Last week I facilitated a board meeting where two outside experts were invited to brief the directors on artificial intelligence. They came armed with examples, predictions, and noted: this is the worst AI will ever be. A year from now, what feels advanced today will look ordinary. That comment stuck with me.
After the meeting I thought about the organizations I work with. These are not global giants with endless resources. Most are mid-sized companies, often with a few hundred employees, that have to weigh every decision carefully. And yet even in this group, the patterns are clear. Leaders are moving forward with AI, and they are doing it in practical ways that other executives should pay close attention to.
Where to Focus
Many people look to AI to shave time or reduce headcount. That’s not wrong, but the companies getting ahead are asking a better question: how can AI help us win more business? They are testing it in sales support, proposal writing, lead qualification, and customer engagement. Efficiency matters, but revenue keeps the company healthy. Effective executives are keeping that distinction front and center.
The People Equation
There is real anxiety about job loss. What I am actually seeing is different. Companies are not rushing to layoffs. They are pausing backfills in positions that will almost certainly be automated, such as basic call-center roles. They are letting natural attrition create space. And they are retraining good people to work alongside the technology, shifting them into roles where judgment, creativity, and customer relationships matter more than repetition. Their message: AI is not taking your job. A person who knows how to use AI well is.
How Leaders Begin
Nobody is launching wholesale transformations. They are running small pilots. Spend a few thousand dollars. Test one process. Learn the vocabulary, make the mistakes, and build confidence in a controlled way. Pilots don’t just teach you about the tool, they teach your managers how to sponsor, measure, and communicate around AI projects. Those lessons will pay off when the stakes get higher.
Guardrails
Every client I work with is writing down some version of a short AI policy. Don’t use customer data in open tools. Check outputs for bias. Document which vendors are allowed access and how data is secured. These are not thick binders or complicated systems. They are clear, common-sense standards that reduce risk and signal to employees that leadership is paying attention.
If you were sitting with me in a client meeting, here’s the advice I would give you.
Start small but start now. Identify two or three projects where AI could improve revenue or reduce obvious friction. Assign clear ownership. Set a short time frame and capture what you learn. At the same time, look at your hiring plan. Where roles are likely to be automated, don’t backfill them automatically. Redirect that investment into training your current team on how to use these tools responsibly. And make sure you write down a one-page set of rules for how AI will and will not be used in your company.
AI is not a passing trend. It is becoming a core capability.
The companies that treat it as a side experiment will fall behind. The ones that build capability steadily, with their people at the center, are already creating advantages.
The leaders I respect most are not waiting for perfect conditions. They are learning in real time, alongside their teams, and adjusting as they go. That is what I would encourage you to do.
If strategy has ever felt confusing or theoretical, this guide will help.
It offers a practical way to think strategically, focus your efforts, avoid common missteps, and stress-test your ideas before they’re put into play.
