I came across a survey last week that stopped me mid-scroll. A researcher named Luke Pierce surveyed 242 businesses about their AI implementation plans. Not a vendor-sponsored study. Not a press release from a platform trying to sell you something. Just raw data from real companies trying to figure this out.
The results confirmed what I’ve been seeing in every client conversation for the past six months. And they should change how you think about AI in your business.
The Number That Matters Most
More than half. Not “we don’t believe in AI.” Not “we can’t afford it.” They don’t know where to start. That’s a completely different problem, and it requires a completely different solution.
The education phase is over. Companies have read the articles, attended the webinars, seen the demos. They get it. AI matters. What they’re missing is someone who can walk into their business and actually build the thing.
The Data That Should Change Your Thinking
Three stats from this survey reshape the conversation entirely.
tried AI
results
the blocker
61% have already tried AI. These aren’t skeptics. They bought in. They opened a ChatGPT account, maybe ran some prompts, possibly even subscribed to a tool. The motivation is there. The execution isn’t.
25% tried it and got limited results. This is the most important segment in the entire survey. These companies already spent time and money on AI. They’re not asking “should we?” anymore. They’re asking “why didn’t it work?” That’s a very different conversation, and it’s one I have almost every week.
Only 4% said budget was a blocker. Read that again. In a survey of 242 businesses, almost nobody said money was the problem. This kills the assumption that companies need cheaper tools or lower-priced consultants. Price isn’t the objection. Clarity and trust are.
The Execution Gap
Here’s what the survey makes clear: the market doesn’t need more AI educators, more webinars, or more tool comparisons. It needs builders. People who can walk into a company, understand the operations, and construct an AI system that actually produces results.
I see this gap every time I start a new engagement. The client has a folder full of AI strategy decks. They’ve been to the conferences. They’ve done the “AI readiness assessment” with a Big 4 firm that charged them $50K for a PDF. What they don’t have is a system that runs.
That’s because most AI consulting is advisory. Someone tells you what to do and hands you a document. You’re left figuring out how to actually do it with your team, your tools, and your budget. The advice is usually right. The implementation never happens.
What Actually Moves the Needle
The survey revealed something else worth noting: 44% of respondents want efficiency, not revenue growth. They’re not looking for AI to make them more money (yet). They want it to save time, reduce manual work, and make their existing operations faster.
This is where I start with every client. Not “how do we use AI to grow revenue” but “what are you doing manually that AI could handle by next Tuesday?” Marketing is usually the answer. Reporting, content drafts, competitive monitoring, email triage. These are real hours that disappear the moment you build the right system.
That’s not theoretical. That’s what I built for my own business first, then adapted for clients. Daily morning briefings. Automated content drafts. A knowledge system that gets smarter with every interaction. All running on a $700 Mac Mini that works while I sleep.
When I show clients what their version of this looks like, the reaction is always the same: “Why didn’t anyone show me this before?” Because most consultants don’t build. They advise.
Where to Start (For Real)
If you’re in the 52% who don’t know where to start, here’s what I’d tell you over coffee.
Start with marketing. Not because marketing is the most important function (it might be, but that’s a different article). Because marketing has the clearest, fastest feedback loop. You build an automated content system, you see the output the next morning. You build an AI-powered reporting workflow, you save 5 hours that same week. The wins are immediate and visible, which makes it easier to justify expanding AI into other areas of the business.
If you’re in the 25% who tried AI and hit a wall, the issue probably isn’t the tool. It’s the context. AI without your brand knowledge, your audience data, and your business rules is just a sophisticated autocomplete. AI with that context built in becomes something that actually understands your business.
The Bottom Line
This survey confirmed something I’ve believed for a while: the companies that win with AI won’t be the ones with the best tools. They’ll be the ones who build systems that compound, with someone who can actually construct those systems inside their business.
The execution gap is real. 52% of businesses are stuck. 25% tried and stalled. Only 4% think it’s a money problem. The rest just need someone to build.
Data referenced from Luke Pierce’s AI Implementation Survey (March 2026), a study of 242 businesses exploring AI adoption.
