In the past, disruption was about whether or not incumbents adopt new technologies. It went something like this:
- A new technology is cheaper and has some advantages, but mostly worse.
- The ‘mostly worse’ combined with the inertia of the existing business incentivizes incumbents to avoid adopting the new technology.
- The new technology eventually becomes ‘better enough’ through lower costs and improvements, enabling startups to disrupt incumbents.
Degree, not adoption
But with AI, it’s not about adoption. Adopting AI is table stakes. The danger for incumbents is the degree of AI adoption.
It’s easy to superficially integrate AI to claim you have an AI strategy. However, creating a compelling product predicated on post-AI assumptions requires rebuilding it from the ground up, which is not in the rational self-interest of incumbents.
This is even harder than past decisions about whether or not to adopt new technologies because, with AI, you can fool yourself into thinking you’ve gone far enough.
How far is far enough?
AI is such a game-changer that we have no idea what ‘far enough’ means because it’s so new and will continue to evolve with AI and customer expectations. So, the best we can do is run in that direction as fast as possible, which is hard to do with the baggage of an existing business.
Startups are uniquely suited to this because they have less (if any) baggage and are, by definition, bets on a different future.
A lens to see further
One useful lens for pushing firther with AI to consider UI as a crutch for human constraints. This helps illuminate how AI can fill the gaps in experiences and replace many complex UIs predicated on pre-AI assumptions.
So, consider all existing companies with complex product UIs like Adobe, Microsoft, and thousands more. How many are willing to rebuild their products based on post-AI assumptions, knowing it will upset their existing (profitable) customer base? Not many, and that’s the opportunity for startups.
Read more thoughts onย how to build AI products here.
This post was inspired by Jason’s excellent post on strategies for AI startups.
