Aloha,

Before we dive into today’s topic, I have an invitation for my fellow founders 🙂 

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• Actionable frameworks, not theory: Their pricing strategy masterclass helped us a lot in how we should think about our business model.

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If you're building a SaaS product with $5K-$100K MRR, apply by May 18th to transform promising momentum into sustainable growth.

Now let’s dive into today’s topic!

The Human Element in AI-First Companies: Beyond the CEO Buzzwords

Last month, my LinkedIn feed exploded with reactions to three tech CEOs declaring their companies "AI-first." It wasn't just another buzzword on the corporate bingo card – these announcements marked the beginning of the most significant transformation of work since I started studying remote work a decade ago.

Unlike most tech CEOs who make vague gestures toward "innovating with AI," these leaders laid out concrete, radical shifts in how their companies will operate starting right now.

But what caught my attention wasn't just what they said – it was what they're actually doing as a result. And rather than relying solely on personal observations,

This dataset reveals exactly how the AI-first transformation is playing out in real organizations, providing empirical evidence for what works, what doesn't, and why most companies struggle to match the ambitions of their CEOs.

TL;DR: Five Key Insights based on AI Maturity Index

1. The Leadership Paradox: C-suite executives are 58% more likely to use AI daily than the middle managers responsible for implementation—creating a critical execution gap.

2. Quantified Productivity: Banking professionals save 24 hours weekly through AI tools—equivalent to reclaiming 3 full workdays—with other industries showing similar dramatic gains.

3. The Skills Constellation: Success with AI depends less on basic tool proficiency and more on five interconnected capabilities, with customization and collaboration being the largest differentiators.

4. Psychological Returns: Daily AI users report 7.5× more positive emotional impact than infrequent users, revealing that initial anxiety transforms into confidence with consistent usage.

5. The New Productivity Stack: AI is primarily enhancing creative and analytical tasks rather than automating routine work, with content creation and research emerging as the dominant use cases.

The Three Most Honest CEOs in Tech

Duolingo's Luis von Ahn didn't sugarcoat the coming changes. After his team used AI to create 148 language courses in a single year – a task that previously took 12 years – he announced contractors would be phased out for work AI can handle, and new headcount would only be approved if teams proved they couldn't automate more.

Shopify's Tobi Lütke went further, flipping the traditional tech adoption model on its head. Teams must now prove why they "cannot get what they want done using AI" before requesting more people or resources. He described seeing employees leverage AI to accomplish "implausible tasks" and "get 100X the work done." The company will now factor AI usage into performance reviews.

Most candid was Fiverr's Micha Kaufman, who told his 775 employees point-blank: "AI is coming for your jobs. Heck, it's coming for my job too." His memo warned that no role was safe – not programmers, designers, lawyers, or even CEOs. His survival advice was blunt: master AI tools in your field, find mentors who understand AI, and become a prompt engineer within months, not years.

These weren't empty threats. They were acknowledging the reality that McKinsey research has confirmed: AI can deliver 20-30% productivity gains across business functions. Nielsen Norman Group found even more dramatic results – a 66% productivity boost on average when using AI tools. That's equivalent to 47 years of natural productivity growth compressed into a single technological leap.

For the rest of the corporate world still debating whether to embrace AI, the math becomes brutally clear: your competitors using AI will rapidly outpace you.

1. The Quantified Productivity Revolution

When Shopify's CEO mentions employees accomplishing "100X the work," it sounds like hyperbole. But our AI Maturity Index data reveals the tangible impact across industries:

Banking professionals save 24 hours weekly through AI tools – nearly reclaiming three full workdays.

This isn't theoretical productivity – it's actual hours liberated from routine tasks, shifting the fundamental calculation of how much a single knowledge worker can accomplish. These numbers explain why AI-first companies aren't just more efficient – they're operating in an entirely different competitive reality.

2. What This Actually Means For Your Job

I've spent years helping companies transition to remote work, and I see striking parallels in this AI shift. Just as remote work wasn't simply "office work from home" but a complete reimagining of how teams collaborate, AI-first isn't just "current work plus AI" – it's a fundamental redefinition of human contribution.

Let me break down what's really happening beneath the corporate-speak:

The most successful remote-first companies didn't just move their office processes to Zoom. They reimagined workflow, communication, and decision-making. Similarly, AI-first companies aren't just plugging ChatGPT into current processes – they're rebuilding around what AI makes possible.

3. The Leadership Adoption Gap

While von Ahn, Lütke, and Kaufman are showcasing bold AI visions at the top, our AI Maturity Index data reveals a troubling pattern that explains why most companies struggle with implementation:

Founders and C-level executives are far more likely to use AI daily than the directors and senior managers responsible for implementation.

This creates a "strategic-tactical gap" that fundamentally undermines AI transformation efforts. The vision at the top is rarely matched by practical experience in the middle, where the actual work of implementation happens. When 75% of founders use AI daily compared to just 47% of senior managers, we're seeing more than a mere adoption lag—it's a fundamental misalignment in how the technology is understood and valued.

This gap isn't just a metric—it's the primary barrier to AI transformation. When those tasked with implementation lack firsthand experience with AI tools, they naturally focus on theoretical risks rather than witnessed possibilities. They become the organizational immune system, protecting against change rather than facilitating it.

4. The Skills Gap No One's Talking About

When I speak with knowledge workers about AI, they often focus on learning how to use specific tools like ChatGPT or Midjourney. That's useful, but it misses the deeper transformation happening.

AI Maturity Index identified the actual skills that determine who thrives in AI-first environments:

Daily AI users demonstrate dramatically higher capabilities across five key dimensions, with the largest gaps in customization and collaboration.

