Artificial deja vu: The AI hype is just like the blockchain frenzy

In recent years, artificial intelligence (AI) has taken centre stage across various industries. From AI-generated art to chatbots in customer service, every sector is seemingly poised for disruption.

It’s not just in your news feed every day – venture capital is pouring in, while CEOs are eager to declare their companies “AI-first”. But for those who remember the lofty promises of other technologies that have since faded from memory, there’s an uncanny sense of déjà vu.

In 2017, it was blockchain that promised to transform every industry. Companies added “blockchain” to their name and watched stock prices skyrocket, regardless of whether the technology was used, or how.

Now, a similar trend is emerging with AI. What’s unfolding is not just a wave of innovation, but a textbook example of a tech hype cycle. We’ve been here many times before.

The tech hype cycle, first defined by the research firm Gartner, describes how emerging technologies rise on a wave of inflated promises and expectations, crash into disillusionment and, eventually, find a more realistic and useful application.

It can also mean the difference between making a good business decision and a very costly mistake. Meta, for example, invested more than $40 billion into the metaverse idea while seemingly chasing their own manufactured tech hype, only to abandon it later.

In 2017, blockchain was everyone’s focus. Presented as a revolutionary technology, blockchain offered a decentralised way to record and verify transactions, unlike traditional systems that rely on central authorities or databases.

US soft drinks company Long Island Iced Tea Corporation became Long Blockchain Corporation and saw its stock rise 400% overnight, despite having no blockchain product. Kodak launched a vague cryptocurrency called KodakCoin, sending its stock price soaring.

These developments were less about innovation and more about speculation, chasing short-term gains driven by hype. Most blockchain projects never delivered real value. Companies rushed in, driven by fear of missing out and the promise of technological transformation.

But the tech wasn’t ready, and the solutions it supposedly offered were often misaligned with real industry problems. Companies tried everything, from tracking pet food ingredients on blockchain to launching loyalty programs with crypto tokens, often without clear benefits or better alternatives.

In the end, about 90% of enterprise blockchain solutions failed by mid-2019.

Fast-forward to 2023, and the same pattern started playing out with AI. Digital media company BuzzFeed saw its stock jump more than 100% after announcing it would use AI to generate quizzes and content. Financial services company Klarna replaced 700 workers with an AI chatbot, claiming it could handle millions of customer queries.

The results were mostly negative. Klarna soon saw a decline in customer satisfaction and had to walk back its strategy, rehiring humans for customer support this year. BuzzFeed’s AI content push failed to save its struggling business, and its news division later shut down. Tech media company CNET published AI-generated articles riddled with errors, damaging its credibility.

These are not isolated incidents. They’re signals that AI, like blockchain, was being overhyped.

One of the clearest takeaways so far is that AI should be used to enhance human productivity, not replace it. From people pushing back against the use of AI to replace them, to AI making frequent and costly mistakes, human oversight paired with AI-enhanced productivity is increasingly seen as the most likely path forward.

Long-term success comes from thoughtful experimentation, implementation, and clear purpose, not from chasing trends or short-term gains. Hype should never dictate strategy; real value lies in solving real problems.