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Let’s face it: tech marketing has muddied the waters for investors looking for real AI companies. As we’re all aware, not all AI companies have actual AI as their core value proposition. 

You can break out AI companies into two categories: ones that use AI as a medium, or as an add-on to automate a certain function. And others whose entire raison d’être depends on AI.  As an AI practitioner and investor, I am biased. I believe companies that do real AI are being unfairly grouped with companies that merely use AI as a function, often couched under “automation.”

We’ve all read this story before. It’s reminiscent of the early cloud days, where a bifurcated ecosystem of companies emerged. On one side, we had the companies that were born pre-cloud; on the other, we had the “cloud-first” batch.  The latter is the equivalent of what we’re seeing today with AI — companies born far enough into the maturity lifecycle of AI that they could build companies that are entirely powered by AI. These are companies that think differently and that unlock true innovation. 

Words matter — you can’t simply tack on ‘AI’ to your solution and call it real AI

Not to introduce more industry jargon, but I am going to — because we need clarity in this space. Companies that do real AI are what I call AI-native. And if AI is not the reason it exists; it’s not AI-native. Plain and simple.


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Let’s take a quick quiz. Is YouTube AI-native? If yes, you’re disqualified. If no, ding, ding, ding! YouTube merely uses AI as a medium to drive consumption, but it’s not central to the user experience like it is for, say, TikTok. TikTok decided to put AI to work for creators too, with editing tools and enhancement suggestions that resonate with the audience they want to reach. 

By making AI central to its service, they’ve created a new innovative category for making videos that enable people to change their faces, control video elements with facial expressions, etc. That is what makes many TikTok videos nearly impossible not to watch repeatedly. 

For another example of AI-native, take Insitro, which is an AI-native company building disease models from large-scale automated experiments with the goal of developing new therapies. Parsing huge volumes of clinical and genetic data, these models can determine “how a disease works” and help identify new subtypes of disease — and ultimately assess which patients are most likely to respond to a given therapy. This is only possible because of machine learning due to the very large number of confounding factors at play.

Here’s another example that will help crystallize my point. Ask yourself: why are (EV-native) cars like Tesla and Rivian so different from other traditional (gas-first) car manufacturers entering the EV race? The end game may be the same, but the products don’t compare.

In the last decade, we’ve seen AI-washing take over. In many cases, AI has become a buzzword to mean anything with some form of algorithmic “intelligence”—from traditional functions like insurance and financial management to placing the right ads in front of people. 

Looking to invest in AI-native? Make sure you’re asking the right questions.

Unsure as to how to tell between an AI-native from a non-AI-native one during a pitch? Lead with these questions and you’ll get the answer rather quickly:

  • Question: Why is this real AI? 
    • If, for example, the answer is something to the effect “our platform boasts an automation engine to streamlining workflows,” probe further. 
    • If you get some wishy-washy answer like, “it has some data and some logic,” something is fishy. 
    • Or if you get a jargon dump to the effect of, “it’s a database plus a best-in-class sophisticated query engine,” run. 
  • Question: What was built first, the model or the company / solution? 
    • If the answer is something to the effect of, “well, we focused on the user experience and then applied algorithms to streamline the workflows engine,” it’s not AI-native. 
    • If there’s language about “layer in” AI after the fact, or that we’ve “built a sophisticated AI engine on top,” you know it’s likely not real AI.
  • Question: Is AI a boardroom conversation at the company? You know AI is not core to the company when….
    • The word AI appears on a slide and everyone is surprised and befuddled. 
    • When the founder says, “the board slides were generated by AI.”
    • If the board meeting starts with a TikTok.

To sum up my argument: I applaud any ethical use of AI. But calling any company that makes some use of AI an ‘AI company’ undermines companies doing deep AI work or AI-native products; it’s also misleading and potentially risky from an investment perspective. 

So, next time you get the inkling to use the word AI to describe a company, think about these points, perhaps even ask yourself the questions above. If in the end, you realize you’re not AI-Native, that’s perfectly ok—just be more thoughtful about the use of the word ‘AI’ for the sake of clarity in the industry. I think we can all agree that we need it.

Luis Ceze is a Venture Partner at Madrona Ventures and CEO of OctoML


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