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If the defining maxim of the social media age was: you What new economic metaphors will the transition to AI spark?
The key difference between AI startups and mobile-era software companies is how they view the work and value of new user acquisition.
User growth has been the coin of this realm for the past few decades, as vividly depicted in a defining scene from “Silicon Valley.” Why look for a revenue stream when an app developer can simply run a “pre-revenue” company? After all, investors will begin to judge your company’s financial performance once the revenue is shown. Rather than worrying about making a decent amount of money now, it’s better to chase your dream of earning a big salary in the future.
The AI infrastructure investment train is, in a sense, implementing this strategy. Spending is the new growth. But something has changed.
“AI-driven startups are building businesses that are very different from the highly successful but now outdated ‘software-as-a-service’ (SaaS) business model,” DataTrek co-founder Nicholas Colas wrote in a note to clients earlier this week. So this is not your grandfather’s SaaS.
Growth remains important. But the economics of AI, or the huge computing costs associated with training and running models, are forcing next-generation technology companies to pivot their sales strategies.
The barrier to becoming an “AI company” is now incredibly low. For those with the courage and entrepreneurial spirit, explore coding your home office atmosphere. But while revenue growth from every new customer was almost pure profit for software startups in the previous period, AI startups now face tough computing costs, Colas noted.
Software companies were obsessed with renting out their platforms in exchange for a fee, with the mantra of swallowing users and growing at all costs. As Colas observed, the tech giants also built their customer relationships on a fixed-fee model.
In contrast, the new generation of AI startups should focus on paid options from the beginning. Having the “right” users (e.g. early adopters willing to put in the cash) is more important than pure growth. And most importantly, because computing costs are so high, the sales model will be proportional instead of flat.
“This difference is one reason why AI is so highly valued,” Collas wrote. “These companies intentionally set prices to shift profits from users to their own profit and loss statements.”
