Catalog & Cocktails: The Honest, No-BS Data Podcast
Oct 16, 2026 · 5 min · 3 segments
This is the takeaway episode with Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo. He recently visited Juan and shared his framework on talent in…
Juan SequedaHostMohammed, you've been thinking about people in this new AI age in a different way, and tell us about it.
And so you said, "Hey, if we think about what's happening in this AI first world, automation's happening at scale.
Um, we're moving from humans being sort of this key resource," let's use that word because I know it's kind of an intense word, right? On the, on the assembly line, and instead being this spark that is a part of this innovation engine.
Uh, and so I think that's, that's a very interesting framing for this, this framework that you went into, which is that, hey, u- use an analogy, right? Like, hey, the best taxi, is it gonna get you to the airport, what, 10, 15% faster? But when you think about knowledge work and the work of the future, there's, uh, an opportunity for people who excel in a couple of different dimensions to 5X, 10X, 50X, 100X, 1,000X, right? And these are the people, or more, maybe more importantly, these are the skills ultimately that we want to, that we wanna nurture, we wanna lean into.
Um, and those two dimensions were more of the learning axis, and then more of the drive and entrepreneurship axis.
People can have sort of different roles or personas depending on where they are in this.
And, and what's important is, and I asked you a little bit about, like, h- why is this the optimistic view versus the pessimistic view? You know, the pessimistic view would kind of be like, you know, hey, like, you know, a lot of people are gonna be out of a job right now, you know, soon because, you know, you don't fit the, the framework.
... to invest in people and expand their skillset and give them more space, right? Which I, which we, we didn't talk about directly, but I think was implied by a lot of what you were saying.
... on the job, to try new things, to experiment, and then leverage automation and all these things that can help to actually then lock in your, you know, 1,000X impact.
That, that's like a way for us to really change what we do and have a bigger impact in organizations to affect the outcome.
And I think an important thing you noted was instead of being so focused on the, the known, right? The known is gonna be automated.
And, you know, for some people that may sound like hell on earth, but for a lot of people it probably sounds actually like heaven on earth because it means we're back to the age of innovators and explorers, right?
Mohammed, you've been thinking about people in this new AI age in a different way, and tell us about it.
And so you said, "Hey, if we think about what's happening in this AI first world, automation's happening at scale.
Um, we're moving from humans being sort of this key resource," let's use that word because I know it's kind of an intense word, right? On the, on the assembly line, and instead being this spark that is a part of this innovation engine.
Uh, and so I think that's, that's a very interesting framing for this, this framework that you went into, which is that, hey, u- use an analogy, right? Like, hey, the best taxi, is it gonna get you to the airport, what, 10, 15% faster? But when you think about knowledge work and the work of the future, there's, uh, an opportunity for people who excel in a couple of different dimensions to 5X, 10X, 50X, 100X, 1,000X, right? And these are the people, or more, maybe more importantly, these are the skills ultimately that we want to, that we wanna nurture, we wanna lean into.
Um, and those two dimensions were more of the learning axis, and then more of the drive and entrepreneurship axis.
People can have sort of different roles or personas depending on where they are in this.
And, and what's important is, and I asked you a little bit about, like, h- why is this the optimistic view versus the pessimistic view? You know, the pessimistic view would kind of be like, you know, hey, like, you know, a lot of people are gonna be out of a job right now, you know, soon because, you know, you don't fit the, the framework.
... to invest in people and expand their skillset and give them more space, right? Which I, which we, we didn't talk about directly, but I think was implied by a lot of what you were saying.
... on the job, to try new things, to experiment, and then leverage automation and all these things that can help to actually then lock in your, you know, 1,000X impact.
That, that's like a way for us to really change what we do and have a bigger impact in organizations to affect the outcome.
And I think an important thing you noted was instead of being so focused on the, the known, right? The known is gonna be automated.
And, you know, for some people that may sound like hell on earth, but for a lot of people it probably sounds actually like heaven on earth because it means we're back to the age of innovators and explorers, right?
The rest of this transcript — segmented and speaker-labeled, so you land on the exact moment something was said
Search every transcript — by keyword, by phrase, or by meaning, across every show Radar indexes
Trends — what is surging across podcasts, measured against its own baseline
Alerts — when a name you follow appears in a newly indexed episode
No account is needed to search Radar.
