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How to Invest in the Future of Generative AI

A look at the themes, companies, and funds in the generative AI space.

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The launch of ChatGPT was just the start of the generative AI movement: Numerous other companies’ products have also staked their claim in the generative AI market, including Google’s GOOG Bard, Baidu’s BIDU Ernie Bot, and Salesforce’s CRM Einstein GPT. Additionally, Microsoft MSFT has joined forces with OpenAI to introduce Copilot, integrating language models into Bing search and 365 applications to simplify complex tasks and enhance user productivity and experience.

What is generative AI? It’s an area of artificial intelligence that centers on creating novel and distinct datasets such as images, videos, text, and audio across multiple domains by using multimodal large language models trained on diverse inputs.

This market has surged in recent years as significant strides have been made in scaling large language models, which makes it possible for AI to perform at a human level in tasks such as creating art, writing articles, engaging in conversations, copywriting, and designing products. According to PitchBook data, this generative AI market is predicted to reach $42.6 billion by 2023 and exceed $98.1 billion by 2026.

The affordability of computing, along with the speed of language models and greater accessibility, is poised to transform multiple businesses across content economy, graphic design, coding, automation, marketing, and sales. This transformation will not only reduce the cost of knowledge creation but also significantly increase labor productivity and economic value.

Companies are racing to integrate this technology into their products and solutions, and the trend shows no signs of slowing. Here, we outline the generative AI theme and how investors can engage with this trend.

Defining the Generative AI Innovation Theme

We use five themes to classify public companies that are actively engaged in creating products and solutions related to generative AI.

These themes include:

  • Automation: This theme centers on the development of decision-making systems and workflow optimization. For instance, Tesla TSLA is using algorithms in combination with sensors, cameras, and synthetic data to actively pursue self-driving technology. And Salesforce is incorporating this innovative technology to improve customer relationship management and streamline user workflows.
  • Content creation: The theme revolves around the development of unique and innovative content, including music, text, and art, with the aim of transforming the way we consume and interact with it. Adobe ADBE, for example, is exploring ways to use this technology to create, edit, and enhance digital content through its Photoshop and Adobe Experience Manager tools. Similarly, Roblox RBLX, Tencent TCEHY, and Unity Software U are collaborating to create highly realistic virtual characters that can be used in video games, virtual reality, and other contexts.
  • Personalization: Companies involved with this theme aim to personalize user experiences, particularly in the areas of content moderation, digital assistants, and recommender systems. This makes user experiences more intuitive and customized. Companies like Netflix NFLX and Spotify SPOT are actively involved in this space, using the technology to generate personalized product recommendations. Similarly, Meta META is also focused on content moderation as part of this theme.
  • Generative design: This theme focuses on creating tools that generate designs, models, and prototypes for applications including architecture and graphic design. It helps reduce time and cost needed for creating and testing prototypes, resulting in faster time-to-market and reduced manufacturing overhead. To this end, Siemens SMAWF is focusing on industrial automation, Autodesk ADSK on optimizing structural design for strength and efficiency, and Hitachi HTHIF on optimizing manufacturing and supply chains to minimize wastage for clients.
  • Platform and solutions: The theme centers on building platforms, interfaces, and solutions that other businesses can use to create their own applications and products, promoting widespread adoption across businesses of all sizes. Notable players in this theme include Alphabet, Microsoft, and Nvidia NVDA, as they develop language models and related solutions. Darktrace DRKTF is also included in this theme, as it works toward building threat-prevention solutions that enable fair usage of Generative AI.

Stocks Linked to Generative AI Themes

Using the Natural Language Processing algorithm described in our methodology paper, “Theme Retrieval for Equities,” we have curated a list of 35 global companies that have meaningful linkages to these generative AI themes.

Our algorithm analyzed various unstructured sources, including corporate filings, news articles, and revenue segment information, to identify relevant theme keywords that associate these themes with the companies’ activities, such as research & development, mergers & acquisitions, product development, and patent filings. Nevertheless, we urge investors to exercise caution as this list is generated through a quantitative algorithm, and the findings should be interpreted with prudence.

Table showing 35 companies that are engaging with some aspect of the generative AI theme.

Funds Linked to Generative AI Themes

We further examined funds with linkages to generative AI themes by aggregating their holdings and applying a minimum weight threshold of 20%. To avoid bias toward funds with a tilt to FAANG stocks (Facebook [now Meta], Amazon.com AMZN, Apple AAPL, Netflix, and Google parent Alphabet), we also applied a holding count match of at least 10. The combined assets under management of these funds is around $15 billion, with most being associated with the technology sector and some focused on the artificial intelligence theme. These AI-themed funds are also part of the Morningstar Thematic Fund Landscape, but none have Morningstar Analyst Rating coverage.

Table showing funds with exposure to generative AI, primarily associated with the technology sector and some focused on the artificial intelligence theme.

Despite the significant potential of the space, most companies still need to demonstrate how they plan to evolve their business models and technology to incorporate generative AI. This includes questions related to observability, skill gaps, copyright, trust & safety, ethical concerns, and model development costs.

Nevertheless, the current efforts are focused on creating strong foundations for prototypes, and we expect to see more value creation as the theme evolves.

Leveraging our quantitative algorithms, we can improve how we find linkages related to these emerging themes. Investors should keep a close eye on this space as the theme continues to develop and more companies become actively involved.

The author or authors do not own shares in any securities mentioned in this article. Find out about Morningstar’s editorial policies.

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