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AI anxiety has sent markets into a tizzy, but experts say the jitters will only ‘punish those chasing the froth’

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Major technology stocks tied to artificial intelligence took a sharp downward turn Tuesday, rattling markets and raising concerns the sector’s billion-dollar promises may not be bearing fruit as quickly as hoped.

Shares of Palantir Technologies, the data-analytics firm widely viewed as an AI bellwether, plunged more than 9%, its worst tumble since March, after prominent short-seller Andrew Left of Citron Research renewed his bearish stance. Other major names felt similar shocks, highlighting underlying investor doubts: Oracle, in the midst of aggressive AI investments and a strategic pivot that included mass layoffs in its cloud division, saw its shares drop nearly 6%. Chipmakers integral to the AI boom struggled as well: Advanced Micro Devices fell 5.4%, Arm Holdings lost 5%, and Nvidia, the sector’s dominant force, slid 3.5%.

SoftBank, whose outsize bets on AI have defined its recent strategy, dropped more than 7%—amplifying concerns about a broader tech correction and underscoring Wall Street’s uneasy relationship with the so-called next big thing. OpenAI CEO Sam Altman even admitted AI is in a bubble.

The abrupt selloff echoes broader skepticism about the sustainability of sky-high valuations seen in AI-focused companies. But experts say that while investors are right to be cautious, the underlying technology isn’t going away—and this is a short-term drop during a long-term transformation.

Behind the market jitters, a recent report from MIT said approximately 95% of company generative AI pilot programs resulted in “little to no measurable impact” on revenue or profits. While a handful of startups have thrived, the vast majority of corporate efforts have stalled, caught in flawed enterprise integrations and learning gaps. The research, encompassing 150 executive interviews, 350 employee surveys, and an analysis of 300 public AI deployments, paints a sobering picture: Outside exceptional cases, generative AI projects have yet to justify the vast spending across the sector.

MIT’s lead author, Aditya Challapally, told Fortune failure may lie less in the underlying tools than in enterprise execution, citing issues around workflow adaptation and resource allocation. In contrast, nimble startups have rapidly scaled revenues—validating the potential of the technology when well integrated, but also highlighting a gulf between hype and reality for larger companies.

“There’s no doubt that when MIT reports a 95% failure rate in AI pilot programs, it’s alarming,” Mike Sinoway, CEO of AI-powered search software company Lucidworks, told Fortune. “But the problem has less to do with the underlying technology and more with how companies are approaching it.

“In our own research, polling over 1,600 AI practitioners and leaders and validating this with bot analysis, we found 65% of teams are rolling out AI without the fundamental tech infrastructure in place,” he said. “Trying to build cutting-edge applications atop weak foundations is like building an F1 car on a go-kart engine—you simply won’t get results. So while a 95% failure rate might seem like a sign of a bubble, once organizations focus more on what AI actually needs to succeed, we’ll begin to see the traction everyone is expecting.”

Chase Feiger, CEO of Ostro, an AI-powered platform for life sciences brands, agreed current volatility is part of a typical tech cycle. “Talk of an AI bubble isn’t new,” Feiger told Fortune.

“Every major tech shift goes through a stage where hype runs ahead of business fundamentals,” he said. “Some companies are burning money on inference costs, offering ‘all-you-can-eat’ models that cost thousands to run but bring in only hundreds in revenue—a pattern reminiscent of Uber’s early years. That overinflation explains market caution, but the underlying technology isn’t overhyped. In health care, for example, AI is transforming drug development, patient care, and physician decision-making.

“The correction will come. But over the long haul, the winners will be those who prove AI delivers durable value in complex, high-stakes environments,” Feiger added.

Harvard professor Christina Inge told Fortune the duality at work is nothing new.

“Investors are right to be cautious,” she said. “Not every company claiming to be ‘AI-driven’ is creating real value; a lot of it is smoke and mirrors, with some tools amounting to incremental improvements on non-AI tech. Correction is inevitable, as history shows.

“But the technology isn’t going away. AI is already making a difference in health care, marketing, logistics, and finance. And we’re only scratching the surface. In the long run, I expect the impact of AI to rival the Industrial Revolution. There’s a lot of froth in the market right now, but the bigger story is just beginning. In other words: short-term bubble, long-term transformation.”

That view is echoed by Shay Boloor, chief market strategist at Futurum Equities.

