I was driving to a meeting last week when a warning light popped up on my truck’s dashboard. At the stoplight, I snapped a picture, uploaded it to ChatGPT, and learned it was just a seatbelt sensor issue. Nothing urgent (phew).
That same day, I used AI to help choose hotels for a team trip, debug some code over breakfast, and draft responses to a handful of emails that would’ve taken me an hour to craft carefully.
This is what AI adoption really looks like for most people. It’s not a massive digital transformation. It’s small, practical moments where you realize: this tool just saved me time and helped me make a better decision.
Large enterprises are pouring billions into AI pilots, according to an EY report, $49.2 billion was invested in Generative AI in the first half of 2025 alone. That’s more than all of 2024 and roughly double 2023. Yet, an MIT report found that only about 5% of AI pilots deliver rapid revenue growth.
Small businesses don’t have billions to spend, but they have a key advantage: speed. Without layers of bureaucracy or legacy systems, SMBs can experiment faster and adapt in real time.
Here’s the framework I recommend: three clear tiers that take you from dabbling with AI to making it part of your business infrastructure.
Tier 1: Just Use ChatGPT… A Lot
The best way to start is to simply start. Don’t overthink which tool to use. My advice: just use ChatGPT.
Yes, there’s Gemini, Claude, DeepSeek, and a dozen other options that all claim to be better at something. But constantly bouncing between models trying to find the “best” one is a distraction. OpenAI is the market leader; their models are good, and they keep getting better. Pick one tool and actually learn it.
Use it for everything. Draft emails. Summarize documents. Debug a problem you’re stuck on. Plan your week. Ask it questions you’d normally spend twenty minutes Googling. The more you use it, the better you’ll get at knowing when it’s useful and when it’s not.
Here’s the critical part: if you’re a business owner, you need to do two things right away.
First, give your team explicit permission to use AI. Most employees are already experimenting with it on their own, but they’re nervous about whether it’s allowed. That hesitation kills adoption. Make it clear: using AI isn’t cheating. It’s learning how to work smarter.
Second, and this is very important: Get a paid Teams account.
According to Verizon’s 2025 Data Breach Investigation Report, 72% of employees use personal accounts to access AI tools at work, creating major data security risks. Paid business subscriptions protect your data and send a message to your team that this technology is officially part of how your company operates.
The goal here isn’t perfection. It’s habit. Get your team using AI every day, safely and intentionally. Small productivity gains will stack up fast.
Tier 2: Train Custom AI Assistants (But First, Do the Hard Work)
Once your team is comfortable with basic AI usage, the next step is to build custom AI assistants for repetitive or specialized workflows. Tools like Custom GPTs (ChatGPT), Gems (Gemini), and Projects (Claude) make this surprisingly accessible.
But there’s a catch: AI doesn’t learn by osmosis the way humans do.
When you hire someone new, they can absorb a lot just by being around. They sit in meetings, ask questions, and pick up on your company’s tone and processes over time. You don’t necessarily need a perfect onboarding doc because humans figure things out.
AI doesn’t work that way. It needs clear, written data. That means documenting your FAQs, processes, brand guidelines, and sales playbooks.
It’s tedious but valuable. Most small businesses lack strong documentation, and this gives you a reason to finally create it. The clearer your information, the smarter your assistant becomes.
Start small. If customer support eats up time, create an AI assistant trained on your documentation. It can draft on-brand responses, summarize interactions, or guide employees through steps.
Salesforce research found that nearly half of business leaders believe AI will improve customer service interactions. But this process hasn’t been without setbacks, including high-profile examples of companies rolling back their initiatives and returning to more analog workflows. Klarna, for instance, recently reversed course on its customer service AI after realizing customers preferred speaking with humans.
Those missteps usually come from skipping the training phase. An untrained AI can sound robotic or get details wrong, which erodes trust quickly.
A well-trained assistant, on the other hand, can sound natural, accurate, and helpful, turning AI from a novelty into a genuine teammate that handles the repetitive work so humans can focus on the personal touch.
Tier 3: Embed AI Into Your Core Business Systems
This is where it gets real. Tier 3 is about integrating AI directly into your CRM, accounting software, HR systems. Whatever tools run your business day to day.
This is the most complex tier, but it’s also where the biggest impact happens. When AI is embedded into your core systems, it stops being a side experiment and becomes part of your infrastructure. It’s not something your team has to remember to use; it’s just built into their workflow.
Let me be clear: this requires real work. There are tools that can help, but ultimately you need systems integration: connecting AI to your actual business data. It’s not plug-and-play.
Here’s the difference. In Tier 2, if a customer asks, “Why did my bill go up?”, your Custom GPT can reference your documentation and explain common reasons bills increase: pricing changes, usage patterns, and seasonal factors. That’s useful.
But in Tier 3, when a customer asks, “Why did MY bill go up by $30?”, the AI connects to your customer database and support ticket history. It can see that this specific customer added two users last month, and here’s the exact breakdown. It’s not answering from general knowledge; it’s pulling their actual account data.
That level of integration takes hard work. You’re connecting AI to your CRM, your billing system, your support history. But when you get it right, AI doesn’t just assist; it automates entire workflows. Same goes for sales forecasting, HR onboarding, or internal reporting. AI can pull the specific data you already have, analyze it, and surface insights your team would otherwise miss.
This is how small businesses punch above their weight. You’re operating with the efficiency of a much larger company, but without the overhead. The right AI integrations don’t just save time; they let you compete with businesses that have ten times your headcount.
The Biggest Mistake Is Waiting
Here’s the thing about AI: it’s changing so fast that assumptions you made a month ago are probably already wrong.
Something that didn’t work in your business three months ago might work perfectly today. AI was terrible at handling images six months ago. Now it’s solid. Code generation was clunky a year ago. Now I’m writing production code with it over breakfast.
This is why the worst thing you can do is try something once, see it fail, and then write off AI for the next year. That mindset worked in the pre-AI world. If you tried implementing a new software category and it didn’t work, yeah, maybe revisit it in a few years. But with AI, a year happens in two weeks. You can’t afford to wait.
My advice: always err on the side of using AI too much rather than dismissing it too quickly. Stay curious. Keep experimenting. Pay attention to what’s changing, because it’s changing fast, and the tools that frustrated you last quarter might be exactly what you need today.
The small businesses that win in this environment won’t be the ones who waited for AI to “settle down” or for someone else to figure it out first. They’ll be the ones who started learning early, built the habits, created the documentation, and kept iterating.
Start with Tier 1. Just use the tools. Then move to Tier 2 when you’re ready. Document your processes, train some custom assistants, and see what happens. Tier 3 will come when the time is right.
But start. Because the path from zero to AI hero isn’t about having the biggest budget or the fanciest tech stack; it’s about starting now and learning as you go.
