--- title: The AI Adoption Challenges Small Teams Hit in Month Two description: Why AI adoption challenges show up in month two, the signs of a stall, and how a named owner and a 15-minute weekly check-in keep your team using it. image: https://ai-marketinglabs.com/hubfs/The%20AI%20Adoption%20Challenges%20Small%20Teams%20Hit%20in%20Month%20Two.jpg --- [![AI Marketing Labs](https://ai-marketinglabs.com/hubfs/raw_assets/public/ai-labs/pages/assets/brand/logo-lockup.svg)](https://ai-marketinglabs.com/) - Systems [AIO System](https://ai-marketinglabs.com/ai-search-engine-optimization) [Voice Assistant](https://ai-marketinglabs.com/the-ai-assistant-for-business-that-runs-on-your-voice) [Buyer's Table](https://ai-marketinglabs.com/ai-market-research) [RAG System](https://ai-marketinglabs.com/ai-knowledge-management) [Custom AI Automations](https://ai-marketinglabs.com/ai-automation-services) - [Consulting](https://ai-marketinglabs.com/ai-consulting-services) - [About](https://ai-marketinglabs.com/about) - [Free tools](https://ai-marketinglabs.com/free-ai-marketing-resources) - [Blog](https://ai-marketinglabs.com/lab-experiments) [The Lab](https://ai-marketinglabs.com/the-lab) [Book your audit](https://ai-marketinglabs.com/ai-audit) [AIO System](https://ai-marketinglabs.com/ai-search-engine-optimization) [Voice Assistant](https://ai-marketinglabs.com/the-ai-assistant-for-business-that-runs-on-your-voice) [Buyer's Table](https://ai-marketinglabs.com/ai-market-research) [RAG System](https://ai-marketinglabs.com/ai-knowledge-management) [Custom AI Automations](https://ai-marketinglabs.com/ai-automation-services) [Consulting](https://ai-marketinglabs.com/ai-consulting-services) [About](https://ai-marketinglabs.com/about) [Free tools](https://ai-marketinglabs.com/free-ai-marketing-resources) [Blog](https://ai-marketinglabs.com/lab-experiments) [The Lab](https://ai-marketinglabs.com/the-lab) [Book your audit →](https://ai-marketinglabs.com/ai-audit) [The Lab Notes](https://ai-marketinglabs.com/lab-experiments) › # The AI Adoption Challenges Small Teams Hit in Month Two ![Kelly Kranz](https://ai-marketinglabs.com/hubfs/1c8a298050a84a029fa51a6945685d90.png) Kelly Kranz Nov 10, 2026 [Twitter](https://twitter.com/intent/tweet?url=https://ai-marketinglabs.com/lab-experiments/the-ai-adoption-challenges-small-teams-hit-in-month-two&text=The%20AI%20Adoption%20Challenges%20Small%20Teams%20Hit%20in%20Month%20Two) [LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https://ai-marketinglabs.com/lab-experiments/the-ai-adoption-challenges-small-teams-hit-in-month-two) ![The AI Adoption Challenges Small Teams Hit in Month Two](https://ai-marketinglabs.com/hubfs/The%20AI%20Adoption%20Challenges%20Small%20Teams%20Hit%20in%20Month%20Two.jpg) The AI adoption challenges that stall small teams tend to show up after launch, not before it. Somewhere in month two the tool fails on a real case, nobody is clearly responsible for fixing it, and people quietly go back to the old way. Plan for that month before you roll anything out: name one owner, hold a short weekly check-in, and keep a list of where the tool fell short so you fix the cause instead of losing the habit. **TL;DR** - Launch week is easy. The stall comes once the novelty is gone. - One named owner beats a shared sense of responsibility. - A failed case is information. Log it, fix it, tell the team. ## Why does AI adoption stall after launch? Because launch is the easy part. People try the tool in the first week, the demos work, and the kickoff goes well. Then real work arrives: the odd client request, the document in a format nobody tested, the week everyone is too busy to learn anything new. The tool gets one wrong answer on something that matters, and trust drops. The research points the same way. BCG's 2025 survey of over 10,600 workers across 11 countries found "only 51% of frontline employees are regular users," a figure it described as having "stagnated," and that "Just 25% of frontline workers say their leaders provide enough guidance on AI" ([BCG](https://www.bcg.com/press/26june2025-beyond-ai-adoption-full-potential)). That's a broad survey, not small teams in particular, but the shape is familiar: people try it, and without guidance the use levels off. ## What does a stall look like in month two? - Usage drops to the two people who were keen from the start. - Someone says "it doesn't really work for my stuff," and nobody asks what happened. - The prompt or instructions that worked in week one stop fitting, and nobody updates them. - Work gets done twice: once with AI, once the old way "to be safe." - The person who set it up is now busy with something else. Any one of these is normal. Three at once means the rollout needs attention, not more enthusiasm. ## Who should own it? One person, by name, with time set aside for it. Not "the team," and not whoever is most interested in AI. The owner's job is small but specific: collect what isn't working, fix or escalate it, and keep the instructions and examples current. In a team of five, that might be two hours a week for the first two months. If nobody has two hours, that's the real finding. The rollout was planned without anyone to run it. ## What happens in a weekly check-in? Fifteen minutes, same day each week, with whoever uses the tool. Three questions: 1. **Where did it save you time this week?