AI Bubble: Experts Warn of Overvaluation and Failure to Monetize

AI Bubble: Burst or Transformation? There’s been a lot of talk lately about whether we’re in an AI bubble. I recently came across a post and also read Sam Altman’s comments comparing today’s AI market to the dot-com bubble. Both made me reflect on where we really are. Here’s my perspective: 🔹 Yes, valuations are inflated and some startups are running on hype rather than sustainable models. A correction is inevitable. 🔹 But AI itself is not a bubble. Just like the internet didn’t vanish after the dot-com crash, AI is too transformative to fade away. 🔹 The shakeout will be healthy. Weak players will disappear, and the ecosystem will become stronger and more grounded. 🔹 The real winners will be those who combine strong AI tech with solid business fundamentals. So rather than seeing this moment as a “burst,” I see it as AI maturing — moving from hype to real, long-term impact. 🌍 AI isn’t ending. It’s just beginning to find its true footing. #AI #Technology #Innovation #Future

The AI cost paradox is real: While token prices plummet 10x annually, total AI expenses are skyrocketing. Just read Christopher Mims' WSJ piece revealing why AI is becoming MORE expensive, not cheaper. The culprit? "Reasoning" models that burn through 100,000+ tokens for complex tasks versus 500 for basic chatbot responses. Key reality check for enterprises: 📊 Legal document analysis: 250,000+ tokens 🤖 Multi-step agent workflows: 1 million+ tokens 💰 Result: Some AI startups seeing margins drop from 90% to 80% This validates what we're seeing at Pay-i: enterprises desperately need visibility into agent economics. When a single workflow can consume millions of tokens, you can't manage what you can't measure. The article highlights companies like Notion losing 10 percentage points of profit margin to AI costs. Meanwhile, "vibecoding" startups are watching users burn through monthly credits in days. Three critical takeaways for executives: 1. Unit economics matter more than per-token pricing 2. Agent complexity directly impacts your bottom line 3. Without ROI measurement, you're flying blind As Theo Browne (T3 Chat CEO) notes: "The arms race for who can make the smartest thing has resulted in a race for who can make the most expensive thing." The solution isn't avoiding AI innovation. It's gaining complete visibility into which agents deliver value and which destroy margins. What's your biggest challenge with AI economics right now? #GenAIROI #AIGovernance #EnterpriseAI #DigitalTransformation #AIAgents #FinOps #CFO

**Is the AI Spending Bubble Looming Over Our Markets?** The hype around artificial intelligence (AI) is palpable, and recent trends suggest that we might be approaching an AI spending bubble. 🚀 According to Axios, global AI investment is projected to skyrocket to $1.6 trillion by 2025, driven by businesses eager to incorporate AI into their operations. Yet, as companies pour billions into AI technologies, questions arise: Are we investing in sustainable growth, or are we setting ourselves up for disappointment? Interestingly, a recent study by McKinsey found that only 20% of AI projects yield substantial financial returns, raising concerns about a potential market correction. 📉 Companies might be rushing into AI adoption without fully understanding its implications, potentially leading to overspending without adequate return on investment. Moreover, various analysts suggest that if the growth trajectory of AI doesn't match the investment surge, we could see a significant market shift, reminiscent of the dot-com bubble. The landscape is evolving rapidly, and while the potential for AI is immense, a prudent approach to spending could safeguard our economic future. As we navigate these uncharted waters, it's crucial to balance enthusiasm with caution. Let’s invest wisely! 💡 #AI #Investment #MarketTrends #EconomicGrowth #Sustainability

The AI Paradox: Why We Don’t See AI in Productivity (Yet) Artificial Intelligence is everywhere - in our apps, news feeds, and workplaces. We’re told it’s a revolution on par with electricity or the internet. Investments are surging, companies are reorganising, and public fascination is sky-high. But here’s the paradox: if AI is so transformative, why don’t we see it in the productivity statistics? 🔹 The Productivity J-Curve  Like electricity and the internet before it, AI comes with a delay. The “J-curve” means heavy upfront investment in infrastructure and reskilling before real productivity gains appear. 🔹 History’s Lesson  The incandescent lamp was invented in 1879, but electricity didn’t significantly boost productivity until the 1920s. It took decades to reach critical adoption levels - a reminder that change is slower than hype. 🔹 Why AI May Be Different  Unlike electricity, AI is spreading at record speed. Citi Research finds AI-related investment is already outpacing the 1990s internet boom. The gains may arrive sooner this time - but we’re still in the flat part of the curve. 🔹 The Human Roadblock  Technology isn’t the main barrier - people are. Surveys show 44% of workers say their company is “trying to adopt AI,” but only 22% think their firm has a clear plan. Training, strategy, and cultural change are the real bottlenecks. 🔹 The Prize Ahead  Once adoption matures, productivity growth could rise by 0.5–1.5 percentage points annually for a decade - a seismic economic shift on par with the internet boom of the 1990s. Takeaway: The absence of an AI productivity boom isn’t proof of hype. It’s the predictable early stage of the J-curve. The real question is not if AI will deliver - but whether businesses and society will be ready when it does. This post draws on insights from Citi Research’s report, Productivity & the AI Revolution (Sept 2025), which I’ve attached here for reference. Disclaimer: This post is for information only and does not constitute financial advice. Please do your own research before making decisions.

