel they must invest in AI and advanced computing to stay competitive. A notable trend is de-globalization: countries want their own AI cloud infrastructure and domestic robotics supply chains for strategic security. This has meant duplicative investments – e.g., multiple nations each building AI data centers – effectively pumping more capital into the sector than if it were all globalized. Such a policy environment makes it less likely that investment will abruptly dry up; there’s a quasi “arms race” dynamic prolonging the boom. Not Everyone Is a Believer Yet: Curiously, one argument that the bubble isn’t at its peak is that there remains widespread skepticism and uneven participation. In true manias (like housing in 2007), nearly everyone is convinced “this time is different” right before the fall. With AI, you still have many respected voices warning about hype, and many investors under-allocated (and painfully aware of it). As one fund manager quipped, the difference between a bull market and a bubble is whether you’re invested in it or not. There’s some truth there: those who missed the AI rally call it a bubble, those who rode it call it a paradigm shift. The reality is a bit of both, but the fact that skepticism persists means we haven’t reached the euphoria phase where caution is thrown entirely to the wind. Bubbles usually burst when the last skeptic capitulates and “greater fool theory” stops finding new fools. We may not be there yet for AI. In Mike Fox’s view (head of equities at Royal London AM), “the level of AI exuberance is not yet at internet [bubble] levels… Bubbles burst when everyone believes in a new paradigm… not when there is widespread skepticism as there is today.”. This suggests a certain resilience – there are still investors on the sidelines who might jump in on any pullback, providing support and extending the cycle.

Corporate Earnings Are (Slowly) Catching Up: As discussed earlier, the big tech companies leading this boom are showing real earnings growth from their AI endeavors. Microsoft, Google, Meta, and Amazon each delivered solid or record earnings in recent quarters while ramping up AI. That indicates their core businesses are benefiting – e.g., Meta said AI recommendations increased user engagement and ad prices on its. If corporate profits continue to rise, it provides fundamental justification for at least a portion of the valuation surge. Moreover, the order backlogs for AI infrastructure are huge: Nvidia can’t make GPUs fast enough; cloud providers report unprecedented demand for AI computing services. ABB’s CEO noted they see “trillions in [AI-related] investment” coming but a constraint in physical capacity to implement it all. In other words, the spending is likely to continue for years just to fulfill currently identified needs – which could keep revenue flowing to the key companies in the ecosystem, sustaining their share prices. So long as these companies produce some tangible results (even if not fully proportional to investment yet), investors may remain patient.

Innovation Begets Innovation: We’re in a phase where breakthroughs in one domain (say, a new AI model) can spur advances in another (like better robots or new chip architectures), which then feed back into further AI improvements. This positive feedback loop can create self-fulfilling optimism. A practical example: AI advancements require more powerful chips, so companies like Nvidia invest in new GPU designs and chip startups get funding; those better chips enable even more capable AI models; those models, in turn, can help design new materials or optimize factory robots; those robots improve productivity and corporate margins, giving more resources to invest in AI. And so on. It’s an innovation flywheel that can drive an economic boom. Historically, such periods (think 1920s electrification or 1950s automotive/highway expansion) can see extended bullish cycles, even if punctuated by corrections. If AI, robotics, and quantum tech indeed reinforce each other’s progress, we could be looking at a multi-decade secular trend that lifts markets more than it crashes them. At least that’s the long-term bull case.

Contained Risk to the Financial System: As mentioned, the current boom doesn’t appear to threaten financial stability in the way, say, the subprime mortgage bubble did. Policymakers like the Bank of England have warned that an AI-driven market correction is a risk, but they also acknowledge it’s primarily a risk to some investors’ portfolios, not to banks or the payments. The U.S. Fed isn’t about to hike interest rates solely to pop an AI stock bubble (if anything, the government wants to foster tech leadership). Without a forced intervention or credit crunch, bubbles can inflate longer than expected. This is essentially what CEPR economists concluded: as long as the AI boom is equity-financed, regulators may well “let it run,” tolerating a later bust in exchange for the innovation. Knowing that, investors might be emboldened – believing that central banks won’t step on the brakes hard unless inflation or systemic risks emerge elsewhere. It’s a risky game, but it’s how many are justifying pushing tech valuations to extremes.

Add these factors up, and it paints a picture of a bubble that might deflate gradually or plateau rather than burst overnight. We could see, for instance, periodic 10-20% corrections in tech stocks that shake out the most speculative money, followed by another upcycle as fundamentals catch up and new innovations (maybe GPT-5, or a big quantum milestone) rekindle excitement. In fact, some market watchers predict an “ebb and flow” rather than a one-time pop: periods of hype and high returns followed by pullbacks and consolidation, repeating as the technology.