** Specific tasks, so others can copy them. 2. **Where did it get something wrong?** Each one goes on the list. 3. **What did you stop using it for, and why?** This is the question that catches the quiet drop-off. The owner leaves with a short list of fixes and reports back on them next week. That loop is what catches the drift back to the old way before it settles in. ## What do you do when it fails on a real case? Treat the failure as a spec. Write down what went in, what came out, and what the right answer was. Then sort it: - **Missing information.** The tool didn't have the document, the price list or the context. Fix the inputs. - **Unclear instructions.** It did what it was told, and what it was told was vague. Rewrite and add an example. - **Wrong job for the tool.** Some tasks need judgment or data the tool can't reach. Take them off its list and say so. Then tell the team. "We fixed the thing that went wrong on Tuesday" is a better nudge than "please use the tool." ## Is it the tool, the task or the training? In our view, it's often the task. Company-wide training on its own is too general to change how people work. A more practical order is to choose one workflow, set the AI up for it, then train only the people it affects, since they now have a daily reason to use it. Starting with the people most eager to try it can help too, because early wins build the habit. Training still matters. In the same BCG survey, people who received five or more hours of training were significantly more likely to become regular users. The point is training on the work in front of them, which is what [AI business consulting that gets your team using it every day](https://ai-marketinglabs.com/lab-experiments/ai-business-consulting-that-gets-your-team-using-it-every-day) covers in more depth. ## When is outside help worth it? When month two arrives and nobody on the team can say why it stalled. Or when the owner has been named but doesn't know enough about the tool to fix what's on the list. An experienced person can look at the failed cases, tell you which are fixable, and work through them with your team so the skills stay after they leave. If you're starting without technical staff at all, here's [an AI implementation plan for a business with no IT team](https://ai-marketinglabs.com/lab-experiments/an-ai-implementation-strategy-for-a-business-with-no-it-team). AI Marketing Labs offers [AI Consulting Services](https://ai-marketinglabs.com/ai-consulting-services) for this: one-on-one work with Rick Kranz on the rollout that's stalled, with scope and fee agreed before anything starts. ## Related articles - [AI Business Consulting That Gets Your Team Using It Every Day](https://ai-marketinglabs.com/lab-experiments/ai-business-consulting-that-gets-your-team-using-it-every-day) - [An AI Implementation Strategy for a Business With No IT Team](https://ai-marketinglabs.com/lab-experiments/an-ai-implementation-strategy-for-a-business-with-no-it-team) - [How to Measure AI ROI Once the Tool Is Running](https://ai-marketinglabs.com/lab-experiments/how-to-measure-ai-roi-once-the-tool-is-running) ## Frequently asked questions How long does AI adoption take in a small team? Plan on two months of active attention, with an owner and a weekly check-in, before you judge whether it worked. Should I make AI use mandatory? Requiring it everywhere can lead to work done twice, once to comply and once to be safe. Require it for the specific tasks it's set up for, and keep checking that it actually helps there. What if only one person on the team uses AI? Find out what they use it for and whether it would work for the others. One keen user is a good owner candidate, if they have the time.   Rollout stalled? Get it moving again, *with Rick* AI Consulting Services is one-on-one work with Rick Kranz on the project that's stalled, including working with your team on their real tasks. Scope and fee are agreed first. [Tell us where it stalled](https://ai-marketinglabs.com/ai-consulting-services) ![Kelly Kranz](https://ai-marketinglabs.com/hubfs/1c8a298050a84a029fa51a6945685d90.png) Written by Kelly Kranz With over 15 years of marketing experience, Kelly is an AI Marketing Strategist and Fractional CMO focused on results. She is renowned for building data-driven marketing systems that simplify workloads and drive growth. Her award-winning expertise in marketing automation once generated $2.1 million in additional revenue for a client in under a year. Kelly writes to help businesses work smarter and build for a sustainable future. [![AI Marketing Labs](https://ai-marketinglabs.com/hubfs/raw_assets/public/ai-labs/pages/assets/brand/logo-lockup-white.svg)](https://ai-marketinglabs.com/) We build AI systems for manufacturers, agencies, educators, and field service businesses. Fixed price. Fixed timeline. You own it when we're done. 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