1 - Most companies think buying the technology is the hard part. It isn't. Success is roughly 10% the technology (AI) itself, 20% your tech and data, and 70% your people and how you work. Almost everyone gets that backwards and pours all their effort into the 10%.
2 - Data is the lifeblood of AI, and most companies skip it. AI doesn't fix a messy organization, it speeds it up. If your information is scattered and no one trusts it, no model will save you. Clean it up first, or you just make the mess faster.
3 - AI can now do real multi-step work on its own (the "agentic" shift everyone's talking about), and that exposed a new problem. The technology is no longer what holds you back, your old processes are. Drop a capable agent into a slow, bureaucratic workflow and it gets stuck in the same traffic everyone else does.
4 - You can't figure out what AI is useful for by sitting in a meeting. You have to try it, fail a bit, and learn by doing. The people getting ahead aren't the ones with the perfect plan. They're the ones running lots of small, cheap, slightly embarrassing experiments.
5 - Nobody fully knows what this technology is best at yet, not even the people who built it. That's the opportunity. Whoever figures out how to use it in their own field first gets a real head start, because there's no manual to wait for.
6 - A new kind of valuable person is emerging, and they don't have a job title yet. They're not the best at typing prompts. They're the ones who can take a fuzzy problem, define what a good result looks like, and direct AI the way a manager directs a small team.
7 - Technology never drives change on its own, people do. Nothing I ever built made a difference until someone inside the business decided to own it and push it forward