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Every seismic shift in business history begins with denial. Railroads dismissed automobiles. Publishers shrugged at the internet. Film studios laughed at streaming. Each time, incumbents convinced themselves that “business as usual” would hold. Each time, they were wrong. And each time, value shifted to those who saw the change for what it was.

What’s the Difference Between Asking a Human to Complete a Task and Asking AI? On the surface, not much. You say “build me an app,” and both human and AI will deliver code. You say “write me some market copy,” and both will produce words on a page.

Some things are easier to deny than to fix. When intelligent systems work well, they create surplus capacity. And when that happens, the default corporate response is as predictable as it is destructive, cut costs. That's exactly where businesses break their own systems.

In the software world and particularly SaaS, features don’t differentiate, experience does. You can match every feature your competitors offer and still lose. Not because your product is worse, but because it feels harder to use, slower to deliver value, or just less thoughtful.

It always starts with clarity. A company is founded to solve a specific, painful problem. The early roadmap is crisp. Focused. Built on urgency and direct feedback from real users trying to get real things done. And then, success. Customers come in. Revenue grows. The roadmap expands.

Fraud used to be limited by human effort. You could spot the broken English in the phishing email. You could hear the hesitation in the voice. You could flag the dodgy PDF with the pixelated invoice. But now?

leadership in a complex business isn’t linear. It’s not even rational in the strictest sense. It’s a real-time collision of context, competing priorities, and partial information. Decisions don’t arrive in order, they come in waves. Many are interdependent.

AI improves productivity by automating repetitive tasks, freeing up time, and unlocking capacity. It’s true, on the surface. But that story is only half the plot, and if you stop there, you’ll miss where the real value is hiding.

AI isn’t magic. It’s a powerful set of tools that extend well-run processes and ruthlessly expose broken ones. Lead with strategy, pick the business lever that matters most, and deploy AI where it can create visible, measurable value.

A few years ago, executives worried that they’d missed the mobile-app boom. Then it was cloud migration FOMO. Now the scramble is for AI—and the potential applications are so vast that most leadership teams are paralyzed by choice.

There’s a popular saying in business: “Vision without execution is just hallucination.” While a bit tongue-in-cheek, it captures an important lesson. Regardless of how impressive or innovative your strategy might be, if your organization can’t implement it effectively, the strategy itself is doomed.

Growing a company is never a one-step process. Moving from $1 million to $5 million, $5 million to $10 million, and beyond $10 million, or even $20 million to $50 million, each requires new skills, new structures, and new ways of thinking.

When it comes to innovation, artificial intelligence (AI) is often heralded as the holy grail, a game-changer capable of transforming industries overnight. The excitement is understandable. AI has the potential to revolutionize how we work, solve problems, and deliver value. However, there’s a concerning trend emerging: businesses leading their innovation efforts with AI rather than using AI to enable innovation.

As the company grows, expanding product lines, acquiring more customers, integrating new technologies, and swelling with more employees, that once-heroic leadership style can quietly become a liability.

While some businesses are quick to adopt AI solutions, others may believe that if they're not actively using AI, they don't need to worry about it. However, even if you have no formal plans to integrate AI into your operations, having a generative AI policy is essential. Here's why.