There is a moment in every industry when the ground shifts. Sometimes it happens slowly, giving leaders years to prepare. Other times it arrives overnight. Artificial intelligence feels like both. It is moving fast, transforming at a pace no one can fully grasp, yet it has been building quietly for years. For many business owners, the uncomfortable truth is beginning to surface. You either speed up now or risk being left behind. There is no safe middle ground.

I hear this fear all the time during coffee chats with clients. They tell me their teams are drowning in work, their competition is getting sharper, and they are starting to feel pressure they cannot quite name. The pressure is coming from AI. It is not a threat in the sense of replacing everything overnight, but it is a shift in what “normal productivity” means. Once a team uses AI properly, their output increases so dramatically that the gap created becomes impossible to close with human effort alone. Right now, that gap is still manageable. In a year or two, it might not be.

The reality is simple. Businesses that activate AI today will pull ahead. Those that delay will struggle to catch up. Some industries, like marketing, logistics, and customer service, are deep into the transformation already. Others, like construction, education, and health care, have more time. But the difficulty is knowing which group you belong to. Most leaders do not know. Even seasoned executives get it wrong.

That is because the transformation is not happening industry by industry. It is happening process by process. Any part of your business that involves information, communication, planning, or decision-making is already being reshaped by AI. If your competitor automates their admin, analysis, reporting, customer follow-up, or compliance processes, they can deliver better outcomes faster and at lower cost. You cannot close that gap by asking your team to work harder. Biology will not keep up with technology. It is as simple as that.

Every business owner I speak with tells me a similar story. They started dabbling with AI tools in small ways. A little help writing emails. A summary of a meeting. A bit of content creation. It felt helpful, but not life-changing. Then, when they learned how to structure the prompts properly, how to create a knowledge base, how to design workflows around AI, the shift in output was shocking. When a team goes from doing everything manually to having AI handle large parts of their day, their available time increases. Their creativity improves. Their stress drops. Their energy returns. They start making progress again, not by working more hours, but by working in a completely different way.

The challenge is that most businesses do not reach this stage on their own. They get stuck in what I call “AI dabbling mode.” They play with it during quiet periods, or when something feels too hard. They do not build systems. They do not create structure. They do not bring the team along with them. And while they are dabbling, other companies are building real capability. Those companies are the ones that will become the future market leaders, not because they have better people, but because they use their people differently.

The risk is not AI taking your job. The risk is your competitor using AI to make their staff ten times more effective. There is no defence against that except to meet the moment with equal energy.

People often ask me whether they should start small or go large. My answer is always the same. Start small internally, but with a large intention. Pick one department or one workflow. Automate something meaningful but manageable. Make sure the team understands the shift and feels part of it. Document your processes. Build your knowledge base. Test and improve your prompts. Get the feedback loop moving. Once you see the improvement, the next steps become obvious. You build confidence, and with that confidence comes momentum.

The reason this matters is because AI compounds. The earlier you begin, the more benefit you gain. The later you begin, the harder it is to catch up. In property, I often saw people who waited years to invest. They always ended up paying more for less. The same principle applies here. The cost of delay is invisible at first, but devastating over time.

One of the most sobering parts of this transformation is the widening skill gap. Many staff, even talented and hardworking ones, are finding it difficult to keep up. Some feel intimidated. Some are quietly resistant. Some cannot accept that the skills they relied on for decades are shifting under their feet. This is not their fault. The pace of change is simply too fast. It is not realistic to expect people to read every update, follow every model release, and evaluate every new tool. Even leaders struggle to stay abreast. I spend half my life testing tools, experimenting with prompts, and researching new workflows, and still the updates outpace me.

This is where businesses must make a choice. Do you wait for your team to naturally adopt AI at their own pace, or do you lead the change? Waiting feels comfortable, but it is the most dangerous option. If people fall too far behind now, it will become almost impossible for them to catch up later. They do not need to become experts. They only need a framework, guidance, and the right tools. They need a leader who shows them the path, not someone who waits for them to find it alone.

One of the biggest mistakes I see is when leaders leave their team out of the AI implementation entirely. They pick tools, build workflows, automate tasks, and then present the new system as a finished product. The team resists. They panic. They fear replacement. They lose trust. This makes adoption slower and costs more in the long run. A human-enabled AI system is always stronger. People are the heartbeat. The AI is the engine. Take away the people and the engine loses purpose. Take away the engine and the people cannot scale.

The businesses that get this right involve their teams early. They ask questions. They listen. They invite ideas. They create champions in each department. They explain the why behind the change. They celebrate small wins. This builds confidence and lowers fear. It also uncovers inefficiencies that leaders often never see. When people feel included, they become allies, not obstacles.

Another question I get is whether to choose a single platform or experiment with many. Again, the best approach is simple. Pick one core platform and build around it. If you are a Google Workspace company, start with Gemini. If you use Microsoft 365, start with Copilot. If your team uses ChatGPT already, stick with OpenAI. Do not jump between systems every week. That is the fastest way to burn productivity. Commit to a platform long enough to understand its strengths. Once you have structure, you can add additional tools carefully, not impulsively.

The mistake many people make is confusing novelty with innovation. Every week, a new model launches. Some are amazing. Some are messy first versions. Some will not exist next year. If you rebuild your AI systems every time something new appears, you will never stabilise. Productivity dies in constant rebuilding. Progress comes from consistency, not experimentation.

Of course, you still need someone who understands what to choose, when to integrate, and how to design the workflow. That is where partnerships matter. You do not need an in-house AI team. But you do need someone who knows how the pieces fit together, because most business owners cannot tell whether their industry will be disrupted in six months or six years. Some sectors like marketing and customer service are already transformed. Others like accounting, legal, and manufacturing are on the cusp. Some trades and manual roles will take longer. But do you know for sure which category you fit into? Most people do not. That is the risk. Misjudging the timeline could cost you years of progress.

This is why speed matters. Not reckless speed, but structured speed. You want to be early enough to build capability without pressure, but not so early that you waste time on unproven tools. You want to set your team up long before their current skills become outdated. You want to automate the parts of your business that slow everything else down. You want clarity, not chaos.

The good news is that once you start, things become clearer very quickly. AI implementation creates clarity because it forces you to examine your systems. You start seeing what matters and what does not. You begin to understand where your bottlenecks are. You see where your team shines and where they struggle. You learn what to automate and what to keep human. What once felt overwhelming becomes manageable, even exciting.

Over time, the question shifts from “Should we do this?” to “Why did we wait so long?”

If you want to understand your risk properly, you need to look at your industry, your competition, your internal processes, your team’s capability, your data hygiene, and your leadership priorities. All of these determine how urgently you need to act.

The critical point is coming quickly. For some businesses, it has already arrived. For others, the window is shorter than they realise. AI will not destroy your business. Delay will.

If you are unsure where to begin, or how to judge the risks in your sector, or how to prepare your team without overwhelming them, then this is exactly the kind of conversation we have at Anaboo. You do not have to make these decisions alone. You do not need to guess. A short discussion can save you months of uncertainty.

If you want to talk through your options, understand the landscape, and see how AI fits your business model, book a coffee conversation with us. We will help you understand your risk profile, your opportunities, and what to do next.

Because in the AI era, speed is not a luxury. It is survival.
And the best time to start is now.

Live with passion & AI,

Brett