The AI Paradox: Why We Don’t See AI in Productivity (Yet) Artificial Intelligence is everywhere - in our apps, news feeds, and workplaces. We’re told it’s a revolution on par with electricity or the internet. Investments are surging, companies are reorganising, and public fascination is sky-high. But here’s the paradox: if AI is so transformative, why don’t we see it in the productivity statistics? 🔹 The Productivity J-Curve  Like electricity and the internet before it, AI comes with a delay. The “J-curve” means heavy upfront investment in infrastructure and reskilling before real productivity gains appear. 🔹 History’s Lesson  The incandescent lamp was invented in 1879, but electricity didn’t significantly boost productivity until the 1920s. It took decades to reach critical adoption levels - a reminder that change is slower than hype. 🔹 Why AI May Be Different  Unlike electricity, AI is spreading at record speed. Citi Research finds AI-related investment is already outpacing the 1990s internet boom. The gains may arrive sooner this time - but we’re still in the flat part of the curve. 🔹 The Human Roadblock  Technology isn’t the main barrier - people are. Surveys show 44% of workers say their company is “trying to adopt AI,” but only 22% think their firm has a clear plan. Training, strategy, and cultural change are the real bottlenecks. 🔹 The Prize Ahead  Once adoption matures, productivity growth could rise by 0.5–1.5 percentage points annually for a decade - a seismic economic shift on par with the internet boom of the 1990s. Takeaway: The absence of an AI productivity boom isn’t proof of hype. It’s the predictable early stage of the J-curve. The real question is not if AI will deliver - but whether businesses and society will be ready when it does. This post draws on insights from Citi Research’s report, Productivity & the AI Revolution (Sept 2025), which I’ve attached here for reference. Disclaimer: This post is for information only and does not constitute financial advice. Please do your own research before making decisions.

The AI Paradox: Why We Don’t See AI in Productivity (Yet) Artificial Intelligence is everywhere - in our apps, news feeds, and workplaces. We’re told it’s a revolution on par with electricity or the internet. Investments are surging, companies are reorganising, and public fascination is sky-high. But here’s the paradox: if AI is so transformative, why don’t we see it in the productivity statistics? 🔹 The Productivity J-Curve  Like electricity and the internet before it, AI comes with a delay. The “J-curve” means heavy upfront investment in infrastructure and reskilling before real productivity gains appear. 🔹 History’s Lesson  The incandescent lamp was invented in 1879, but electricity didn’t significantly boost productivity until the 1920s. It took decades to reach critical adoption levels - a reminder that change is slower than hype. 🔹 Why AI May Be Different  Unlike electricity, AI is spreading at record speed. Citi Research finds AI-related investment is already outpacing the 1990s internet boom. The gains may arrive sooner this time - but we’re still in the flat part of the curve. 🔹 The Human Roadblock  Technology isn’t the main barrier - people are. Surveys show 44% of workers say their company is “trying to adopt AI,” but only 22% think their firm has a clear plan. Training, strategy, and cultural change are the real bottlenecks. 🔹 The Prize Ahead  Once adoption matures, productivity growth could rise by 0.5–1.5 percentage points annually for a decade - a seismic economic shift on par with the internet boom of the 1990s. Takeaway: The absence of an AI productivity boom isn’t proof of hype. It’s the predictable early stage of the J-curve. The real question is not if AI will deliver - but whether businesses and society will be ready when it does. This post draws on insights from Citi Research’s report, Productivity & the AI Revolution (Sept 2025), which I’ve attached here for reference. Disclaimer: This post is for information only and does not constitute financial advice. Please do your own research before making decisions.

