It seems like AI and its little sibling generative AI are the darlings of the moment, but for those who’ve been keeping a closer eye on the tech scene, it’s starting to look like the honeymoon phase might be over for generative AI.
In the first half of 2023, AI companies accounted for 41% of all U.S. deal value, raising $38.6 billion out of $93.4 billion invested in U.S. startups.
According to the latest Gartner Hype Cycle, generative AI has predictably started its descent from the Peak of Inflated Expectations and is heading straight into the Trough of Disillusionment. And this is actually a good thing.
So, What’s the Trough of Disillusionment Anyway?
Think of the Trough of Disillusionment as the moment when the initial hype fades, and reality sets in. It’s that awkward phase where expectations collide with actual capabilities, and everyone realises that this shiny new tech isn’t going to solve world hunger overnight. But here’s the kicker: this phase is crucial. It’s the part of the cycle where we weed out the hype and start focusing on what’s actually valuable.
The Trough of Disillusionment isn’t a dead-end—it’s a detour that forces us to reassess, refine, and ultimately realise the true potential of generative AI.
Salesforce: A Case in Point
Take Salesforce, for example. The cloud software giant recently found itself in a bit of a pickle. After missing Wall Street’s earnings estimates for the first time since 2006, the company’s stock took a nosedive, and the AI buzz that once surrounded it started to fizzle. Investors, who were initially enthralled by Salesforce’s AI promises, are now questioning whether the company can genuinely harness AI to boost its profitability.
Salesforce reported a meagre 11% revenue growth to $9.13 billion in Q1 2024, missing Wall Street’s estimate for the first time since 2006. This caused a 20% drop in stock, its worst day in 20 years.
This shift in sentiment isn’t unique to Salesforce; it’s a microcosm of what many companies are facing. The allure of AI is undeniable, but the reality of implementing it—particularly in a way that delivers real, tangible value—is a lot trickier.
“As the hype dies down, the focus will shift to practical, value-driven use cases. Expect to see AI solving real business problems, not just headline-grabbing stunts.”
So, as we descend into the Trough of Disillusionment, the question on everyone’s mind is: What next?
The Upside of Disillusionment
While it might sound like a doom-and-gloom scenario, the Trough of Disillusionment is actually where the magic really happens. Here’s why:
Reality Check: This phase forces businesses to take a hard look at their AI strategies. It’s time to move away from lofty promises and focus on what value AI can realistically deliver.
Cutting Through the Noise: As the hype dies down, so does the flood of AI buzzwords. Companies will need to prove their AI credentials with actual results rather than just marketing hyperbole.
Practical Applications: With the hype fading, the focus will shift to practical, value-driven use cases. Expect to see more companies leveraging AI in ways that genuinely solve business problems.
Tech Refinement: Developers will use this time to address the shortcomings of generative AI, making it more secure and more reliable for professional real-world applications.
Sifting Through the Chaff: The less viable AI ventures—the so-called “AI-vapourware”—will fade away, leaving more space for the innovations that truly matter.
Gartner predicts that by 2025, AI will influence 75% of enterprise software vendors to include AI-driven features in their products, up from 33% in 2020.
Generative AI’s Future: A Case for Optimism
Despite the challenges, the future of generative AI is far from bleak. The current downturn is a natural part of the technology’s evolution. As we navigate through the Trough of Disillusionment, we’re likely to see a shift in how businesses approach AI—moving from speculative experimentation to more grounded, effective implementations.
Gartner estimates that by 2026, generative AI will be responsible for 10% of all data produced, compared to less than 1% today.
Take the broader AI landscape as highlighted in the latest Gartner Hype Cycle: while generative AI might be cooling off, other AI technologies are emerging with significant potential. From autonomous AI systems that can operate with minimal human oversight to AI tools that enhance developer productivity, the opportunities are vast. These technologies will likely shape the next wave of AI innovation, helping businesses unlock new levels of efficiency and creativity, while the focus of generative AI will shift from speculative experimentation to solving genuine business problems.
Where do we go from here?
So, as we bid farewell to the peak and start our descent into the trough, let’s remember that this is just the beginning. The Trough of Disillusionment isn’t a dead-end—it’s a detour that forces us to reassess, refine, and ultimately realise the true potential of generative AI. It’s a necessary step on the journey to creating AI technologies that don’t just promise the moon but actually help us reach it.
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