How to Work, Hire, and Lead in an AI-First World

How to Work, Hire, and Lead in an AI-First World

When Duolingo cut 10% of its contractors, they didn’t sugarcoat it. They said AI could do the work faster and better. 

Shopify took a different approach but sent the same message. Before any team can request a new role, they have to prove a human is essential. As Shopify CEO, Tobi Lütke put it, “No new hires without proof AI can’t do the job.”

What both companies are signaling is something bigger than cost-cutting or tool adoption. Some call it “AI-first,” and it’s changing who gets hired, how teams function, and what people are expected to deliver. 

And it’s not limited to a few tech outliers. According to McKinsey’s latest State of AI report, the percentage of organizations using AI in at least one business function is climbing fast. The chart below shows just how sharply adoption has accelerated.

So given all the buzz about being AI-first, it’s worth asking: what does it mean, and how should you be thinking about it?

Here’s what you need to know.

What It Means to Be an AI-First Company

An AI-first company embeds AI into every system and department. 

Microsoft’s 2025 Work Trend Index, calls this the rise of the "Frontier Firm," an emerging model of companies designed for human-agent teams, intelligence on demand, and widespread AI integration.

According to McKinsey, frontier companies share six traits that set them apart. The factors are:

1. AI sets the direction: These companies align leadership around a vision for how AI creates value. Strategy starts with what AI can do and builds from there.
   

2. Talent builds leverage: They hire and develop people who know how to work with AI. Skills like automation, prompt writing, and workflow design are expected, not optional.
   

3. Work is designed for systems, not silos: Business, tech, and operations are tightly connected. AI is embedded in how work happens, not treated as a separate track.
   

4. Technology drives results: Tooling is selected based on performance and impact. Teams move fast to adopt what works and let go of what doesn’t.
   

5. Data and AI drive decisions: Strategic choices are shaped by systems that analyze patterns and surface what humans are likely to miss. The better the data, the better the results.
   

6. Activation and scaling are built in: AI isn’t useful without follow-through. These companies focus on rolling out tools across the business, measuring what works, and managing risk without slowing down.

Or as Duoling CEO, Luis von Ahn, says, “It’s about removing bottlenecks so employees can focus on creative work and real problems, not repetitive tasks.”

What happens when you go AI-First

There are clear upsides: faster cycles, leaner teams, more room for creativity. And less time spent on repetitive, low-leverage work.

People get to focus on strategy, ideas, and collaboration rather than admin and grunt work.

But there are tradeoffs.

When AI becomes the default, we can’t deny the impact on jobs. Some are going to disappear. The remaining team members are likely to experience higher pressure to perform and company culture can take a hit when change outpaces communication. 

For employees, this changes the rules.

Roles are moving from task-based to value-based. It’s less about what you do and more about what outcomes you create. Experience still matters, but it doesn’t outweigh your ability to use AI to move faster or make smarter decisions.

What does it take to adapt?

The disruption is real, but ignoring it isn’t an option. Whether you're leading a team or building your own path, here’s how to start moving forward.

If you’re leading a team: 

Start by analyzing how your team gets work done. Identify the repeatable tasks and hand them off to automation. 

Redesign systems so people are focused on judgment, creativity, and speed, rather than admin. Make AI fluency a skill everyone’s expected to build. 

Train across departments. Set expectations. Track performance and keep improving.

If you’re building a career:

Focus on outcomes not tasks. Build automations where you can. Understand the tools in your tech stack well enough to know where they work and where they fall short. If your organization offers training, take it and if they don’t suggest leading lunch and learns or peer sharing sessions.

What used to be optional is now the starting line

We’re past the phase where experimenting with AI feels innovative. The companies and individuals pulling ahead are the ones treating it as foundational rather than optional.

“AI literacy in some form or another will be a baseline expectation for all employees. This is now the most in-demand skill of 2025.”

— Paul Roetzer, CEO, AI Marketing Institute

As Paul says, this is the new baseline. And the people who know how to build with it will shape what comes next.