This data reveals something crucial: basic AI tool proficiency (the "Skill" dimension) is just the entry point. The real differentiators are the ability to customize AI outputs, apply creative direction, establish appropriate trust, and collaborate effectively between human and AI systems.

These patterns explain why some professionals thrive with AI while others struggle despite using the same tools. The most valuable people I work with don't just use one AI tool well – they orchestrate multiple systems within creative workflows.

Problem Definition: As AI handles execution, precisely defining the problem becomes crucial.

Taste and Judgment: AI can generate infinite options but can't tell you which is best. Your creative judgment, emotional intelligence, and ability to anticipate human reactions become your most valuable contribution.

Exception Spotting: The most costly AI failures happen when algorithms miss the unusual case. The people I see thriving are those who develop a sixth sense for when something seems off in AI-generated work.

None of these skills appear in typical job descriptions, and few training programs address them. They're developed through direct experience working alongside AI systems.

5. The Reality Check

Despite the CEO pronouncements and the clear skills needed, there's an enormous gap between AI ambition and reality in most companies. According to McKinsey's 2025 research, while 71% of organizations use AI in at least one function, only 1% consider themselves to have reached AI maturity.

This gap explains the disappointing financial results so far. IEEE Spectrum's analysis of McKinsey data shows most companies implementing AI have seen revenue increases below 5% and cost reductions under 10%. Goldman Sachs predicts the real productivity and GDP gains won't materialize until 2027 and continue through the 2030s.

Why such a gap? I've observed three consistent barriers in my consulting work:

1. The Middle Manager Freeze
Middle managers face the greatest disruption from AI – potentially seeing their teams shrink while being asked to deliver more. Without addressing their legitimate concerns about status, career paths, and skills relevance, they become resistance points rather than change agents.

2. The Training Mirage
Companies offer generic AI courses without creating safe spaces to apply new skills to real work. True AI proficiency develops through hands-on experience in low-stakes environments, not theoretical training.

3. The Trust Deficit
Even when AI tools work perfectly, widespread adoption requires trust. Employees need confidence in the systems' reliability, accuracy, and ethical foundations before they'll fully embrace them. This trust is earned through transparency and consistent results, not mandates.

6. The Psychological Returns Curve

Beyond productivity gains, our research uncovered a fascinating pattern in how people emotionally experience AI adoption:

The emotional impact of AI use increases dramatically with frequency, creating a "returns curve" where benefits accelerate with engagement.

This data validates what I've seen countless times: initial AI use often triggers anxiety, but pushing through this phase leads to dramatically more positive emotional outcomes as users build competence and witness tangible benefits.

7. The New AI Productivity Stack

So what does work actually look like in an AI-first environment? Our data reveals exactly what's changing in day-to-day practice:

🧠 Top AI Use Cases (Daily Users)

⚙️ Top AI Tools Powering Daily Workflows

This emerging "productivity stack" shows AI isn't primarily automating routine tasks but augmenting creative and analytical work. The most popular tools – ChatGPT, Claude, Perplexity, and Gemini – focus on extending human thinking rather than replacing it.

This explains why companies like Duolingo, Shopify, and Fiverr are seeing such dramatic results. They're not just making existing processes more efficient – they're fundamentally reimagining what's possible when humans focus on defining problems and evaluating solutions while AI handles the production process.

What This Means For You

If you're reading this, you're likely wondering what to do in response. Based on my work with companies navigating this transition and our research data, here's my practical advice:

For executives: Stop treating AI as a technology initiative and start viewing it as a business model transformation. The companies seeing real results aren't just implementing AI tools – they're reimagining their entire value creation process with AI at the center. Address the leadership adoption gap by creating incentives for middle managers to embrace this shift rather than resist it.

For managers: Your role is evolving from supervising execution to curating problems and evaluating solutions. Start shifting your focus from "how" to "what" and "why." The teams succeeding with AI dedicate more time to precisely defining problems and evaluating outputs, less time to production itself.

For individual contributors: Your technical skills will become less valuable than your ability to collaborate with AI systems. Start documenting the tasks in your workflow that feel repetitive or procedural – these will be automated first. Then identify where your uniquely human judgment adds value – that's your future focus area.

Beyond the Buzzwords

The headlines focus on AI replacing jobs, but the reality I see is more nuanced. The future isn't simply fewer humans – it's humans engaged in fundamentally different kinds of work.

The organizations and individuals who thrive will be those who don't just adapt to AI but actively reshape themselves to capitalize on its possibilities. They recognize that productivity in this new paradigm isn't about doing the same work faster; it's about doing entirely different work that wasn't previously possible.

When Duolingo creates 148 language courses in a year instead of 12 years, that's not just efficiency – it's a transformation of what's achievable. When employees use AI to "get 100X the work done," they're not just moving faster – they're operating at a different scale entirely.

For the past decade, I've helped organizations navigate the remote work revolution. That transition taught me that the greatest challenges weren't technological but human – helping people reimagine their work rather than simply relocating it. The AI revolution requires the same fundamental shift in mindset, just at a much larger scale.

The companies making the boldest AI-first declarations today may be ahead of the curve, but every organization will eventually face this transition. The difference will be in timing and approach.

For all of us navigating this shift, the path forward requires both courage to embrace change and wisdom to preserve what makes us uniquely human. The goal isn't AI for its own sake but using AI to unlock human potential in new ways.

The future isn't artificial intelligence replacing human intelligence. It's synthetic intelligence – the powerful combination of human creativity, judgment, and empathy with machine speed, precision, and scalability. That's the true promise of AI-first – not just more efficient companies, but more empowered humans.

If you enjoyed this edition - please do share it with your networks 👇️ 

Until the next time,

Iwo