“What we’re seeing isn’t a bubble, but the foundation of a new economy,” Boloor told Fortune. “There will be volatility—inevitable with a sector this hot—but the fundamental reality is every industry will be transformed by AI. Just look at Microsoft and Meta this quarter: Azure hit its biggest revenue numbers ever, Microsoft Cloud crossed $46 billion, and Meta monetized not just attention but intelligence, with 22% revenue growth and 38% profit growth, while spending $70 billion in capex. The demand is not hypothetical—it’s scaling now.

“We’re not at the peak of AI. We’re at an inflection point.”

Siamak Freydoonnejad, cofounder of Sprites AI, which makes an AI-powered marketing agent, says, however, deciding whether or not we’re in an AI bubble “misses the point” entirely.

“Stock prices may have outpaced fundamentals, but inside enterprises, AI is already infrastructure,” Freydoonnejad told Fortune.

“No one who’s seen campaign launch speed improve by 70% is going back to the old way,” he said. “Some vendors did slap ‘AI’ on legacy products to cash in, but those valuations will be corrected—and deservedly so. What matters is which firms are using AI not as a shallow trend but as the basis for their entire product. Real efficiency gains are showing up for companies embedding AI deeply in their workflows. The market is about to sort out those with substantive results from those selling only promises.”

Omar Kouhlani, CEO of Runmic, which uses AI to design revenue strategies for sales teams, told Fortune infrastructure spending reveals the true momentum.

“Big Tech just raised AI spending guidance to $360 billion–plus for 2025, up sharply from previous estimates. I watch those numbers more closely than day-to-day share price changes,” he said.

“This isn’t a rejection of AI, it’s a market becoming more selective,” Kouhlani continued. “The crash is separating real AI revenues from companies that only have AI PowerPoints. We’re not in another dotcom bust. The infrastructure is being built now, and expectations are adjusting faster than the technology itself.”

Usha Haley, the W. Frank Barton Distinguished Chair in International Business and professor of management at the Barton School of Business at Wichita State University, argues that cycles of bubbles and corrections are intrinsic to tech revolutions. “Historically, every breakthrough technology comes with bubbles,” Haley told Fortune. “AI is already delivering productivity gains, even as it erodes some jobs. We’ll see some correction and consolidation, but not a collapse. The strongest players will emerge into a changed landscape. Regulation and stochastic shocks could alter outcomes, but competitive environments—not monopolies—will point to future leaders.”

Fabian Stephany, a lecturer at the University of Oxford, sees evidence for both sides: “To some extent, yes, there is an AI bubble. But long-term fundamentals are exceptionally strong,” he told Fortune. “Many firms use AI for marketing more than substance, which has inflated valuations. Yet stock-market gains this year are overwhelmingly linked to real advances in AI at companies like Nvidia, Meta, Microsoft, and Broadcom. Nvidia alone accounts for 26% of the S&P’s advance, underscoring real market transformation.”

David Brudenell, executive director at Decidr, which builds an AI-powered operating system for businesses to automate workflows, told Fortune that “correction is necessary” as it “separates speculation from structural value.” And David Russell, global head of market strategy at TradeStation, agreed: “Pullbacks are normal after rallies stall.

“Major players like Palantir and Microsoft failed to hold breakouts after strong earnings. That’s a sign the good news may be priced in,” Russell told Fortune. “Markets move ahead of fundamentals, but excessive prices punish those chasing the froth. In the weeks ahead, sentiment could shift to other macro factors.”

The expert consensus is clear: While stocks have pulled back, the fundamentals behind AI remain strong. Most believe the recent rout is an overdue market sorting—separating hype from reality, speculation from enduring value. Even MIT’s cautious findings are seen as a spur rather than a death knell.

Now, all eyes will turn to Nvidia, which reports quarterly earnings next week. But broadly speaking, what the market is experiencing isn’t a sign of crisis, but a marker of growing pains.

For this story, Fortune used generative AI to help with an initial draft. An editor verified the accuracy of the information before publishing. 

This story was originally featured on Fortune.com



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The investment of the year and AI like fire

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As we all know, there’s a lot of talk about AI lately. Some of it is pretty hyped-up (“it will be a disaster!” vs. “heaven is just around the corner!”), but IO+ is here to select the pearls from the rubbish. Pearl of the week is the interview Carlo van de Weijer had with the Possible Futures Podcast. Van de Weijer is basically optimistic, but with a realistic perspective. “Technology has always been the main thing that saves our future,” he argues. “Every breakthrough created new problems, but also the tools to solve them.”