This would be more akin to how the smartphone or cloud computing booms played out in the 2000s/2010s – not without volatility, but ultimately an upward trajectory – rather than the sudden boom-bust of the dot-coms. Only time will tell, of course. Bubbles are usually obvious in retrospect and murky in the moment. But it’s fair to say the current environment has some unique sustaining forces.

Risk vs. Reward: Why Betting on the Tech Revolution (Carefully) Might Be Worth It

All this leads to the final consideration: given the evident risks of frothy valuations and possible downswings, why are so many investors convinced that staying in AI/robotics/quantum is worth the potential pain? What makes this bubble (if it is one) different, such that even a cautious investor might allocate some capital here?

There are a few compelling arguments:

1. The Winners Could Be Game-Changers: In transformative technological shifts, a few big winners often account for the lion’s share of gains. Think of the internet era – yes, many dot-coms failed, but catching even one Amazon or Google early would have outweighed dozens of busts in a portfolio. The same logic applies now. If AI truly is the new electricity, the companies that become AI’s standard-bearers (be it software platforms, chipmakers, or AI-driven service providers) could see decades of growth and trillions in market cap appreciation. Missing those would be devastating to one’s long-term returns. As venture capitalists like to say, you only need to hit one grand slam to make up for a bunch of strikeouts. Public market investors are echoing that sentiment: they’d rather risk some losses than miss the next Nvidia or next Tesla. This asymmetric payoff – limited downside (you can only lose what you invest) versus potentially enormous upside – makes a calculated bet on the tech revolution attractive, especially if diversified across several leading contenders.

2. Stronger Foundations than Past Bubbles: Unlike, say, the crypto craze or the cannabis stock bubble, the AI/automation boom is grounded in clear use cases and immediate productivity gains, even if at times overhyped. Many of the companies involved are profitable or at least have revenue streams. This means investing in them isn’t purely speculative; you’re investing in existing businesses that are likely to survive even if the market rerates their multiples. For instance, Microsoft and Alphabet aren’t going anywhere; they have diversified businesses, and their AI investments augment already robust profitability.

If you buy such companies for their AI exposure, the worst-case scenario might be a stock pullback, not a bankruptcy.

This is very different from buying pets.com in 1999 or a no-name SPAC in 2021. Even smaller players like IonQ or UiPath (robotic process automation) have decent balance sheets due to earlier fundraising and can weather a downturn if needed. In short, the quality of assets in this “bubble” is higher. As one analysis pointed out, in 2000 tech stocks traded at over 2× the valuation of the broad market, whereas now the tech sector is around 1.3× – elevated, but not completely detached. Tech companies also carry less debt and more cash than most, giving them resilience. This reduces the tail risk of permanent capital loss, tilting the risk/reward calculus in favor of staying invested.

3. Innovation Bubbles Yield Long-Term Benefits: From a societal and even investor perspective, there’s an argument that innovation-driven bubbles aren’t entirely bad. They effectively finance R&D and infrastructure that might not get built otherwise. Yes, some investors lose money, but the overall economy gains new technology and productivity enhancements.

For the investor, one can be on the winning side of that equation by focusing on fundamental progress. For example, even if a dozen quantum startups fail, if you held stock in one that masters quantum computing, your gains could offset all losses.

Meanwhile, the broader advancements lift other investments too (AI making non-tech companies more efficient, etc.). Economists Danielsson and Macrae note that policymakers might even tolerate an AI bubble for the greater good of innovation – the subtext being that those who invest in innovation, even at high prices, help drive it forward and can capture outsized gains if they ride the right horses.

Jeff Bezos’s remark also resonates here: an “industrial bubble” can lay the groundwork for society’s next leap. Investors with a long horizon may accept volatility in exchange for being part of that leap.

4. Diversification and Adaptation Can Mitigate Risks: You don’t have to go all-in on the frothiest names to participate in the trend.

Many seasoned investors are focusing on picks-and-shovels and diversified plays. For instance, rather than gambling on a pre-revenue AI startup, one might invest in Nvidia (providing the hardware every AI model needs) or Taiwan Semiconductor Manufacturing Co. (making the chips) or ASML (lithography machines for chip production).

These companies benefit from the AI boom indirectly and have tangible moats.

Similarly, instead of betting on which quantum startup wins, some prefer owning shares of IBM or Honeywell, which have quantum programs but also stable core businesses.

