The enthusiasm surrounding artificial intelligence (AI) in the market is palpable and justified. However, this fervor has led many venture capitalists (VCs) to act irrationally, eagerly pursuing any investment opportunity associated with a dot-ai domain name.
Several investment justifications stem from outdated conventional wisdom, which are essentially misconceptions or “myths” in the realm of AI investing.
Here are three prevalent myths:
Myth No. 1: The Significance of Being the First Mover
Numerous VCs have expressed the necessity of being the “first” and “fast” to ride the AI wave. However, this mindset reflects hasty decision-making or, more likely, a lack of critical thinking. Consider examples like Pets.com vs. Chewy, Webvan vs. Instacart, AltaVista vs. Google, or Myspace vs. Facebook. While being the first may not be a disadvantage, it does not inherently confer an advantage either.
Spencer Greene
Certain scenarios exist where being the first holds importance. In a “land-grab” market, the initial company that invests significantly to acquire a majority of customers can establish long-term dominance.
This was the rationale behind a16z’s aggressive funding of Clubhouse. While it did not yield the desired outcome at that time, occasionally, this strategy proves successful.
In other market structures, being well-funded and the first mover entails educating customers on a new behavior, thereby facilitating later entrants to capitalize on your groundwork.
Given the rapid evolution of AI, the advantages of being the first are arguably diminished compared to slower-moving markets.
Companies like Google and OpenAI have invested billions in technology that Facebook is now offering for free. This does not imply that Google or OpenAI will not succeed — they are likely to thrive.
However, if a startup or investor emphasizes being the first mover as their primary competitive advantage, skepticism is warranted. It suggests a lack of foresight regarding how to sustain a competitive edge over time.
Myth No. 2: Equating an Exciting Product with an Exciting Business
A common fallacy lies in assuming that an exciting product automatically translates to an exciting business. While a good product is typically a prerequisite for a successful business, it is not adequate on its own.
Netscape, the pioneer of the World Wide Web with its Navigator browser, exemplifies this. Despite its groundbreaking product, it failed to materialize into a profitable business.
In the realm of AI, we witness captivating demonstrations regularly, showcasing remarkable, almost science-fiction-like advancements. However, not all of these innovations will translate into profitable ventures.
The appeal or novelty of a product often does not align with its business viability. The real revenue potential sometimes lies in less glamorous markets. For instance, compare Netscape, the web browser innovator, to F5 Networks, a leader in HTTP load balancers. While one generates substantial cash flow, the other remains a historical artifact.
Myth No. 3: Underestimating Incumbents
There is a prevailing belief that established companies struggle to innovate, and in times of change, startups inevitably emerge victorious.
Reflect on instances like Netflix vs. Blockbuster, Airbnb vs. Hilton, PayPal vs. traditional banks, or Amazon vs. Barnes & Noble/Tower Records/Walmart.
Presently, technology firms dominate the top positions in the S&P 500, a stark shift from a decade ago. Given this trend, one might assume that new AI-centric startups will overthrow existing tech giants and attain comparable dominance.
Contrary to this assumption, AI startups aiming to disrupt major tech players are unlikely to succeed. Big Tech corporations possess deep knowledge of AI, abundant talent, substantial data resources, and are investing significantly in this domain.
While there may be exceptions where startups outperform Big Tech, as a whole, established tech giants are less susceptible to disruption compared to pre-internet era companies.
The true battleground for AI startups lies in challenging non-tech incumbents. The 80% of the S&P 500 composed of non-tech entities represents the prime targets for AI disruption. Industries previously resistant to automation now present lucrative opportunities for AI integration.
Therefore, the narrative that AI-native companies will replace established tech giants like Microsoft or Apple is unfounded. Rather than AI superseding software, it complements it by addressing what traditional software could not.
