In recent years, artificial intelligence (AI) has been on the centre stage in a variety of industries. From AI-generated art to customer service chatbots, every sector appears to be poised for confusion.
It's not just a daily news feed. Venture capital is being put into it, but the CEO wants to declare the company “AI-First.” But there is a strange sense of deja vu for those who remember the lofty promises of other technology that have faded from their memories.
In 2017, it was blockchain that promised to transform all industries. Companies added “blockchain” to their names, and stock prices skyrocketed, regardless of whether the technology was actually used or not.
A similar trend is currently emerging in AI. What is unfolding is not just a wave of innovation, but an example of a textbook of the technological hype cycle. We have been here many times before.
Understanding the hype cycle
First defined by research firm Gartner, Tech Hype Cycle explains how emerging technologies rise with a wave of inflated promises and expectations, collide with disillusionment, and ultimately find more realistic and useful applications.
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It is important to be aware of the signs of this cycle. It helps to distinguish between true technological changes driven by speculative investment and excellent marketing and the trends that pass through.
It can also mean the difference between making good business decisions and making very expensive mistakes. For example, Meta invested more than 40 billion US dollars in the idea of Metaverse, and at first glance seemed to be chasing a uniquely manufactured technology hype, but later abandoned it.
Read more: Why Metaverse is not ready to become the future of work yet
When Buzz surpasses reality
In 2017, blockchain was the focus of who. Presented as an innovative technology, blockchains provided a decentralized way to record and verify transactions, unlike traditional systems that rely on central authorities and databases.
US soft drink company Long Island Ice Tea Corporation became Long Blockchain Corporation, which has seen stock rise by 400% despite the lack of blockchain products. Kodak launched an ambiguous cryptocurrency called Kodakcoin, causing stock prices to rise.
These developments were not about innovation, but about speculation, chasing short-term profits stemming from hype. Most blockchain projects did not offer real value. The companies rushed to the fear of missing out on it and promises of technological transformation.
However, the technology was not ready, and the solutions it appears to have provided were often misaligned with real industry issues. Companies have tried everything, from tracking pet food ingredients on the blockchain to launch loyalty programs using crypto tokens, often without clear benefits or better alternatives.
Ultimately, around 90% of enterprise blockchain solutions failed by mid-2019.
Generate Aidéjàvu
Fast forward to 2023 and the same patterns started to play with AI. Digital media company BuzzFeed has jumped over 100% in stock after it announced it would use AI to generate quizzes and content. Financial services company Klarna claimed it could replace 700 workers with AI chatbots and handle millions of customer queries.
The outcome was mostly negative. Klarna quickly lost customer satisfaction and had to return that strategy. BuzzFeed's AI content push failed to save a struggling business, and its news department was later shut down. Technology media company CNET has erode its reliability by publishing articles generated by error-stricken AI.
These are not isolated cases. They are signals that AI like blockchain was being over-promoted.
Why do businesses chase tech hype?
There are three mainstays in the play: inflated expectations, short-term views, and flawed implementations. Tech companies are under pressure from investors and media stories, putting too much of what AI can do.
Leaders pitch vague utopian concepts of “change” that don't plan for infrastructure or backup. And many are riding the wave of hype and rushing to implement it.
They often ignore potential shortcomings, integrity with the hype of new technology is hampered by short-term views on what can be done for their company. They want to deploy untested systems, underestimate even complexity and need, and drive return on investment with just novelty.
The results are often disappointing – not because the technology lacks potential, but because it is too early, too early, too little planning and monitoring.
Where from here?
Like blockchain, AI is a legitimate innovation with substantial and transformative potential.
In many cases, these technologies require time to find the right application. The hype for the first blockchain is fading, but the technology has found practical niches in areas like “asset tokenization” within the financial market. This allows assets such as real estate and company stocks to be represented by digital tokens on the blockchain, allowing easier, faster and cheaper transactions.
The same pattern is expected for the generated AI. The current AI hype cycle appears to be tapering, and the results of rushed or unthinkable implementations could be more prominent in the coming years.
However, this decline in hype does not indicate the end of the relevance of the generated AI. Rather, it marks the beginning of a more grounded phase where technology can find the most appropriate application.
One of the clearest takeaways so far is that we use AI to increase human productivity and not replace it. From people who oppose the use of AI to replace them, to those who make frequent and costly mistakes, human surveillance combined with AI-enhanced productivity is seen as a path that is likely to move forward more and more.
Recognizing patterns of technological hype is essential to making smarter decisions. Instead of rushing to adopt all new innovations based on inflated promises, a measured, problem-driven approach leads to more meaningful outcomes.
Long-term success is not about chasing trends or short-term profits from thoughtful experimentation, implementation, and clear objectives. Hype should never direct a strategy. The real value lies in solving real problems.
