According to McKinsey’s latest State of AI research, roughly two-thirds of organizations say they’re experimenting with AI—testing pilots, running proofs of concept, or integrating small features into their products. But only a fraction have fully started scaling AI into their workflows, culture, and decision making. In other words, most companies are still exploring AI rather than operationalizing it broadly.
And that’s okay. Every major technology shift looks like this at first. Curiosity is where momentum begins. The real opportunity comes from taking the first step from exploring to doing.
Curiosity Is the First Step Toward Competence
Progress always begins with curiosity. But curiosity alone doesn’t create change.
Throughout every technological transition—from spreadsheets to smartphones—the breakthroughs came from people who were willing to try something new. They weren’t experts. They were explorers. They learned by making small things work a little better.
Today’s AI agents follow the same pattern.
You don’t need to be a data scientist or write code to start benefiting from AI. Increasingly, AI tools are accessible to non-technical users who want to automate a process, reduce friction, or bring a new idea to life. And the best way to understand AI is not to read about it. It’s to use it.
Start small. Build or use an agent that helps plan your week, summarize notes, or organize your ideas. Then iterate. Add more context, connect it to other tools, and let it handle a bit more work.
Once you’re comfortable, apply the same approach to your job. Choose one repetitive report, one simple workflow, or one common request and let an agent take the first draft. You’ll be surprised by how quickly capability grows when you learn through doing.
This is the progression we see again and again in Agent.ai workshops: curiosity about AI leads to tinkering with AI which leads to confidence with AI.
Why Small Businesses Struggle to Start
When we talk with small business owners, we hear a common refrain: They believe AI could help them, but they’re not sure where to begin.
And it’s not because they’re skeptical. It’s because they’re busy.
Small businesses operate with tight margins, lean teams, and limited time. When you’re wearing five hats throughout your day, adopting a new technology can feel like adding a sixth. Most small businesses don’t need a complex AI strategy or a months-long transformation plan—they need a clear, simple entry point. Tools that help immediately, not someday.
That’s why starting with small, practical use cases matters so much: a few minutes saved on client communication, a quicker first draft of a proposal, streamlined reporting, etc. These efficiencies are lifelines that return precious time and reduce daily friction. When a small team sees an agent handle work that normally steals an hour of their day, something shifts. AI stops feeling abstract and starts feeling like leverage. It moves from theoretical to practical.
Small Starts Lead to Scaled Success
Even in companies that achieve meaningful value from AI, progress often begins with targeted, practical use cases. Not massive transformations on day one. Success comes from learning, iterating, and redesigning workflows over time.
You don’t need a data lab to begin your AI journey. You just need a spark of curiosity and tools that help you turn that curiosity into action. Your curiosity is your competitive edge. The most important thing isn’t how fast you scale—it’s simply that you start.
