By Ivan Nikkhoo
Introduction
The AI boom is at a critical point with funding slowing and fears of a tech bubble. Many early-stage AI startups, lacking profitable use cases, may fail as AI shifts from novelty to necessity. But this shakeout is a natural part of tech evolution, paving the way for innovation.
First the funding stops, then the failures start.
The rapid rise of AI has been astonishing, but as the initial excitement wanes and practical considerations set in—such as identifying viable use cases and achieving sustainable monetisation and ROI—there are growing fears that we’re witnessing yet another tech bubble that’s about to burst.
Based on previous technology investment cycles, there’s good reason to think that we’re on the brink of a significant wave of AI startup failures. Early-stage investment into nascent AI startups has already slowed and we’re now seeing signs of a similar slowdown in later-stage capital. Overall, this quarter’s deals are projected to drop to 900, down from 1,052 last quarter and nearly 30% lower than the same period last year. As this trend takes hold, and with the M&A market for startups slow and the IPO pipeline virtually non-existent, many previously lauded startups will begin to flounder.
It’s easy to dial up the alarmist rhetoric about what’s happening (the AI winter is coming), yet in truth, this is a natural phase in the maturation of any groundbreaking technology. It will be painful for the startups that don’t make it and for the investors that backed them, but it’s a necessary stopping-off point on the road to broad adoption and implementation in large enterprises.
Solutions in search of a problem
Thousands of new startups have emerged over the past 18 months offering generative AI solutions for a wide range of different consumer and business use cases. They have attracted billions in venture investment at lofty valuations, and many of the technology applications are undeniably impressive at face value. However, to stand out, startups should consider developing a focused AI MVP that aligns with specific business needs and clearly demonstrates value from the outset.
The problem is that very few of these startups have identified cast iron business use cases that their potential clients would be willing to pay for. This isn’t surprising – after all, businesses themselves are still unsure about how and where AI should be applied within their organisations, and how this will impact the different aspects of their businesses, from hiring to revenue generation. Every week another major news story breaks about an AI use case gone awry.
What we’re seeing is a plethora of AI startups scrambling for problems to solve with their technology solutions. As funding tightens, the cracks in their foundations will become increasingly evident.
The technological limitations of AI are becoming clear
The litmus test for any emerging technology is its suitability for enterprise and large-scale usage, and in the case of AI, we’re now seeing that even the most promising use cases are difficult to scale due to the sheer processing power required.
Current hardware limitations are a major bottleneck, and while this will improve over time as advancements in chip technology continue in line with Moore’s Law, it’s an acute problem for AI startups that need to monetise now, rather than in two to four years’ time. If enterprise leaders feel they’re currently only able to deploy AI at the margins, their AI spend will reflect this.
Don’t fear the fallout
The coming wave of AI startup failures is not a sign of an industry in decline but one in evolution. The most robust and viable AI companies—those that have identified specific problems, have clear monetisation mechanisms, and built practical solutions to this brief—will continue to thrive.
Just as the ecommerce boom led to huge funding rounds, followed by a large number of failures before giants like Amazon emerged dominant, the AI sector will see a similar shakeout. Moreover, these failures also create opportunities for other companies to acquire great talent and innovative technology. Walmart’s acquisition of Jet.com, for example, not only provided them with a robust ecommerce platform but also brought in a talented team that significantly bolstered Walmart’s online strategy.
Likewise, the acceleration of AI skills development over the past few years will benefit the entire business world and lay the groundwork for the next generation of AI startups. The founders of firms that haven’t gone the distance this time will learn from their experiences. Many will start afresh on new AI ventures with greater focus and clarity of purpose.
It’s too early to pick the long-term winners
Historically, the first companies to enter a new market aren’t the ones that dominate it in the long run. Consider Novell, which once had a stronghold in network software, or IBM, which has been forced to transition from a hardware giant to a services-oriented company.
Microsoft, Google and other Big Tech players may be dominating the current AI conversation, but it’s a mistake to assume that the race is already won, even if many of the current AI startup challengers fall by the wayside.
Indeed, the Big Tech firms are still figuring out their own AI use cases, strategies, and product integrations. It’s massively expensive and structurally difficult for them to embed AI into well-established products, compared to new AI startups which, unburdened by legacy systems, have the flexibility to create innovative solutions from scratch.
The future is embedded AI in everything
The current AI startup landscape is characterised by a struggle to define product/market fit. The only ones to survive the coming fallout will be the companies that demonstrate a laser focus on solving real, valuable problems using AI.
While the impending wave of AI startup failures may seem alarming, it’s a necessary step in the transition from AI as a novelty tool, to AI as a foundational technology embedded in our daily lives and business operations, much like the internet is today.
The internet changed how we live, communicate and conduct business. AI will transform our lives beyond imagination.
About the Author
Ivan Nikkhoo, Managing Partner of Navigate Ventures. With over 40 years of global C-level experience in tech, Ivan is a seasoned investor, entrepreneur, advisor, board member, operator and educator. As the Founder and Managing Partner of Navigate Ventures, he leads a B2B Enterprise SaaS fund focused on entrepreneurs outside Silicon Valley between series A and B Growth rounds (A Extension Rounds).
