A recent study by American Management Association revealed that 58% of professionals feel "behind" in their AI adoption journey. While most folks know me as "the Beyond the Prompt guy," here's what you might not know: I struggle with this stuff too.

Last week, I proposed a simple but fundamental shift: we need to stop thinking about AI as a technology rollout and start treating it like a new teammate. What I didn't fully explain is that this isn't just a semantic distinction. It produces measurably better results.

I’ve been seriously thinking about AI for over two years now, and I’m finally hitting my stride when it comes to my point of view. The fundamental shift I believe everyone must make is from thinking of AI as a technology, to thinking of AI as a teammate.

Still waiting on other people before you tap AI? Big mistake. This post exposes the silent tax of “AI inaction,” hands you the five‑rung ladder for turning any model into your on‑call mentor, and launches a seven‑day sprint that will hard‑wire the habit—so you can seize the advantage while everyone else is still scheduling meetings.

Last week, Shopify CEO Tobi Lütke released an internal memo that's been making waves. My take: this isn't just another tech CEO jumping on the AI bandwagon. It's the clearest articulation I've seen of a principle I've been exploring the past 18 months: the greatest risk with AI isn't failure—it's inaction.

I'm best known for my work on innovation, creativity, and entrepreneurship. My “shift” toward AI might seem like a radical departure. But it's not a shift—it's an evolution. Having taught and spoken to tens of thousands from ~100 countries in the last two years, I’m more convinced than ever that AI isn't separate from innovation; it's the most profound innovation platform of our lifetime.

AI isn't coming for your job. But someone using AI almost certainly is. So why not take your own job before someone else does? It’s time to prioritize and systematize disrupting ourselves.

When organizations think about AI transformation, they immediately focus on technical roles: data scientists, developers, prompt engineers. But what if the most important AI role in your organization requires zero technical expertise?

Behold the great AI measurement delusion: Organizations tracking usage metrics are missing the only thing that matters—impact.

More use isn't better use. Better use is better use.

Last week a CEO asked me the same question I hear from every executive: 'How do I get my team to use AI?'

My answer shocked him.

In the AI age, love is more important than ever. Because now anyone can generate “good enough” solutions with a few prompts. But people want more than good enough. When average is free, only above-average passion will stand out.

"I don't really have any pain points to automate," a CEO told me during an AI workshop last week. "I don't do repetitive work like other people in the company do."

Then he mentioned how he spends six hours manually editing every report his team sends him… I had to stop him right there.

There’s only one right answer to the question, “Did AI help with this?” The shift to an AI-first mindset isn't just about saving time. It's about recognizing a fundamental truth: AI isn't a tool you might want to use. It's an amplifier you'd be reckless not to use.

Learning to work with AI isn’t really a technical challenge. It’s a human behavior change effort. AI skill building is about far more than learning new tools. It’s about unlearning old ways of working.

AI is transforming industries. Designers are compressing month-long workflows into minutes. Scientists are using AI to condense years of research into days. But what about decades into minutes? Meet Adam. He doesn’t have a LinkedIn account. But in 45 minutes, he built an AI tool that'll save his organization thousands of days of work every year.

Right now, in boardrooms and Slack channels across the globe, leaders are inadvertently creating a culture of AI shame. They're reinforcing the very hesitation they should be helping their teams overcome. It's time for an intervention.

The quality of our thinking is deeply influenced by the diversity of the inputs we collect. Implementing practices like Brian Grazer’s “Curiosity Conversations” ensures innovators are well-equipped with a variety of high-quality raw material for problem-solving.

The first question an innovator must answer is not “can I make it?” but rather, “should I?” This has become something of a mantra among CEOs I work with, as a needful protection against the gravitational pull of the organizational bureaucracy.

One of the defining contributions the d.school is helping teams ask themselves, “What kind of thinking is appropriate, when?” We call such clarity being “Mindful of Process.” And it can seem like semantics until you realize we need to show up in different ways.

You’re probably getting fat on AI content: bingeing podcasts, hoarding newsletter tips, saving Twitter threads... While it feels productive, all that consumption is just giving you a knowledge sugar high. And like any sugar high, it’ll crash—leaving you with exactly zero new capabilities.