AI won’t change the basics of human life, Van de Weijer expects. “It won’t rewrite the rhythms of human existence. It just makes them smoother.” Still, he warns against complacency. “AI is like fire. Fire gave us warmth and cooking, but it could also burn down your house. The difference is that AI moves much faster and can continually improve itself. That’s why we need regulation.” Van de Weijer also discusses jobs lost & found, increased productivity, and its impact on education. More here.

ASML

The news leaked on Sunday afternoon and was made official on Wednesday: ASML has acquired more than 10% of the French AI company Mistral for €1.3 billion. Hardware is embracing software; iron into AI. We were on top of it with the first news, the nuances from ASML itself, and an analysis of this rather surprising move. We highly recommend the analysis, in which we present the eight most important arguments to show that this seemingly illogical step is actually very logical. “Strategically brilliant,” even, as we heard from ASML itself.

Officially, the goal of this “strategic partnership” is to explore the use of AI models in ASML’s product portfolio and in research, development, and operations. Simply put, it will enhance ASML’s large machines, making them better and more reliable, as well as the research that will lead to the successors of these mega-devices. But that’s not all, because… well, read for yourself 🙂

asml mistral logo

Gerard & Anton Community

Don’t want to miss anything about the startup ecosystem of the high-tech manufacturing industry? Then subscribe to the newsletters of the Gerard & Anton community. Every month, you’ll receive an overview of the highlights – check out yesterday’s edition here.

The Gerard & Anton monthly newsletter is a great way to get a flavor of one of the most active startup ecosystems in Europe. It follows raw ideas (via Drinks, Pitches & Demos), bold visions (via Brabant Bits & Bytes), early successes (via the G&A Awards), lifetime achievements (via the Piek Awards), and all other reasons to celebrate (via the Founders Dinner, a.o.). In addition to all that, Gerardanton.com/news provides your daily update on relevant developments in the ecosystem.

Watt Matters in AI

We are approaching November 26, the day we will be holding our Watt Matters in AI conference. Everything about the exorbitant energy consumption of AI systems, but above all: what solutions are there to prevent this from getting completely out of hand? We have now secured seven very interesting speakers: a guarantee that by the end of the day you will be completely up to speed on this topic. Tickets are available via Watt Matters in AI.

WMIAI

A podcast every day

We’ll keep saying it: every morning at 6:30 a.m. (on weekdays), a new podcast is waiting for you. In it, our AI colleagues Oliver and Shelby discuss the two most interesting topics of the day. This makes the IO+ Daily the ideal way to fill your head with some optimistic news from the world of innovation and technology.

Our other newsletters

Thank you for reading this newsletter. But we have more to offer. Signing up is very easy (just click on the name of the newsletter):

A selection of other highlights from this week:

Enjoy your Sunday and don’t forget that a new episode of IO+ Daily will be waiting for you tomorrow morning at 6:30 a.m.



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Minister Bae targets 200,000 GPUs by 2030 for AI growth – 조선일보

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Minister Bae targets 200,000 GPUs by 2030 for AI growth  조선일보



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Unlocking Human Potential With Technology

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In the quiet revolution happening at the intersection of artificial intelligence and disability support, we’re witnessing something exciting: technology finally keeping pace with human ingenuity. The 1.5 billion people worldwide living with disabilities are not just beneficiaries of this transformation. They’re driving it, reshaping how we think about capability, autonomy and the very definition of what it means to be human in an increasingly digital world.

The psychological impact of this shift cannot be overstated. For too long, assistive technology has been clunky, stigmatizing and one-size-fits-all. But AI is changing that narrative, offering personalized solutions that adapt to individual needs rather than forcing individuals to adapt to technology’s limitations. This represents more than technological progress. It’s a radical reimagining of human potential through a hybrid lens which harnesses the complementarity of natural and artificial assets to their respective full extent.

Transformation In Action

Consider Polly, an AI-powered device developed by former NASA engineer David Hojah through his company Parrots Inc. Designed to fit onto wheelchairs, Polly uses machine learning to provide real-time voice assistance, cognitive support and telecare solutions that learn from each interaction. This isn’t just about convenience—it’s about cognitive sovereignty, allowing users to maintain independence while receiving the support they need.

The educational landscape is experiencing similar breakthroughs. AI-driven tools like conversational agents, predictive text and personalized learning platforms are supporting students with cognitive, speech, or mobility disabilities by adapting to user preferences and learning from interactions. These systems don’t just accommodate difference—they celebrate it, creating learning environments that respond to neurodiversity as a strength rather than a deficit.

