The 97% Unprepared Problem: Why Feeling Behind on AI Is the New Normal

Brian Rozelle

Digital Transformation and AI Strategy Consultant

Founder, Rozelle.ai

Published October 14, 2026

The TD Bank Number That Stopped Me Cold#

A few days ago, TD Bank released a survey that made the rounds in every small business group chat I’m in. They asked 200 U.S. small business owners one question about preparedness, and the answer was sobering.

Ninety-seven percent feel unprepared in at least one key area for the rest of 2026.

Not half. Not even three-quarters. Nearly everyone.

The biggest gaps? Technology and operations (43%), AI adoption specifically (40%), inventory management (37%), and cash flow planning (37%). This is a small sample, 200 owners, so treat it as a sentiment snapshot rather than a census. But the pattern is hard to ignore.

Here’s what really caught my attention, though. In that same survey, 99% of owners reported using AI in some capacity. Seventy-seven percent said their AI use had increased in the last six months. So almost everyone is using AI. Almost everyone also feels behind on it.

That gap is the whole story.

What “Unprepared” Actually Means for Small Business Owners#

I think a lot of us hear “unprepared for AI” and picture something dramatic. Like we need a data team, a six-figure budget, and a consultant with a whiteboard.

The reality is more ordinary, and more fixable.

TD Bank’s “technology and operations” category is the top concern. That tells me owners aren’t struggling to find AI tools. They’re struggling to integrate them. They’ve got a chatbot in one tab, a writing assistant in another, maybe something drafting emails. But none of it connects to how the business actually runs. Tools are scattered. Workflows are untouched. The AI is doing side quests while the real work happens the old way.

This isn’t a failure of awareness or access. It’s a structural gap between “using AI” and “being ready for AI.”

The Readiness-Reality Gap: Why Almost Everyone Feels Behind#

The TD survey isn’t the only data point saying this. Biztrategy found that only 13% of SMBs consider themselves “AI-ready” despite 77% using AI in some form. McKinsey’s research shows 88% of companies use AI somewhere, but only 6% are getting real value from it. And Gartner reports that 57% of AI failures come from expecting too much, too fast.

The pattern is consistent across every source I checked. Adoption is easy. Integration is hard.

If you’re a small business owner who feels behind on AI, here’s the truth that matters. You are not behind. You are normal. Feeling unprepared isn’t a personal failure. It’s the new baseline. And that means the competitive advantage isn’t being “ready.” It’s being slightly less unprepared than you were last month, consistently.

Think of it this way. Your competitors are already spending $20-$30 per month on tools that save them hours every week. The question isn’t whether to start. It’s whether to start with a plan, or figure it out the hard way.

Readiness Isn’t a Destination, It’s a Process#

Randy Wattilete, who writes about AI adoption for small teams, uses a crawl-walk-run framework that I find genuinely useful. Most AI frameworks are built for 500-person companies with data teams. This one is built for businesses like yours.

Crawl (Weeks 1-4): Pick one workflow. One tool. Run it alongside your current process. Don’t replace anything yet. Success gate: the AI output is good enough to edit, not rewrite from scratch.

Walk (Weeks 5-12): Add two or three workflows. Bring in a teammate. Write some lightweight guidelines. Success gate: at least two people use AI weekly without anyone reminding them.

Run (Month 4 and beyond): Now you redesign the workflow around AI. The human job shifts from doing to directing. Success gate: your team can’t imagine going back.

The point is that readiness builds. You don’t wake up ready. You build it.

The 5 Pillars of SMB AI Readiness#

Biztrategy proposes five pillars for AI readiness, adapted here for a non-technical audience. Rate yourself 1 to 5 on each.

Strategy clarity: Can you name three specific processes where AI could save time or money?
Data foundations: Are your key records digital and structured? Can you pull last quarter’s report in under 10 minutes?
Process documentation: Are core workflows written down? If someone left, could another person follow their process?
Team readiness: Is your team comfortable experimenting? Do you have one person who could champion adoption?
Budget allocation: Can you set aside 5-10 hours per week for someone to lead this? Tools are cheap. Time is the real cost.

Total your score. Below 10 means do foundational work first. Ten to 18 means build on your base. Above 18 means you’re in better shape than most, and it’s time to adopt strategically.

Most small businesses I talk to land between 8 and 14. That’s exactly where you want to be to start.

What to Do This Week: A 5-Step Starter Plan#

Here is a plan you can actually finish this week without buying anything or hiring anyone.

Step 1: Name your one weakest area (5 minutes). Pick the single gap from TD’s list that would hurt most in the next 90 days. Technology, AI adoption, inventory, or cash flow. Don’t try to fix everything.

Step 2: Audit one repetitive workflow (30 minutes). Pick the task you do 5+ times weekly that follows a pattern. Write down what triggers it, what steps it takes, how long it takes, and where it goes wrong.

Step 3: Test one AI tool for that workflow (this week). Run one tool alongside your current process. Don’t replace anything. Think of it as a new hire’s first month. Check the work before you trust it.

Step 4: Set a human gate before anything goes live. Define what AI may do, what it may never do, and who approves before anything reaches a customer or moves money.

Step 5: Track one number (start immediately). Pick a metric that proves the workflow is improving: time per task, response time, error rate, or output volume. Hours saved only matter if you redeploy that time.

The Real Competitive Advantage#

Here’s what I keep coming back to. The businesses that pull ahead won’t be the ones that buy the most AI tools. They’ll be the ones that pick one boring workflow, establish a baseline, add AI to draft or retrieve, put a human gate before liability, and track the KPI. Then they do it again.

Jason Wade, who writes practical guides for SMBs, puts it well: “AI use is common. AI operating discipline is rare.” The workflow-first rule is simple. Before selecting any tool, answer what workflow you’re improving, who owns it, what AI will do, where a human approves, and what number should move. If you can’t name the owner and the KPI, you’re experimenting. Not implementing.

And that’s fine. Experimenting is where everyone starts. The difference is whether you stay there.

If you’ve been feeling behind on AI, I hope this is the permission you didn’t know you needed. The gap between where you are and where you think you should be is smaller than it looks. Close it one workflow at a time.

“Ready to put these ideas into action?” Browse our collection of AI implementation tools, templates, and guides at Rozelle.ai ↗ — built specifically for operators who want results, not theory.