Not so long ago, AI startups were the new shiny object that everyone was getting excited about. It was a time of seemingly infinite promise: AI was going to not just redefine everything in business, but also offer entrepreneurs opportunities to build category-defining companies. A few years (and billions of dollars of venture capital) later, AI startups have re-entered reality. Time has come to make good on the original promise, and prove that AI-first startups can become formidable companies, with long term differentiation and defensibility. In other words, it is time to go from "starting" mode to "scaling" mode.
Federico Antoni is managing partner at ALLVP, an early-stage VC based in Mexico. He is a lecturer in management at the Stanford Graduate School of Business. "Over the last couple of years, a billion new people have joined the super-connected world. Billions more around the developing world, now, walk with a high-speed computer in their pockets. And yet, they don't have a bank account, a formal education or access to most of the services we take for granted in the U.S. Imagine the possibilities… imagine how you can change the lives of billions of people."
Summary: The results are in. There is only one demonstrably successful strategy for creating big wins for AI-first companies. We'll briefly summarize the other contenders that have fallen by the wayside and then lift the curtain on the winner. For the last three years we've been close observers of exactly what makes a successful AI/ML strategy. In addition to our own observations we've been listening closely to VCs and how they describe their internal process for deciding who to fund.
Not all applications are ready for AI, despite recent major advances in the field and enabling infrastructure. Anxiety over the prospect of being disrupted is prompting leaders in all industries to experiment with AI-powered solutions. This makes it difficult for aspiring entrepreneurs to distinguish C-suite curiosity from a long-term intention to buy. If AI startups want to move their work beyond the pilot stage toward sustainable, long-term growth, they should avoid chasing opportunities where the stakeholders are not culturally ready for AI, or where more effective technology could be applied. Before you even start working with a potential customer's data, you need to understand the ABCs of AI-readiness: Acceptance, Better Solutions, and Costs.
Sony showed off its AI-enabled Aibo robotic dogs on Nov. 1, 2017. There's been so much hype in recent months around opportunities in artificial intelligence that it's starting to feel a bit like a second gold rush. Just like in 1849, in 2017 there are a lot of people who want to get in on the AI action. And like the prospectors who came before them, they'll be forced to sift through a lot of gravel to find gold. You might be forgiven for dismissing the current rush to build companies around AI as another tech fad.