Perhaps most remarkably, AI is revolutionizing communication access. Speech-to-text transcription, sound identification and audio separation technologies are breaking down barriers for people with hearing loss, while visual recognition systems are providing unprecedented independence for those with vision impairments. Microsoft’s partnership with Be My Eyes exemplifies this approach, using high-quality, disability-representative data to improve AI accuracy and reduce bias.

Supporting Supporters

The ripple effects extend far beyond individual users. Caregivers, family members and healthcare providers are finding that AI-powered assistive technologies reduce their emotional and physical burden while improving care quality. Smart monitoring systems can track health metrics, predict potential issues and provide early interventions, allowing caregivers to focus on human connection rather than constant vigilance.

Integrated AI assistants are moving beyond standalone apps to provide seamless, intuitive support that feels natural rather than clinical. This shift represents a psychological breakthrough for caregivers, who often struggle with the tension between wanting to help and fearing they’re enabling dependency. AI systems that promote autonomy while ensuring safety resolve this dilemma beautifully. The next stage are apps that offer a 360º approach, addressing the wellbeing of the caregiver and those in their care 24/7.

Shadows: Risk And Reality

However, the path forward isn’t without its pitfalls. The same AI systems designed to liberate can also marginalize if not carefully designed. Tools like sentiment analysis and toxicity detection models often exhibit biases toward people with disabilities, perpetuating harmful stereotypes embedded in training data as shown by research from Penn State.

More concerning, studies show that AI systems like ChatGPT demonstrate bias against disability-related resumes, potentially limiting employment opportunities for those who most need technological support to level the playing field. The cruel irony is that the very systems designed to promote inclusion can inadvertently reinforce exclusion.

Privacy concerns loom large as well. AI systems require vast amounts of personal data to function effectively, raising questions about who controls this information and how it might be used. For a community that has historically faced discrimination, the surveillance potential of AI assistive technologies represents a genuine threat to autonomy and dignity.

There’s also the risk of over-reliance. While AI can provide incredible support, it shouldn’t replace human judgment or community connection. The goal isn’t to create AI-dependent individuals but to use technology as a bridge to greater human engagement and self-determination.

The Business Case For Inclusive Innovation

While all of these examples are interesting illustrations of prosocial AI in practice, the double beauty of this transformation lies in its economic sustainability. The global assistive technology market is projected to reach $26.8 billion by 2024, driven not just by moral imperatives but by genuine market demand. Companies like Microsoft, Google and Apple aren’t investing in accessibility features out of charity, they recognize that inclusive design creates better products for everyone.

Consider how closed captioning, originally developed for deaf and hard-of-hearing users, now benefits millions in noisy environments or when audio isn’t available. Voice recognition technology, refined through work with speech disabilities, powers virtual assistants used by billions. This pattern repeats across industries: designing for disability drives innovation that benefits all users.

The European AI Act’s emphasis on accessibility signals that regulatory frameworks are catching up with this reality. Companies that prioritize inclusive AI aren’t just doing good, they’re positioning themselves for long-term success in an increasingly regulated landscape.

The Path Forward: A.B.L.E.

As we are opening this new chapter of technological capability and human need, 4 principles should guide our approach:

Adapt with Purpose: AI systems must be designed for personalization, not standardization. Every individual brings unique needs, preferences and strengths. Technology should flex to fit these differences rather than forcing conformity.

Build with Community: The disability community must be centered in design processes, not consulted as an afterthought. Nothing about disabled people should be created without disabled people and this principle becomes even more critical when dealing with AI systems that can perpetuate or challenge existing biases.

Learn Continuously: AI systems should be designed for ongoing learning and improvement, with feedback loops that allow for real-time adjustments based on user experience. This isn’t just about technical optimization—it’s about creating systems that grow with their users.

Ensure Equity: Access to AI-powered assistive technologies shouldn’t depend on economic privilege. The most transformative innovations mean nothing if they’re available only to those who can afford them. This requires intentional effort to ensure broad accessibility and affordability.

The future of AI and disability isn’t just about making life easier for people with disabilities—it’s about creating a world where everyone can contribute their unique talents and perspectives. When we design for the margins, we create solutions that benefit the center. When we prioritize human dignity alongside technological capability, we build systems that serve not just profit margins but human potential.

The revolution is already underway. The question isn’t whether AI will transform disability support — it’s whether we’ll have the wisdom to guide that transformation toward liberation rather than limitation. The choice, as always, is ours.

An Opportunity To Learn More

Note – At the United Nations Science Summit 2025 a session looks at the potential of harnessing prosocial AI to help everyone a chance to thrive. Please join online on September 15th at 11 AM EST / 5 PM CET / 11 PM Malaysia time.



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