Consumer and Enterprise in the AI era

Revisiting one of my first Substack posts, which feels even more relevant today.

Welcome to issue #55 of next big thing.

It has been some months since my last real essay here, but I’ve found myself referring back to the second one I ever wrote on next big thing many times during the course of this year.

That piece, Consumer and Enterprise, still gets a surprising number of weekly reads, and remains the first Google result for the term consumer and enterprise. In it, I talk about how the lines between categorizing companies as “consumer” or “enterprise” have blurred, and that the most interesting companies in the world fit neither bucket; they are dually-focused on both consumer and enterprise.

This very much rings true today. Consider the largest public companies in the world; Alphabet, Amazon, Meta, Microsoft, and NVIDIA all have businesses and business models that serve consumers and enterprises. Now consider the largest private technology companies in the world; ByteDance, Canva, OpenAI, Stripe and even SpaceX (Starlink has 4+ million subscribers and is on track to do $6 billion in revenue this year!) are all both consumer and enterprise.

At Footwork, we love partnering with founders who dare to build companies that are both consumer and enterprise. Our last three investments fit this mold, as does roughly half of our entire portfolio. And my hunch is that percentage will keep growing in the years to come.

At the intersection of both consumer and enterprise lie some of the largest and most impactful companies in the world.

The AI Era

In November 2022, OpenAI publicly launched ChatGPT. A few months later, NVIDIA CEO Jensen Huang deemed it to be the iPhone moment for artificial intelligence. Sitting here two years later, there is little room for debate that we are now in a new technology era, that of AI, ushered in by the large language models (LLMs) such as OpenAI’s GPT.

The rate of technology adoption in the AI era is like nothing we have seen before. ChatGPT, for example, has over 200 million weekly active users, less than 2 years since launch; while a different type of product of course, it took Facebook more than 5 years to reach that number of users. ChatGPT is rumored to generate $3 billion in annualized revenue after 2 years since launch; it took Google and Facebook each more than 6 years to surpass $3 billion annualized revenue.

Chart from The AI Revolution report by Coatue (from November 2023).

AI is being adopted rapidly by both consumers and enterprises, and most of the key companies driving this adoption cater to both types of end users. The companies building the most-used LLMs — OpenAI, Anthropic, Google, Meta — offer models being used by businesses and other applications, as well as consumer-facing applications themselves. Many of the fast-growing AI-native applications — for example, Cursor, ElevenLabs, Elicit, GPTZero, Granola, HeyGen, Midjourney, Perplexity, Runway, Suno — have consumer, prosumer (a consumer using a product in a professional context), and bottoms-up enterprise adoption. These are all companies that are growing in revenue and usage extremely quickly and efficiently — and some (not all) are building strong bases of retained customers.

AI companies that are both consumer and enterprise are some of the largest and fastest-growing.

Most of these companies begin by catering to consumers or prosumers, enabling anyone to quickly sign up and start using the product, and end up spreading within enterprises. But there’s also a class of enterprise-first companies that are designed for consumers because they are the end users, such as Sierra and other AI agent companies automating customer service and support.

At this application layer of AI, we’re seeing consumers and enterprises exhibit the curiosity to try new products and to stick with ones that demonstrate real value. And the rapid pace of improvement of LLMs is enabling the companies that leverage them to serve different personas, across consumers and enterprises, far earlier in their lifecycle than companies of the past (not to mention the code generation AI products that are speeding up the pace of software development itself, a further accelerant to expanding the surface area products can touch). And the companies listed above are just a fraction of the dozens of AI-first companies finding success serving both consumers and enterprises even in their early days.

Implications for Founders and VCs

One of the reasons I wrote the original post back in 2020 was my frustration with the rigidity of some VCs’ thinking, to want to put every company in a consumer or enterprise bucket. Indeed, many venture firms have separate teams to evaluate consumer companies vs. enterprise companies. Or, worse still, they claim to be generalists but don’t even have a consumer team or investor because they believe the “category” to be “dead.”

I think the evidence is pretty clear that this line of thinking is foolish. No outlier company fits neatly in a box. In fact, many of the outlier companies expand outside a box to span multiple boxes. And this feels particularly true in the AI era, where many of the fastest growing companies are gaining adoption from both consumers and enterprises.

For those founders ambitious enough to build for both, seek out investors who dream with you instead of limiting you. Yes, focus matters, especially in the early days. It’s extremely hard to serve multiple types of users and customers. You’ll have pressure to choose who to focus on. One of the trickiest decisions if your product starts self-serve, growing with consumers but organically also getting enterprise pull, is when to build an enterprise-grade product and go-to-market motion. Getting the sequencing and prioritization right will be key to your success.

But if you have the vision, and if your product starts to catch fire with both consumers and enterprises, you just may be on your way to building a company that breaks the mold. As one founder building a consumer and enterprise company said recently: “let your own conviction and your users prove you right, not investors.” Work like hell, aim high, be bold, and you too can build the next big thing.

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P.S. I still haven’t come up with a pithy name for these companies - ala Unicorn, Thunder Lizard, Narrative Violation, Compound startup.

Any ideas? For example, Chimera and Hydra are both multi-headed mythological monsters. Composite and Conflux are both words describing multiple elements coming together to form one. Would love your suggestions!

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I started next big thing to share unfiltered thoughts. I’d love your feedback, questions, and comments!

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