Why and how investors are betting on generative AI

Two huge funding announcements show exactly why investors are going crazy for generative AI.

And that’s because they’re shaping the future of generative AI in very unique ways.

Why it matters: The size of the potential impact of generative AI cannot be overstated. McKinsey estimates that generative AI could add up $2.6 trillion $4.4 trillion in annual value to the global economy. Such market exposure has investors salivating. Anyone who bets on the right generative AI horse will make a killing.

Connect the dots: In Episode 54 of The Marketing AI Show, Marketing AI Institute Founder/CEO Paul Roetzer shared with me why these companies matter and how to think about the generative AI investment landscape.

• There are three broad types of investable generative AI companies. First, you have the infrastructure companies that provide the chips and cloud capabilities that all generated AI relies on to function. (Think: NVIDIA, Google, AWS, and Microsoft.) Second, you have foundation model companies—companies that build the base models that power AI apps. Third, you have the application layer companies themselves—companies like Writer and Jasper build models on top.
• Inflection and Runway play in the foundation model and application spaces. Inflection builds its own massive, sophisticated large language model, then runs a Pi app on top of that model. Runway’s Gen-1 and Gen-2 imaging models power a range of applications in its creative suite. So both companies combine the foundation model and application layer categories.
• Building and training models is expensive. The reason these companies raise so much money is that they need to invest massively in infrastructure like chips/GPUs and cloud services, Roetzer says. For context, OpenAI CEO Sam Altman estimated that the development of GPT-4 alone cost $100 million. Fund model companies are trying to outperform OpenAI, so they need very deep pockets.
• Because of this, there are only a few fund model companies. Given the high barrier to entry, there are only a handful of foundation model companies such as Inflection, OpenAI, and Cohere. For investors, betting on a few foundational model companies seems like a better bet than guessing which of the thousands of apps built on them will win the market.

How to take measures: Let’s face it: None of us will be writing checks for $1.5 billion anytime soon. So how can you use this information?

Well, you’re probably thinking of other ways to bet on AI companies. For example, which AI companies should you include in your tech stack? How can you be sure that the AI ​​tool you’re bringing to your team will be around in 12 months? Roetzer has some advice based on the work of the Marketing AI Institute, which advises companies on their AI technology stack.

Understand that you’re probably going to be going down two paths in parallel, especially if you’re a large enterprise:

1. In the short term, you’ll likely get ahead with a few affordable AI tools for basic use cases. (For example, empowering your marketing team with AI writing apps like Writer or Jasper.)
2. In the long run, you develop a bigger AI strategy and vision. For enterprises, this may look like a large language model for your game, as you will need to adapt existing ones to your needs or create your own. For these types of needs, look at the technology you already use. If you’re already a Google, Microsoft, or AWS customer, they’re your first port of call when it comes to the larger AI transformation.

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