Strategy without training is just a prettier mess. Practical AI beats performative AI.
The data is striking. Most organizations your size aren't actually using AI well, and they know it.
of small businesses say they need more training to use AI
cite a lack of technical expertise as the main blocker
are fully integrating AI into how they actually run
The gap isn't capability or budget. It's that real training, the kind built for your people doing your work, is the thing nobody is structured to deliver to organizations your size.
That's the work I do. And I do it specifically for organizations like yours.
Adoption doesn't happen because you approved a tool.
The licenses got bought. A team meeting was held. A few people downloaded the app. And then, somewhere around month two, you started noticing the same patterns showing up across every small business and nonprofit I've worked with.
- Only 14% of small businesses are fully integrating AI into core operations. Most are using it. Almost none have built it into how the work actually gets done.
- One or two people on your team have run with it. Most haven't touched it in weeks. And nobody's quite sure what "good use" is supposed to look like for your specific situation.
- 73% of small businesses say they need more training to actually use AI. The training that exists is either too generic to apply, too expensive to scale, or built for an enterprise team you don't have.
- You're worried about the things you should be worried about. Privacy. Donor data. Bias. Quality. And you don't have a CIO to answer those questions for you.
- Meanwhile, the work that AI was supposed to make easier is still piling up. Grant applications. Donor updates. Customer responses. Reports. The drafting that takes the time you don't have.
The goal isn't to use AI everywhere. It's to use it where it actually helps.
The problem isn't resistance to AI. It's bad implementation.
Here's what I hear when I talk to leaders of organizations your size. Not in the public-facing AI conversations. In the quieter ones, where people are honest about what they actually think.
- "I keep meaning to figure out AI. I just don't have the bandwidth to learn it well enough to teach my team."
- "We've paid for tools nobody on staff is using. I don't want to pay for the next one until I know we'll actually use this one."
- "I'm worried about privacy and donor data, but I'm not sure what questions I'm even supposed to be asking."
- "Every AI training I've seen is either fluffy and useless or built for a Fortune 500 team. Neither one fits us."
- "I don't want to look like the organization that's behind on AI. I also don't want to do something stupid just to look current."
- "Honestly? I'd love someone who actually understood what it's like to run something my size to come help us do this right."
The goal isn't to use AI everywhere. It's to use it where it actually helps.
Real AI adoption isn't a tool rollout. It's a structural shift in how decisions get made and how the work gets done.
That kind of shift requires more than a framework. It requires business strategy that happens to include AI. So what I use isn't C.A.L.M. on its own. It's C.A.L.M. layered onto the same traditional business strategy frameworks your leadership team would recognize. The ones that have held up because they actually work.
Here's the test: if your AI plan can't be explained to your board or your most skeptical employee without a glossary, it's not a strategy yet. It's vocabulary.
This is the methodology I built. And it's the one I use.
Clarity
You leave with a list of three to five priorities. Not thirty.
We define what AI is responsible for in your organization, and what it isn't. Use cases tied to outcomes you already care about: capacity, efficiency, donor engagement, customer service.
Clarity first. AI second.
See in practiceFor a small business: picking the three places AI saves the most time. Often that's customer service responses, marketing drafts, and bookkeeping summaries.
For a nonprofit: identifying which mission-critical work AI should support first. Usually grant writing, donor updates, or volunteer coordination.
Alignment
Your team trusts the plan because the plan was built around them.
Workflows redesigned around the new capability, not bolted onto existing ones. Privacy and governance built in early, before something breaks.
The best AI plan is the one your people can actually follow.
See in practiceFor a small business: simple rules for when to use AI and when not to. Approved tools, clear handoffs, and a process for reviewing output before it goes to a customer.
For a nonprofit: governance that protects donor and client data. Human review built in for anything sent externally. Voice and values stay intact.
Leverage
Your people use AI consistently because they were trained to.
Role-based training, not generic webinars. People learn what AI does for their job, with the rules and review steps they need to use it well.
If AI isn't changing how people work, it's not working.
See in practiceFor a small business: your customer service rep gets training built around customer service. Your marketing person gets training built around marketing. Each is using AI on day one.
For a nonprofit: development staff trained on first-draft donor updates and grant summaries. Volunteer coordinators trained on onboarding workflows. No generic curriculum.
Manifest
Real outcomes. Measurable. Reportable. Defensible.