From Dot-Com to GenAI Bubbles: Failures and the Shape of the Future” 🚀 Every tech wave from the #DotCom crash to the rise of #CloudComputing and now #GenAI teaches us something about hype, adoption, and long-term value creation. In this article, I explore: 🔹 Why bubbles happen (and why they aren’t always bad) 🔹 The lessons we can carry from past failures 🔹 What the future might look like as #ArtificialIntelligence reshapes industries Would love to hear your thoughts on whether GenAI will fuel the next lasting transformation—or if we’re heading toward another cycle of overinflated expectations. 👉 Read here: https://lnkd.in/ggjpF26U #Technology #FutureOfWork #AI #Innovation #DigitalTransformation

AI is pegged as the 4th industrial revolution ·     “I’d rather risk billions rather than fall behind AI. If we end up misspending a couple of hundred billion dollars on AI, it’s going to be very unfortunate, but the risk is higher on the other side.” A classic case of FOMO (Fear Of Missing Out) by Marc Zuckerberg ·     Sam Altman has warned that “the frenzy of cash chasing anything labelled ‘AI’ can lead to inflated valuations and risk for many.” ·     “An AI bubble is quite possible,” Zuckerberg admitted ·     In a very recent study by Model Evaluation & Thread Research (METR) they tested a group of experienced software developers to perform coding tasks with or without AI tools. They chose coding as it is something that AI has largely mastered. What METR surprisingly found was that the developers had completed the tasks 20% SLOWER using AI tools than working without it If AI is a bubble and it will soon burst, the aftermath will be worse than the dot.com bubble bursting. AI-related investments have already surpassed what telecom reached at the peak of the dot-com boom. In 2025 alone, the largest U.S. tech companies, including Meta, have spent more than $155 billion on AI development. And, according to Statista, the current AI market value is approximately $244.2 billion There could be a silver lining here, as was the case with the dot.com bubble bursting, the Internet transformed the economy and led to some of the most profitable companies in human history despite the fact that it evaporated $5 trillion of market cap of the stocks involved and a lot of investors lost their shirts.

It is not an AI Bubble... I disagree that we are in a AI bubble. There is certainly trouble just around the corner, but I don't think we could characterise it as an "AI bubble". Yes, the economic insanity and vandalism of the US President will lead to very bad outcomes for America and hence the rest of the world: something between a deep recession and a depression. Yes, many stocks in America and Australia are overvalued. PE ratios of the S&P, NASDAQ and ASX etc are overinflated. And yes, that is likely to correct at some stage. There is a lot of irrational exuberance in the market that are keeping valuations high. Yes, war in Europe, Chinese ascendancy and US insanity is creating massive uncertainty and that will likely lead to an economic downturn.  However we can't blame AI for all this. AI is an enabling technology like electricity. In the age of steam, if there were just eight electricity-generating companies, then yes, their valuations would have been astronomical. Yes, like the rest of the market, AI stocks are overinflated. But I'd argue it's due to the background overvaluation plus the fact that AI investment money doesn't know where else to go. If there is a correction, will the PE ratios of the Magnificent 8 drop more than the average PE ratio of the S&P - I doubt it. The Internet infrastructure was largely cheap and decentralized. Buy 30 modems and you could start an ISP like OzEmail did. AI is centralized. You need a lot of capital, data centers and expensive machine learning expertise to create state of the art (SOTA) foundation models. It's a very different paradigm from electricity and the Internet. In the past, electricity and the internet were not largely identified as belonging to certain companies. Second generation unicorn companies like Facebook, Google, etc. were seen to be USING the Internet, not CREATING the Internet. Like the Internet, the true AI unicorns will be the innovators leveraging and monetising AI more broadly. Likely we haven't even seen the new mega AI companies yet. Will there be a stutter in the adoption of AI into business and the world? Maybe. Will AI be going away? No.

The AI Productivity Paradox: A Cubed Exploration of Efficiency https://lnkd.in/g22rqJk2 The Status Quo is Unsustainable in the AI Economy The rapid growth of AI is impressive, yet there’s a concerning disconnect with productivity. Currently, AI token consumption is surging at over 350%, while growth in U.S. GDP slows below 2%. With 95% of corporate Generative AI deployments falling short of expectations, the need for change is clear. Key Insights: AI’s Impact on Productivity: AI enhances addictive content and improves app experiences. Many organizations adopt AI without proper integration, leading to technical debt. Contextual Shift: Transition from traditional wood chopping to managing AI tools. Focus shifts to writing effective prompts and specifications. Three Core Problems: Resistance to new productivity frameworks. Navigating increasing levels of abstraction. Understanding AI’s commercial motives. Call to Action: Let’s embrace this transformation together. Share your thoughts on thriving in the AI economy! Source link https://lnkd.in/g22rqJk2