Artificial intelligence has grown in popularity over the past five years, evolving from something consumers only saw in sci-fi movies to a widespread technology. Many companies now use AI in some form, and it has become commonplace for many consumers as AI services are integrated into internet search engines, phone applications, and other daily interactions. However, as AI is deployed at an ever-increasing pace, it is becoming clear that the technology is not being leveraged to the extent hoped for while companies realize the value of human workers.
As more companies roll out AI services, investors have rushed to buy technology stocks on New York Stock Exchange indexes such as the S&P 500 and the tech-heavy Nasdaq in recent years. Only seven companies, Amazon, Alphabet (Google), Nvidia, Meta (Facebook), Microsoft, Apple and Tesla, have dominated this focus. More and more city analysts and financial economists are now warning that the AI bubble will burst at some point.
Jeremy Grantham, founder and investment advisor of a major asset manager, said he plans to sell his technology stocks because he expects the AI bubble to burst soon. Grantham said that AI is similar to inventing the railroad or the Internet in that everyone over-invests, and when he realizes that it is a utility like electricity, he understands that there isn’t much money to be made from the invention itself, except for the companies that build services on top of it.
Businesses and consumers are impressed by the capabilities of AI technologies, which appear increasingly intelligent. More companies are investing in integrating AI services into their operations, while consumers are using AI for basic, everyday tasks like internet searches. However, with the boom in AI, users are slowly losing trust in certain services as it becomes clear that there are limits to the “intelligence” or human-like capabilities of AI.
In the manufacturing sector, companies have been investing in automation for decades, as engineering and technology companies develop automated devices that can perform simple tasks instead of humans. This has helped speed up production lines, reduce the need for people to perform more dangerous or monotonous tasks, and reduce the price of goods. However, the emergence of AI poses a far greater threat to workers in this sector.
Manufacturing companies around the world are showing greater interest in AI as they seek to reduce reliance on human workers. However, there are concerns about the risks of rapidly integrating AI into manufacturing operations, particularly in more complex roles. Automation works well in stable, repeatable environments, which is not the case in manufacturing plants. Companies managing manufacturing assets face a range of challenges, including late deliveries from suppliers, machine breakdowns, fluctuating demand and regulatory restrictions – problems that existing AI simply cannot address.
AI will likely become a critical component in manufacturing, providing services such as predictive maintenance and inspection. However, it could cost companies time and money if it is used in variable operations that it cannot yet perform. In a January Forbes article, the author explained: “For AI to be useful, it must work in production systems, be based on real data and real workflows, and hold people accountable for the results. In this application, AI helps people move faster and see more clearly. It does not replace judgment.”
The statistics already reflect the early failures of AI in certain industries. For example, S&P Global’s most recent executive survey found that 42 percent of companies have abandoned most of their AI initiatives in 2025, compared to 17 percent in 2024. Meanwhile, a 2024 RAND report suggested that more than 80 percent of industrial AI projects fail, largely due to process complexity, poor data quality, and lack of real-world context.
Automaker Ford has expanded its use of AI in recent years to increase productivity by automating systems that speed decision-making and simplify development. However, after implementing these systems, Ford quickly discovered that some of these AI systems were less resilient than expected, especially when given incomplete or insufficiently differentiated data.
Ford’s vice president of vehicle hardware engineering, Charles Poon, explained: “We mistakenly thought that simply introducing artificial intelligence and adapting to our design requirements would produce a high-quality product.”
The company found that experienced engineers left with them a large amount of institutional knowledge. Important information has been omitted from the data sets used to train AI systems. This has led to Ford bringing back and promoting over 350 experienced engineers to improve data collection and interpretation methods and support AI training for future applications. However, it remains unclear whether this will be effective.
Despite the widespread popularity of AI in recent years, companies are quickly realizing the limitations of existing AI technology. While AI can be used to improve a variety of operations, it is not and may never be suitable for more complex or variable tasks. This will likely cause the AI bubble to burst at some point, but the timing is unknown.
By Felicity Bradstock for Oilprice.com
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https://finance.yahoo.com/technology/ai/articles/ai-bubble-burst-190000071.html