This way, even if the pure hype names collapse, your portfolio might just take a modest hit while still gaining from the general sector growth. Additionally, investors can rebalance – taking some profits after big run-ups and reallocating to underappreciated areas (some are rotating into robotics or industrial automation stocks, for example, which haven’t spiked as much as pure AI software stocks). By staying agile and diversified, one can manage the bubble risk and still be exposed to the revolutionary upside. 5. The Cost of Sitting Out Is Too High: This is more psychological, but very real on Wall Street. Fund managers are paid to generate returns, and if “everyone else” is making a killing on AI, the pressure to not underperform becomes intense. In other asset classes too – consider a real estate investor watching property values skyrocket due to AI-fueled tech growth in a city, or a bond investor seeing credit risk fall for companies adopting AI to improve profits – the ripple effects of the tech boom are everywhere.

Being entirely on the sidelines means you risk underperforming the market significantly if the boom continues.

Many learned this the hard way in the last decade when tech stocks led the market; those who avoided tech on valuation concerns missed out on huge gains and eventually had to capitulate and buy in at higher prices. In the current scenario, even conservative investors feel they need at least some exposure.

As the saying goes, “you don’t have to get the timing exactly right if your thesis is right.” 

If you believe AI and related tech are truly transformative, then over a 5- or 10-year period that secular growth can bail you out of even a bad entry point today.

For example, someone who bought Amazon or Nvidia at their peaks in past cycles still made multiples on their investment if they held on for a few years. Thus, many conclude that enduring a potential 20-30% drawdown is an acceptable price for being in position for a 5-10x gain longer-term. It’s a risk worth taking in their view.

None of this is to suggest one should be reckless. There will be volatility, and not every company will justify its valuation – some will go bust or languish for years. Caution and due diligence are essential. It’s also wise to size positions such that you can sleep at night and won’t be forced to sell at a bottom. But with those caveats, there is a coherent case that investing in the AI/robotics/quantum revolution is rational, even at seemingly high valuations, because the potential reward is so extraordinary and the momentum so powerful. As Sundar Pichai warned early in 2025, the biggest risk in AI might be “missing out” – a sentiment clearly shared by many investors fueling today’s trends.

Navigating the Tech Bubble Without Missing the Big Picture

We are living through a remarkable moment when science-fiction-like technologies are becoming reality.

Artificial intelligence is writing code and articles; robots are working in factories and warehouses; quantum computers are edging closer to solving problems once thought impossible.

It’s no wonder markets have reacted with enthusiasm – perhaps overenthusiasm at times. By many measures, parts of the market are in bubble territory: sky-high valuations, speculative frenzy, and a faith in future outcomes that isn’t matched by present earnings. History tells us that such periods do not last forever, and a correction or shakeout is likely on the road ahead.

However, history also shows that when genuine technological revolutions are underway, the long-term trend after the bust is upward and to the right. The dot-com bust was brutal, but it paved the way for the internet giants of today. The railroad mania of the 1800s ended in bankruptcies, but it left a nation connected by steel rails. In the same way, even if an AI or quantum bubble “pops,” it may be more of an air being let out slowly, followed by years of sustained growth for the true winners. And crucially, because today’s boom is backed by real use cases and not dangerously leveraged, its unwinding – should it come – might resemble a healthy rotation or a sector decline, not an economy-wide crisis. As the IMF’s economist noted, a dot-com style bust in AI is possible but would likely “not crater the economy” – it would mainly mean some investors lose money, while the technology itself marches on.

For investors, the challenge is balancing short-term risk management with long-term vision. It’s entirely sensible to take profits or avoid obviously frothy microcaps; at the same time, trying to time the exact peak of a transformative trend is notoriously difficult. Many seasoned hands advocate staying invested in quality companies driving the revolution, but doing so with eyes open to volatility. As one fund manager said, keep an open mind – we could be in a bubble and AI could be the most important trend of our time, both can be true. The key is to ensure your portfolio can survive the journey. That might mean holding a broad mix of tech and non-tech, using hedges, or simply being mentally prepared for ups and downs.

In the end, those who carefully ride out the waves of this period could find themselves on the forefront of owning pieces of the future economy – an economy likely more automated, intelligent, and computationally powerful than anything we’ve seen. The risk of losing some money in the interim is the toll for a chance at outsized gains. For many, that’s a bet worth making, provided it’s done with prudence and perspective. Unlike prior bubbles built on fluff, this one is built on world-changing ideas. And even if the road gets bumpy, the destination could indeed be spectacular. As investors, blending optimism with caution – enjoying the ride and wearing a seatbelt, so to speak – is probably the wisest course. After all, the goal is not just to survive a bubble, but to be positioned to thrive in whatever new world emerges once the speculative dust settles.