The thriving AI sector is clearly evident, with the six leading global companies – NVIDIA, Microsoft, Apple, Google (Alphabet), Amazon, and Meta (Facebook) – all heavily involved in AI to varying degrees. It appears that US stock markets are significantly supported by the impressive earnings generated by these companies.
In simple terms, NVIDIA, a leading global supplier of about 90% of the unique graphics processors essential for AI data centers, has achieved and surpassed a market value of $4 trillion, making it the first company to reach such a milestone.
Additionally, Microsoft surpassed a market value of $4 trillion within approximately a week, and they have significantly contributed to OpenAI, the developers behind ChatGPT and LLM, as well as Windows 11’s AI assistant, Copilot.
Regardless of the assurances and theories put forward by leading AI companies about the potential impacts of their technology, both positive and negative, there’s growing evidence suggesting that the current AI expansion might turn out to be a significant bubble, comparable to or even exceeding the size of the dot-com boom.
According to a recently released study conducted by MIT’s NANDA project, an endeavor aimed at fostering the creation of a genuine network of AI agents, approximately 95% of AI projects initiated in a trial phase do not progress past their initial development stages (as reported by Fortune).
According to a recent study from MIT’s NANDA project, just around 5% of artificial intelligence pilot projects manage to progress past their initial development phase.
As a research analyst at MIT, I delve into investigations by engaging in extensive surveys and interviews with numerous employees and leading figures within organizations. Additionally, I undertake an external assessment of multiple AI pilot projects, some of which may have shown promising results prior to their eventual halt. This holistic approach allows me to gather a comprehensive understanding of the landscape and potential outcomes of these AI initiatives.
The majority (95%) of AI-based pilot programs appear to be encountering challenges in their implementation, according to MIT’s report. This issue seems to stem from the enterprise sector struggling to integrate AI tools effectively, as opposed to any inherent shortcomings in the quality of the AI models themselves.
According to Fortune’s report, an additional factor contributing to the issue is the misdirection of resources. Specifically, it highlights that over half of the budget allocated for generative AI is often channeled towards marketing tools, instead of investing in areas where AI can generate the most revenue, such as automation and streamlining processes.
Approximately a month ago, a forecast by Gartner indicated that at minimum, around 30% of AI-based innovation projects would be discarded following their demonstration phase by the end of 2025. Now, MIT has published a research paper on the subject matter.
AI was just booming, but now it’s a bubble. What gives?
After the unveiling of the MIT NANDA paper, I noticed a significant drop in the valuation of tech stocks in the US, amounting to approximately $1 trillion within just four days. The primary reason behind this slide seems to be an inflated assessment of AI companies, which have a knack for swallowing billions in investments, but often delivering minimal returns.
Sam Altman, the CEO of OpenAI (known for developing the widely-used AI model, ChatGPT), didn’t exactly make things easier with his recent comments. About five days prior, The Verge published an interview with him in which he stated that we are currently experiencing a bubble in the AI sector.
When bubbles form, intelligent individuals tend to become excessively enthusiastic about a grain of truth. If you examine the majority of historical bubbles such as the tech bubble, there was indeed something significant at play. Technology did matter greatly; the internet was indeed groundbreaking. However, people tended to get carried away. Is it possible that collectively, investors are currently showing too much enthusiasm about AI? In my opinion, yes.
Sam Altman, speaking with The Verge
After the disappointing launch of OpenAI’s newest model, GPT-5, Altman expressed his thoughts. Despite promoting GPT-5 to great extremes, its performance turned out to be so poor that OpenAI was compelled to reactivate previous models such as GPT-4o.
The change here? GPT-4o is now subscription-based, meaning users need to pay a recurring fee each month to access what was previously considered the superior AI model at no cost.
It wasn’t unexpected when OpenAI didn’t meet the expectations set for its GPT-5 model. A report from 2024 indicated that all three companies, including OpenAI, Google, and Anthropic, had encountered difficulties in creating sophisticated AI models. In 2023, Bill Gates forecasted that such a plateau in development would occur at some point for projects like the GPT-5.
For about 16 months now, I have enthusiastically followed Gary Marcus, a psychologist, scientist specializing in cognition, and researcher in artificial intelligence who runs the “Marcus on AI” Substack and newsletter. Over this period, he has consistently raised concerns about an imminent burst of the AI bubble.
A new post dated August 20 by Marcus focuses on the MIT NANDA study, market worries regarding stocks, and the shifting climate regarding Artificial Intelligence companies and their assertions.
As a researcher delving into the realm of artificial intelligence, I first raised concerns about the AI bubble during OpenAI’s development of GPT-2. I proposed that the economic rationale behind AI remains elusive, yet my skepticism seemed to be overshadowed by an unabating wave of enthusiasm. However, as Marcus himself put it, “Despite what I argued, the excitement continued to escalate.”
However, just like GPT-5, Altman’s promises were grand but fell short in delivery. Years were spent hyping up the moon, yet when it came time to deliver, the result was far from satisfactory. This didn’t go unnoticed by many.
Gary Marcus, Marcus on AI
Prominent individuals in artificial intelligence have not hesitated to outline the detrimental impact AI could have on white-collar professions and potentially on humanity as a whole. Indeed, such a grim scenario could become reality.
However, it’s starting to appear that these proselytizations might primarily serve to fuel excitement and attract investments, rather than being grounded in authentic predictions about the future.
As a tech enthusiast, I strongly believe that AI holds incredible promise for our future. However, I can’t help but wonder if we’re facing an expanding bubble that could burst sooner rather than later. The hype and expectations surrounding AI are escalating at an unprecedented pace, which certainly raises concerns about its sustainability.
What are your opinions about the latest MIT study and its impact on the AI industry? Does it seem that AI is excessively hyped up, possibly inflating a bubble? Feel free to share your thoughts in the comments below!
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2025-08-26 00:40