The 1990s saw the emergence of the World Wide Web (WWW), still informally called the ‘Internet’. This technology revolutionised humanity by providing newer, cheaper means of communication, enabling real-time news reporting, and enabling the financial sector access to data critical for decision-making. However, while the decade opened on a high point because of the benefits offered by the Internet, it closed on a low note because of the .com bubble.
What is a bubble?
A bubble is the price of specific company shares hitting unreasonably high values when compared to the shares’ base value. This may be done by artificially or organically inflating share prices. While the artificial way is technically a financial crime called fondly ‘pump and dump’, the prices can also inflate organically, fueled by extraordinarily positive investor sentiment. These lead to more speculation as other entities join in, either out of the fear of missing out (FOMO) or speculations about higher earnings from share sales. Then, inevitably, the market corrects as the hype around the novelty lessens, leaving only a few strong players who can absorb the financial shock.
The .com bubble: A déjà vu?
The World Wide Web revolutionised humanity in various ways. However, these early benefits also saw many entities, both foreign and domestic investors, trying to cash in on the hype. While every tech company was being eyed favourably, the investors favored the Internet-based companies more. This led to the formation of a lot of startups that had backing from various types of investors, including Venture Capitalists (VCs) and hedge funds. Investors poured money into these startups in the hope of them becoming profitable later. While investing, they ignored red lines such as the cash ratio and allowed the startups to burn through the capital. So when most of the companies failed to deliver, the market inevitably crashed, leading to a recession. Does the trend of companies throwing cash at startups who have no clear milestones or semblance of a final product look familiar now?
Sequel in the making?
Generative Artificial Intelligence, or GenAI, has been creating tsunamis across the technical and societal domains.
As per Amandeep Singh Khanuja, Principal Analyst and Associate Director, QKS Group, “Generative AI is poised to become a trillion-dollar innovation engine, driving unparalleled transformation across industries. Its potential to revolutionize processes, enhance creativity, and redefine customer experiences is setting the stage for a new era of technological and economic growth.”
The question almost everyone seems to be ignoring is, is this another bubble in the making?
The present situation has many similarities. World-changing technology (Internet then, AI now) and the eagerness to get onto the new trend bandwagon while ignoring essential metrics such as price-to-earnings ratio are just some of the eerily similar factors. Another key factor is the output from all the investments. While this technology, in its current avatar, is being touted as revolutionary, the results have been less than flattering in many cases. Many AI-drawn paintings contain errors such as extra fingers on human hands, and the quality of the other content is also not up to the expected levels as yet.
Another key issue the industry will face soon enough is copyrights. AI works through Large Learning Models (LLM). The LLMs are techniques that process vast amounts of data to ‘learn’ by drawing insights through the processing. The models process different types of data for specific use. The fraud detection AI used in banking software, for instance, particularly processes vast amounts of transactions to spot patterns of fraud and other financial crimes.
Generational AI, in particular, uses LLMs that process data such as articles, knowledge repositories such as encyclopedias to generate paintings and various types of content, including software code, prose and poetry, through rules formed by recognizing patterns and relationships. As is the norm, LLMs work by scanning a large volume of data. However, this data also includes copyrighted data, which will further increase the AI provider company’s expenditure and can drag them into legal trouble. The New York Times is already suing ChatGPT. The minefield is now open to everyone.
Regarding the sector’s fate in 2025, Amandeep has a rather gloomy take. “The QKS Group predicts that 47% of generative AI initiatives within companies will shift focus toward delivering tangible outcomes, moving decisively away from the initial hype. Additionally, 20% of organizations are expected to abandon generative AI projects launched solely on the wave of hype, as a lack of expertise and clear value realization renders these efforts unsustainable. This signals a pivotal moment where the emphasis will increasingly be on strategic implementation and measurable impact.”
Another factor is investor fatigue. Sooner or later, the companies that are investing massively in GenAI adoption will want to see actual results. As was observed in the 1990s, the lack of any results will result in investors losing a lot of money and being extra cautious about their investments, leading to a term called VC Winter. Like the Internet in 1999, Generative Artificial Intelligence is a revolutionary technology with a lot of potential. However, a decisive breakthrough that will unlock its intended potential has yet to arrive. This scenario poses the danger of stalling the sector’s growth, as the funding may dry up if the technology fails to reach the intended milestones those channeling the capital are looking at achieving.
However, Khanuja has a different take. “Generative AI is positioned to become the fastest-adopted technology in history, largely due to its exceptional accessibility, and bring advanced capabilities directly to users’ fingertips. This democratization of AI ensures it seamlessly integrates into daily life, often subconsciously, fostering widespread reliance and adoption. Although its current reach remains within a relatively small user base, the coming years are poised to witness an exponential acceleration as businesses and individuals increasingly recognize its transformative potential.”
TLDR : There are high chances of the current AI boom deflating and causing a lot of damage, as it resembles the 1990’s infamous .com bubble and crash of the 90s.