By Jason Hauer
At Davos this month, Anthropic CEO Dario Amodei predicted that half of all entry-level white-collar jobs could disappear within five years. Software engineers, he said, might be obsolete in 6 to 12 months.
Some dismissed this as hype. Others panicked. Both reactions miss the point.
The debate about whether AI will transform work is over. The question now is whether you'll be the one doing the transforming or the one being transformed. And that question isn't really about technology at all. It's about agency.
I keep seeing the same pattern. The companies that invested in AI-native capabilities 12 to 24 months ago aren't just moving faster. They're learning faster. Every cycle feeds the next. Every insight compounds. 2024 was experimentation. 2025 was when the leaders started building real systems. 2026 is when the gap becomes structural.
But here's what's interesting: the gap isn't about who has access to the best models. Everyone has access to the same models. The gap is about who's willing to actually redesign how work gets done.
McKinsey found that only 6% of organizations have achieved meaningful bottom-line impact from AI. The other 94% are stuck in what the industry now calls "pilot purgatory." They have the tools. They've run the experiments. But they haven't captured the value. Why? Because they're layering AI onto old structures instead of building new ones.
That's not a technology problem. That's an agency problem.
Brian Tracy taught me something in my twenties that I think about constantly now. He called it internal locus of control. Draw a circle. Everything important in your life goes either inside the circle (you control it) or outside (you don't). High performers put everything inside. Not because they're delusional about obstacles. Because they treat every obstacle as a skill issue.
I can learn that. I can figure that out. I haven't solved it yet, but I will.
Nate Jones has been writing about this same idea. He calls it "high agency." The barriers that used to take years to overcome can now be addressed in weeks. You can learn while building instead of learning for years before building. But the mindset has to come first. The tools are useless without the belief that it's yours to figure out.
I see the opposite constantly. Smart people. Good intentions. Waiting for permission. Waiting for certainty. Waiting for someone else to go first.
This plays out at the organizational level too. The 94% stuck in pilot purgatory have external locus of control baked into their culture. AI transformation is "waiting on IT." Innovation is "blocked by budget." Speed is "limited by the org chart." They're not in control, so why try?
The 6% put it all inside the circle. They own it. They figure it out. They keep building.
So what does high agency actually look like when you're redesigning work around AI?
It starts with how you think about the human-machine relationship. Royal Philips CEO Roy Jakobs put it well at Davos: "When you are going to adopt new workers into your workforce, you need to rethink how the team is going to play together." He wasn't talking about hiring humans. He was talking about integrating AI as a participant in how work gets done.
If you treat AI as a cost-cutting tool, you'll optimize for the wrong outcomes. If you treat it as a productivity enhancer, you'll get incremental gains. But if you treat it as a new category of worker that requires thoughtful integration, you open the door to transformation.
The critical shift is from prompting to delegating. The old model was quick exchanges: prompt, response, iterate. The new model looks more like managing a capable junior analyst: brief, delegated assignment, intermediate checks, deliverable. That's the same transition you made when you went from individual contributor to manager. And most of us, if we're honest, never learned to delegate well in the first place.
The marketing manager who can orchestrate five AI tools to launch a campaign in a day isn't doing the same job faster. They're doing a fundamentally different job. Less execution, more judgment and creative direction. The burden shifts from task completion to system design and expert human guidance that ensures outcomes exceed expectations. That's what value creation looks like in an AI-native organization.
But this only works if leaders are willing to confront the hard questions. When AI handles 60% of a marketing campaign or the first pass on a financial analysis, who reviews it? How do you measure the human's contribution? What happens to the junior roles that used to do this work? How do people build expertise when they skip the foundational tasks?
ManpowerGroup's research shows that 70% of the skills needed for the average job are expected to change by 2030. Yet 55% of employees report receiving no workplace training in the past year. That's not a skills gap. That's a leadership gap.
Mercer found that 62% of employees feel their leaders underestimate AI's emotional and psychological impact. People aren't just worried about losing their jobs. They're worried about losing meaning in their work. Leaders who ignore that reality will face engagement problems that no technology can solve.
Here's what doesn't get talked about enough: this isn't just an efficiency play. It's a growth play.
The organizations redesigning work around AI aren't just cutting costs. They're compressing time-to-market. They're validating product concepts in weeks instead of quarters. They're enabling commercial teams with intelligence that actually closes deals. The ROI conversation has shifted from "how much can we save" to "how fast can we grow."
Cognizant's research estimates that current AI technology could unlock $4.5 trillion in U.S. labor productivity. But as their CEO Ravi Kumar noted at Davos, that value only materializes "if you start to think about reinvention of existing businesses." Not optimization. Reinvention.
The companies capturing that value aren't the ones with the biggest AI budgets. They're the ones where leaders model the change themselves. McKinsey found that high performers are three times more likely to say their senior leaders demonstrate ownership of AI initiatives. Not delegation to IT. Active engagement, including using the tools themselves.
That's agency. That's putting it inside the circle.
The future of work isn't something happening to us in 10 years. It's something we're building right now, whether we're intentional about it or not.
Randstad CEO Sander van't Noordende called 2026 "the year of the great adaptation." He's right. But adaptation isn't something that happens to you. It's something you choose. It requires tolerating the discomfort of redesigning how work gets done. It requires accepting that the org chart you have today probably isn't the one you'll need tomorrow. It requires believing that you can figure it out.
The tools have never been more accessible. The only question is whether you believe it's yours to figure out.
AI doesn't need to happen to your people. It can happen with them. But only if you do the work to make that possible.
Jason Hauer is CEO and Founder of HauerX Holdings, a portfolio company that backs and builds AI-native enterprises focused on compressing enterprise growth from months to days.
