The past two years have been challenging for investors in the technology sector. SoftBank, a prominent Japanese investment firm emblematic of the venture capital boom of the 2010s, is facing challenges. These challenges stem from shifting dynamics, characterised by higher interest rates and reduced corporate valuations. Despite these challenges, investing in artificial intelligence (AI) remains a notable area of interest for the firm’s charismatic founder, Son Masayoshi.
The emergence of generative AI platforms like ChatGPT has sparked widespread discussions among investors. These discussions revolve around the potential of this growing industry and its disruptive capabilities. Son draws parallels between this era and the early days of the internet. He envisions generative AI as a catalyst for a new wave of initial public offerings and the emergence of mega-cap tech companies.
Investors are confronted with two pivotal questions. Firstly, which frontier technologies hold the promise of significant returns? Secondly, will the value primarily accrue to agile start-ups backed by venture capital or entrenched technology giants?
Deciphering these complexities is no easy task. The optimal strategy remains elusive—whether it is possessing the most advanced chatbot or a substantial customer base. Simply being at the forefront of innovative technology does not guarantee profitability. Often, established giants dominate the landscape.
Companies like Alphabet, Amazon, and Meta, collectively valued at $3.4 trillion, exemplify the success of early movers in the internet era. Similarly, Alibaba’s trajectory underscores the value of strategic investments. Recognising tech trends and developing robust platforms proved immensely lucrative for early investors, leaving legacy firms struggling to adapt.
Will history repeat itself in the AI domain? Insights from management guru Clayton Christensen shed light on potential trajectories. Christensen’s theory suggests that smaller companies excel in nascent or overlooked markets. Meanwhile, incumbents focus on leveraging new technology within existing frameworks. Despite their awareness of technological advancements, incumbents often underestimate disruptive forces until it is too late.
Investors like Son bet on a future shaped by AI-focused start-ups, anticipating a period of transformative innovation. However, recent enthusiasm surrounding generative AI platforms primarily focuses on their technological potential. It doesn’t center on their ability to create entirely new markets. Previous advancements in machine learning have predominantly benefited incumbents, raising questions about the fate of AI-focused start-ups.
Christensen’s theory underscores the unpredictability of revolutionary innovation in business terms. Nevertheless, existing tech giants are heavily investing in AI, positioning themselves to capitalise on potential market shifts. Consequently, investing in broad index funds tracking established tech firms may yield comparable or superior returns. This is in comparison to investments in private AI start-ups.
Theories on why innovation can be disruptive or not are commonly debated among business and management students rather than stock pickers. However, understanding this difference is crucial. It plays a significant role in determining whether the next wave of listed tech giants will emerge from private AI firms. These giants are anticipated to have market capitalisations in the hundreds of billions. Currently, it seems increasingly probable that the technology market value will further strengthen the position of existing tech giants.
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