How AI Is Changing Strategy—and 4 Skills Leaders Need Next

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Ethan Mollick (0:56)

One of the most depressing things I see when I talk to boards of very large companies and to C-level leaders is a lot of them have come to believe they just can't change, right? So I show them what AI can do and they're like, well, I guess we'll ride this out. And like, that's an insane answer. You have 100,000 people working for you. The smartest people in the world are working for your company. You have customers and resources. The idea that you can't be flexible, compete seems to be overly baked in right now.

SPEAKER_5 (1:26)

Ethan Mollick, Professor at Wharton and author of Coexistence. Welcome to the IdeaCast.

Ethan Mollick (1:32)

Thanks for having me.

SPEAKER_5 (1:33)

Yeah. So you've been closely tracking advances in AI and constantly experimenting with all the new tools. What is different today than even a few months ago in terms of how new developments should guide the way that leaders are thinking about strategy in particular?

Ethan Mollick (1:51)

One is the exponential curve continues. AI just keeps getting better. There isn't really a sign of that stopping right now. And the second is that agents are real, which are AI tools can go off and do work on their own autonomously and do real process work, real important things.

And that has become a viable approach to work in the near past.

SPEAKER_5 (2:10)

It seems like a lot of companies right now are thinking of AI as really a productivity exercise. You know, you're automating tasks, you're saving time, you're reducing costs.

How does a genuinely strategic AI transformation strategy differ from that? What do you think companies should be doing now?

Ethan Mollick (2:32)

I think it's actually pretty hard to do a few things. One is viewing this purely as a productivity tool gets you in trouble in a lot of different ways. People are getting ROI from AI, right? They're getting ROI from that productivity gain. Productivity gains are real.

The problem is that those productivity gains get eaten up by the organization, which is, if you don't change a part of the process, AI is mostly a single player entity and you end up with more of everything. If you don't change your KPIs, people can produce more PowerPoint, they produce more code. That's not actually what you want. Leadership needs to decide what this thing is. The second is, AI is getting very capable. I worry that if our default is automation, we end up with a situation where we just keep handing tasks to AI and don't think hard enough about where humans fall into this process, and that leads to a lot of danger as well.

SPEAKER_5 (3:12)

Is your argument that leaders need to move from asking where can we use AI in this existing business alongside humans to a question that's more like, how does AI change our business going forward?

Ethan Mollick (3:30)

At this point, we have ample evidence that AI can regularly do the kind of work that would take a human to 18 weeks in a reasonable amount of time, a reasonable amount of money with high success rates. That implies a lot of different things. That implies that what your organization does has to change. How you think about the boundaries between jobs is changing. I talk to C-level leaders all the time, and one of the first effects they see of AI, and we saw this also in our research, is that jobs start to blur. Coders do design work, designers do coding, product managers do everything. How do you start thinking about what the boundaries of your organization are? What's the product you're trying to produce? Is it an interim product or PowerPoint? What was the point of the PowerPoint in the first place? You start to run into really fundamental questions about what the goal of the organization is, how you accomplish that, what are your values for getting there? And they're urgent. This isn't sort of theoretical, you know, let's sit down in an academic way. It is your organization already changing from the inside. What do you do about that?