You know how the CEOs of AI companies like Anthropic and OpenAI keep making these big predictions? Sometimes it's hard to tell. Are they delusional, is this just marketing, or are they actually right?
I had this exact conversation with Maurizio Cuna, a Partner at Infosys Consulting who's been working with enterprises for 20+ years. He brought up something that really stuck with me.
I watched a documentary about the International Space Station (ISS) a while back. It illustrates the point perfectly. In it, astronauts wonder why people on earth don’t see why we should cooperate because it’s just one big unified planet. How when you're up there, it's just one big team traveling through space. People should do the same. But these are highly trained people, probably some of the smartest alive, who've spent their whole lives learning to cooperate under high-stress situations with different nationalities.
The rest of us? We're not trained to that level. We're talking billions of people trying to figure this stuff out, not 20 people on a space station.
Maurizio sees the same thing with AI adoption in enterprises. Just because the technical founders can use these tools effectively doesn't mean everyone else will adapt quickly. People need time to experiment, find use cases, fail a bunch of times, and keep going until something actually works.
With that being said, there's this widening chasm between people who are technical (not necessarily coding, just comfortable with the tools) and those who aren't using AI at all.
His perspective on navigating this uncertainty, especially from someone who's seen 20 years of technology hype cycles in large organizations, is genuinely refreshing.
Watch the full conversation here: https://youtu.be/zx5NzJq6WGo
You'll get his framework for separating signal from noise, plus insights on what executives are actually thinking about AI adoption right now.
Cheers,
Kenny