#100 Navigating the Hype: Will Generative AI Avoid the Trough of Disillusionment?

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The concept of the "trough of disillusionment," popularized by the Gartner hype cycle, has long served as a rite of passage for emerging technologies. It marks a phase where lofty expectations give way to the sobering realities of innovation, inevitably leading to a dip in interest and market activity. The question that looms large in discussions around generative AI is whether this disruptive technology will also plunge into such a trough, or navigate its way around it.

Understanding the Trough: A Cycle of Innovation and Reality

The trough of disillusionment acts as a filter that sifts out the fair-weather fans and retains only the true believers—both on the vendor and customer sides. As people come to grips with the fact that not all the grand promises can be fulfilled immediately, interest wanes and only the serious players remain. Yet, this trough also provides breathing room for companies to refine their innovations. The rise from the trough is gradual but sustained, producing longer-lasting impact, unlike the fleeting hype that preceded it.

Why Generative AI Stands Apart

One key reason generative AI might evade this trough is its relative invisibility compared to more consumer-centric technologies. This makes it challenging for critics to rally against it easily. Moreover, generative AI is evolving at an unprecedented pace, thanks to foundational models like GPT and Vertex AI. Since enthusiasts of generative AI are often well-versed in classic AI, they grasp that both impact and evolution are nonlinear. This nuanced understanding could stave off widespread disillusionment among the technology's core supporters.

Potential for Disillusionment Looms

However, it would be premature to assume generative AI will smoothly bypass the trough of disillusionment. Hype continues growing at a breakneck pace. Some make overinflated claims about current capabilities. As LLMs are deployed more broadly, limitations around bias, factual accuracy, and coherence will become more evident. Many organizations still lack the data pipelines and skillsets to properly utilize generative AI ( check out my previous article on this matter and discover how partnering with InfoObjects can assist you in navigating these challenges with ease.).

While core enthusiasts understand rapid evolution is the norm, the general public may grow frustrated with inconsistencies and gaps between expectations and reality. These factors could tip generative AI into at least a partial descent down the trough. The question is how steep the drop and how long the stay before it climbs back out. Still, there are indicators that the generative AI ecosystem could develop enough momentum to power through a potential trough of disillusionment

Ecosystem Synergies: A Case for Optimism

Generative AI diverges from previous hype cycles like the dot-com bubble, where public speculation ran rampant. Instead, it more closely mirrors the smartphone revolution led by a few dominant players, fostering an ecosystem that enables a myriad of businesses to evolve in new and unexpected ways. Uber didn't aim to compete with Apple or Google Android; it disrupted a traditional industry by leveraging platforms these companies created. In a similar vein, generative AI could spawn solutions for needs that existed but remained unmet due to technological constraints. For instance, Roost.ai leverages the power of generative AI and large language models to automate the generation and execution of test cases, achieving near 100% test coverage—solving a problem that previously seemed insurmountable.

Navigating the Path Forward

Disillusionment, if it occurs, doesn't emanate from the skeptics; it springs from the believers. But with the rapid evolution of generative AI and the ecosystem it fosters, the odds are favorable for avoiding a steep descent into disillusionment. By focusing on responsible development and practical applications, generative AI has the potential to circumvent the trough and move directly into a phase of broad societal impact. In this narrative, the trough isn't an inevitability; it's a challenge to be met and overcome, enabling generative AI to fully realize its transformative potential.

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