If you read any news about business, technology or startups today, you’re almost certain to find at least one mention of AI. And with good reason: Tech is on the hunt for its next growth vector.
Over the years, we’ve seen lots of interesting technologies strive for that mantle. From blockchain-based technology, to AR and VR for both consumer and enterprise applications, to creator-focused platforms, the list is long indeed.
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Most of those technologies, however, lost much of their luster when it became clear that it would take much longer than many expected for them to reach mass adoption. In some cases, the technology was not ready for everyday use, or it wasn’t as applicable for corporate or consumer usage as everyone thought. In many cases, they were simply too unwieldy to implement.
AI is the latest in that long line of hopefuls. Indeed, it has pretty much earned its place: Large language models are incredibly interesting and can serve a host of new and existing applications. Invariably, that has spurred public-market investors to expect tech companies to unlock new opportunities for growth from AI. Tech CEOs feel the same way, as do venture capitalists.
The industry is suffused with incredible optimism around the use of new AI technologies. Money is flowing into companies of all sizes and shapes that want to build AI models, help customers train and use those models, protect data from (or conserve information inside) LLMs, or apply the technology directly for various use cases.
It’s still unclear how all these new AI-related features and tools will be monetized, but everyone generally seems to agree that this New Thing really does have legs and it’s reasonable to be optimistic about AI’s impact on our lives.
I’m here for it. But I am also worried about who is going to make all the money.
It’s a rich company’s world
Rewinding the clock to July, Reuters noted that of the $173.9 billion that PitchBook counted in the first half of 2023, venture capitalists “poured more than $40 billion into AI startups.” That’s almost a quarter of all the money invested in that time — a simply immense portion at a time when VC activity is declining around the world.
Yet, we already have some companies that are doing well with their AI offerings. Microsoft remains the quintessential Big Tech example, as it is using generative AI inside of GitHub to bolster that revenue stream and has introduced other AI tools inside of Office products to the same effect.
More recently, we learned that OpenAI is apparently generating around $80 million in monthly revenue, which grants it an annual revenue run rate of around $1 billion. Sure, it’s not ARR in the SaaS context, but that’s still a lot of revenue growing rapidly from a far smaller base.
It’s clear that some companies will successfully use generative AI inside their products and tools. The general vibe, as far as I can tell, is that the more a company is involved in a customer’s operations (or works with their proprietary data), the greater the chances that it will be able to use new AI tech in its product, and probably juice that tech for new revenue sources or at least augment existing ones.
Venture capital investors obviously expect startups to win a piece of the pie, given that they’ve bet $40 billion (which could be rephrased as several dozen billions of dollars) in just the first half of 2023. Tech is hunting for its next growth engine, and if it’s AI, startups are set to do well, right?
Maaaaybe.
Every time a new area of investment opens up, investors invariably pour capital into it. That inevitably leads to distortions, inflated valuations, and some high-profile missteps. Such is the investing cycle of the private market. Exuberance, of course, is hardly constrained to venture investors and startups; public-market investors can get just as far over their skis. We’re not alone in noting that this is likely happening with AI startups as well: The Wall Street Journal this week published an entire article titled “AI startup buzz is facing a reality check.”
I wonder, however, if smaller startups are at an insurmountable disadvantage in the AI race when it comes to leveraging LLMs and related technologies as effectively as their larger rivals. Here’s how the argument could be phrased:
- Salesforce will have an AI strategy because it has lots of customer data that exists nowhere else.
- Microsoft will have an AI strategy because it operates with a great fraction of the world’s corporate workload.
- Startups, in contrast, lack the same scale of customer data and rarely find themselves as deeply integrated into customer workflows.
- Thus, startups are largely facing a future in which they are at a disadvantage to their largest, wealthiest competitors in the AI era.
There are and will be exceptions to these, of course, but the nature of AI makes it sort of unwieldy for a small business. A SaaS tool can be built by any company of any size in any part of the world, and it could do well, but AI is not simply well-written code, good design and an innovative go-to-market strategy. It is a layer of learning atop a mountain of data and analyzed action. Startups may find it very hard to build a real moat for their products in a market where they lack both of the possible fulcrum points for AI usefulness we mentioned above.
I hope that startups do well in the generative AI era, build lots of cool stuff and tackle a giant or two. Capitalism without creative destruction and startups rolling out the guillotine is simply corporate fan fiction, and that can be worse than some real fan fiction.
But given what I am hearing from CEOs of public companies — they expect data wealth and workflow integration to prove key to their AI efforts — I am worried that startups are at a disadvantage, at least when it comes to this tech moment.
Big Tech has fared well in the tech shifts of the recent past, despite startups eking out wins here and there. Alphabet and Apple cornered the mobile OS market, and Google’s browser tech dominates the web-browsing market on any platform, for example. If AR and VR had taken off, Meta and Apple would have been in a position to win in that market, too. In crypto, the latest bit of significant change came with the introduction of Base, a blockchain backed by Coinbase, an incumbent.
We’ll see how it plays out, but it really does seem like the biggest tech companies are best positioned to win the AI war — so long as the tech lives up to its own hype, of course.