Artificial Intelligence

A Tech Investor's Guide to AI in 2024

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By Kevin He, Founder & CEO, DeepMotion AI

Investor interest in artificial intelligence (AI) reached a fever pitch in 2023. Equity markets were dominated by large-cap stocks whose early investments in artificial intelligence began to pay off with record profits. This trend was exemplified by chip maker NVIDIA, whose momentum has appeared unstoppable – its stock rose 239% in 2023 and has continued to climb thus far in 2024. While some early AI players could seemingly do no wrong over the last twelve months, other well-established brands, even tech bellwether Apple, fell behind and struggled to catch up.

Meanwhile, ethical issues arose that threatened to offset the goodwill and potential of AI development, and the threadbare regulatory framework struggled to fully grasp the transformation in the industry. Investors also grappled with the mixed signals in the tech industry, as a resilient stock market was overshadowed by recessionary fears and mass layoffs – the technology industry shed nearly a quarter of a million jobs last year.

For investors, it is clear that AI and machine learning technologies have matured past the point of novelty and have begun to show real value in automating and scaling operations for companies in every industry. With ChatGPT fueling the early interest in AI investing, much of the attention has been focused on generative AI and its potential to reshape human communication in fundamental ways. This focus is well-deserved, but investors should also be aware of the less visible opportunities that are driven by AI, such as the infrastructure supporting it that will shape the tech sector and overall markets going forward. We’ll discuss each of these opportunities below, starting with the emerging trends for investors to pay attention to in generative AI.

Emerging Trends in Generative AI

User-generated content creator platforms: The arrival of ChatGPT lifted expectations and unlocked new possibilities in digital content creation. This sudden growth in user generated content (UGC) has fueled a need for high-quality, real-world data to train generative models. Platforms that can capture and leverage this data can produce the next generation of solutions, allowing users to become proficient digital creators in any imaginable medium.

Companies like Roblox, Midjourney, and DeepMotion have been offering versatile content creation platforms that anyone can use to create games, images, and animations, respectively. Such platform companies are massing large quantities of domain-specific UGC and data, which is the crucial raw material to train and grow next-generation Gen-AI models. In a similar vein, Reddit's recent endeavors in the AI data market could significantly boost its valuation. By exploring new revenue streams through the sale of its data, particularly valuable for training AI models, Reddit aligns with industry giants like Microsoft and Alphabet in recognizing the intrinsic value of real-time, user-generated content.

As investors seek competitive advantages in consumer and commercial generative AI, the unique advantage of content creation platforms powered by UGC may indicate an attractive investment opportunity at the inception stage. Investors should analyze these opportunities by considering their demonstrated ROI through traditional metrics such as production costs and revenue, as well as qualitative measures of user engagement, cultural impact, and sustained ability to collect and leverage UGC.

NLP AI, virtual assistance, and chatbots: Another high-profile, highly lucrative area in the early development of AI has been natural language processing (NLP), which has rapidly progressed. The integrations of AI virtual assistance and chatbots, powered by sophisticated NLP and underpinned by machine learning, are allowing companies to scale services in unprecedented ways, reducing human errors, bolstering margins, and delivering value for customers. NLP integrations will likely continue to deliver value for investors as well.

The Broader AI Investment Universe

For AI-focused investors, plenty of opportunities are emerging outside of generative AI platforms, but avoiding overexuberance is still prudent. Looking back at 2023, it's easy to become envious of the performance of companies like NVIDIA and seek to concentrate AI bets on a few high-profile names. However, diversification remains a critical tool for investors. To capture the potential upside of AI while mitigating the potentially volatile returns of emerging technology, investors should be aware of concentration risks and have exposure to different areas of technology and other sectors benefiting from AI. The AI space continues to be a battleground subject to disruptive players, and a concentrated bet may lead to significant losses.

Other risks that AI investors should be mindful of include regulatory and geopolitical risks. Understanding the geopolitical environment that can impact the development of technologies is crucial. For instance, the semiconductor industry has been shaped by US sanctions on Chinese companies, and any changes to these sanctions can have an outsized influence on the profitability of global semiconductor companies and equipment suppliers.

To minimize these risks while maximizing return potential, investors can spread their bets across AI opportunities, allocating their investments into the following buckets:

  • Generative AI platforms and developers.
  • Hardware, software, and service providers that create the infrastructure for AI. These investments can include semiconductor companies, cloud service providers, and IT service & outsourcing providers.
  • Other industries positioned to benefit from AI.

For AI opportunities outside of the tech sector, investors should hold companies whose value chains will greatly improve amid the development of AI and machine learning solutions. These may be companies in service industries, where chatbots and NLP will allow greater global scaling. There may also be opportunities for industries where machine learning aids in inventory control and pricing power, such as shipping and logistics.

The financial sector will certainly see more integration of AI as a means to optimize returns. And life sciences holds tremendous possibilities as a sector that employed machine learning from its earliest stages and is well-positioned to continue to benefit from AI's ability to screen and suggest optimal treatments for disease.

As far as AI has come in a short amount of time, the future remains wide open. The most successful investors will be those committed to continuous learning and networking as the technologies evolve. Social media allows us to engage with industry experts. Going one step further, participating in some of the growing number of AI conferences and events can help investors identify opportunities before the general public. AI publications and knowledge-sharing platforms are also great ways to stay abreast of industry trends and developments.

Investing in AI is promising and complex. The potential for value creation is tremendous, but disruption also brings risks. The required diligence of successful investing must also be paired with agility. Investors who can balance patience with conviction have a chance to successfully ride the AI revolution.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

Kevin-He

Kevin Kaichuan He is founder & CEO of DeepMotion, a Silicon Valley technology startup focused on building the largest AI-generated animation platform for accessible digital human motion.

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