What Does It Mean To Be "AI-First" Anyway?

AI leadership isn’t just about tools, but about rethinking how people work, learn, and lead

In the past month its been in vogue for public company CEOs to proclaim they are going “all in on AI” or being “AI-first”.

It started with Tobi Lutke, the founder and CEO of Shopify, sharing a memo with his entire team in April where he declared that “Reflexive AI usage is now a baseline expectation at Shopify.” He described one of the key tenets of this policy below:

Using AI effectively is now a fundamental expectation of everyone at Shopify. It's a tool of all trades today, and will only grow in importance. Frankly, I don't think it's feasible to opt out of learning the skill of applying AI in your craft; you are welcome to try, but I want to be honest I cannot see this working out today, and definitely not tomorrow. Stagnation is almost certain, and stagnation is slow-motion failure. If you're not climbing, you're sliding.

And just last week, Duolingo (which has an incredible $24B market cap with its stock up 5x+ over the past two years!) followed suit with CEO Luis von Ahn proclaiming “Duolingo is going to be AI-first” in a similarly themed company-wide memo. He went further to say that Duolingo would “gradually stop using contractors to work that AI can handle”.

Then came the backlash.

Thousands of Duolingo customers and users flooded social media to convey their disappointment in the company allegedly replacing people with AI or accusing Duolingo of removing humanity from the app. From one user: “Deleted Duolingo last week. A 650+ day streak never felt so meaningless once I saw the news.”

We believe this simple argument misses the point on both sides. While we wholeheartedly believe that AI is the most significant supertrend of our time, we also understand the skepticism and fear from those who fear losing their livelihoods due to AI.

The key question is: what does it mean to be AI-first anyways? We believe it is in rethinking workflows, reducing rote mental load, and unlocking strategic and creative capacity.

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We’ve Been Here Before

When we talk about going “all in” on AI, it’s easy for people to assume it instantly means a 1:1 replacement of humans. But history tells a very different story. Every major technological shift has created fear about obsolescence—but in practice, these shifts have consistently elevated the nature of work, not eliminated it.

🖥️ The PC Revolution: From Typing to Thinking

In the 1980s and ’90s, the rise of the personal computer raised alarms about the future of administrative and clerical roles. Word processors and spreadsheets were seen as tools that might make secretaries and office staff irrelevant. But instead of mass displacement, what actually happened was role evolution. Secretaries became executive assistants, office managers, and operations coordinators. The PC didn’t just reduce typing time—it unlocked productivity, analysis, and communication at scale.

Every knowledge worker today uses tools like Excel or Google Sheets—not because they replaced a job, but because they expanded the scope of what one person could do.

An actual headline from the New York Times in 1982

🌐 The Internet Era: From Retail to Reinvention

E-commerce brought fears that traditional retail jobs would disappear entirely. And while it’s true that some sectors faced disruption, the internet also gave rise to entirely new industries and job categories: digital marketing, online customer support, e-commerce logistics, SEO optimization, Shopify storefront management—none of which existed in the pre-internet economy.

What mattered most was whether companies adapted. The winners weren’t the ones who resisted the internet; they were the ones who restructured around it—rethinking how products were sold, how customers were engaged, and how operations were run.

And the punchline is - the ENTIRE size of the retail segment has grown substantially since the early 2000s, with e-commerce englargening the entire pie.

📱 The Mobile Shift: A UX Wake-Up Call

When smartphones went mainstream, they forced companies to rethink the fundamentals of how their services were delivered. Responsive design, app stores, push notifications, and real-time engagement became table stakes. But mobile didn’t replace product managers or marketers—it demanded they upskill, adopt new toolkits, and deliver value in different formats.

The mobile-native mindset created jobs like app product managers, growth hackers, and mobile UX designers, while also dramatically increasing reach and engagement for businesses that embraced it.

So What Really Matters?

In each case, the companies that came out ahead weren’t just the ones who used the new tech—but the ones who restructured around it. They reimagined roles, workflows, and outputs. They leaned into the idea that technology removes friction so people can focus on higher-order tasks: strategy, creativity, judgment, and relationship-building.

AI is the next iteration of this pattern. Like those before it, its real power lies not in automating humans out—but in amplifying what humans are capable of.

So what should CEOs be doing to lead their teams through the AI shift?

• Lead with change management, not just model deployment. Rolling out AI tools is easy; aligning workflows, incentives, and mindsets around them is the real leadership challenge. AI implementation without cultural adaptation fails fast.

• Reskill, restructure, and retrain—don’t just replace. Identify where roles will shift, and invest in helping teams grow into new capabilities. Frame this as evolution, not elimination.

• Celebrate “AI fluency” as a superpower. Highlight employees who integrate AI tools creatively and productively. Make them role models—not targets of skepticism or envy.

• Reimagine workflows from first principles. Don't just plug AI into existing processes. Ask: “If we were starting this team today with these tools, what would it look like?”

• Involve employees in the transformation. Treat them as co-creators in AI-driven redesign, not passive recipients. The people closest to the work often have the best ideas for intelligent automation.

Conclusion: AI-First, If Done Right

There’s no question that some CEOs could be more thoughtful in how they communicate their company’s AI ambitions. Bold declarations without nuance can come off as tone-deaf, especially when they imply that humans are being replaced rather than empowered. But beneath the phrasing lies a reality: we need to be figuring out how to integrate AI into our daily work in every way. The way we work in 6 months, and certainly in 3 years, will look meaningfully different than it does today.

To be “AI-first” isn’t about chasing hype or rushing to automate. It’s about evolving workflows, upskilling teams, and unlocking capacity for higher-order thinking. The companies that thrive in this transition won’t be those that simply deploy new tools, but those that rethink roles, culture, and incentives from the ground up. We believe there will be new jobs that are created as a result of this and many people who will be empowered to do new jobs that they may previously have not been able to (e.g., everybody may now be ‘code’ literate).

History has shown us that technology doesn’t eliminate human value, it reshapes it. AI is no different. The real opportunity is to pair machine efficiency with human creativity, judgment, and empathy. When done right, “AI-first” doesn’t mean less human. It means more empowered, more strategic, and more impactful.