Investment Implications Of Generative AI
Summary
Looking past the enthusiasm and calls for caution spawned by ChatGPT and similar large language models (LLMs), we believe AI is entering a period of broad adoption and application that will enhance business efficiency and expand existing end markets. Several privately held companies offering enhanced computing technology could also vie for enterprise customers but currently lack a full ecosystem crucial to deploying effective AI infrastructure and addressing niche use cases. Scale matters in public cloud, which caused a small group of companies, namely Microsoft (MSFT), Google and Amazon (AMZN), along with potentially Oracle (ORCL), to capture the lion’s share of growth in the space. Moreover, SaaS companies with large amounts of customer data and significant regulatory barriers to entry, such as in human resources and financial applications, are best positioned to maintain their competitive advantage as AI automates more functions. From a business model and investment standpoint, we believe some key areas to watch as generative AI gains wider usage include the implementation cost curve, consumer Internet behavior with AI-enabled search, and actions by regulators and publishers to control and likely limit the proprietary data available to train LLMs.