Time saved. Capacity gained. Better donor communication. Stronger customer service. The kind of results you can show your board, your funders, or your bank.
Strategy is only valuable when it changes what happens next.
See in practiceFor a small business: hours back in the week, faster customer response times, and reporting you can actually use. Numbers your bookkeeper or banker can read.
For a nonprofit: capacity gains you can show your board. Stronger grant narratives. Cleaner program reporting. Funder-ready evidence of efficient operations.
This is the difference between an AI tool subscription and an AI capability. Most organizations have the first. The second is what we build.
Implementation is where AI either pays off or fails.
Implementation is where AI either pays off or fails.
The best AI investment is human understanding.
Capacity. Speed. Better customer experience.
AI training that actually shortens onboarding, frees up your time for revenue work, and helps your team do their work better. Customer service that responds faster. Marketing copy that doesn't take three days to draft. Reporting your bookkeeper doesn't dread.
Mission capacity, with your voice intact.
AI that helps your development team draft donor updates and grant summaries faster, without compromising your voice or your donor data. Human review built in. Volunteer onboarding that scales. Program reporting that's clearer for funders and easier for staff.
For your team
A focused, hands-on session for your specific team and your specific work.
Walk away with prompts, workflows, and rules of thumb your people can use the next morning.
For your specific people
Training built for the actual jobs people do. Development staff. Customer service. Operations. Marketing.
Each person learns what AI does for their work, with the privacy and review rules baked in.
The full engagement
The most comprehensive option. We define your priorities, redesign the workflows, build governance, and train the people who'll actually run them.
You finish with a usable system, not a pretty PDF.
Continued support
For organizations that don't want this to stall after the initial build.
Quarterly strategic check-ins, ad-hoc decision support, and a strategy that holds up as tools and teams change.
Real adoption starts with training, not talk.
Dr. Elisa Janson Jones
That order matters. I learned how people actually learn before I learned how organizations actually run, and I learned both before I learned AI. So when I build a plan for your organization, three things show up by default: the plan lands with the people who have to execute it, it lasts because the strategy holds, and it leverages AI to do the work it's actually good at.
Most AI consultants got here from the technology side. I got here from inside the rooms where people actually learn new things. That difference shows up in everything I build.
in education and learning design
custom GPTs designed and deployed
national keynotes on AI implementation
member community
Music Teacher Guild
Built the full AI integration roadmap for the organization. Designed 12+ custom GPTs for member-facing and operational use. Integrated AI into the coursework and assessments inside their certification programs.
learning assets & an AI chatbot
Conn Selmer
Designed and built a custom AI product education chatbot, layered on top of the 3,300+ asset video learning ecosystem I built earlier. The kind of program that has to scale without breaking, and trust the answers it gives.
artist & partner portal architecture
Roland Corporation
Architected the artist and partner portal end to end, including the multi-persona segmentation strategy for that audience. The foundation layer that makes future AI integration actually viable, instead of bolted on.
Credentials
- EdD
- MBA
- Certified AI Consultant
- AAAI Member
- Author, Prompt & Circumstance
What people usually ask before booking.
The wrong AI plan wastes time, money, and trust. So let's address the questions you're already asking before you commit your team's time to anything.
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No. Small organizations are exactly who I built this for. The framework I use scales down to a five-person team or up to a 45,000-member community. What changes is the application, not the logic.
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Most of my engagements start with a focused workshop or a single role-based training, not a full transformation. We do the highest-value piece first, then decide together whether more is worth doing. Budget isn't usually the blocker. Choosing the right starting point is.
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Most organizations your size have messy or fragmented data. That's not a deal-breaker, but it does shape where AI fits. Part of the work is knowing which use cases work fine on imperfect data and which ones need cleanup first. We figure that out together.
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Most AI training out there is generic, fluffy, or built for enterprise teams. Mine is built for organizations your size, taught by someone who actually understands your operational reality, and tied to the strategic frameworks your leadership already knows. Different work, different deliverable.
Let's get this out of the conference room and into your week.
A 30-minute working call. No deck. No pitch.
We'll talk about where your organization actually is right now, what's already been tried, and whether the kind of work I do is the right fit for you.
If it is, we'll talk about what an engagement could look like and what it would cost. If it isn't, you'll leave with a clearer view of what you actually need.
I'd rather have one honest conversation than ten polite ones. The 30 minutes is for the honest one.