AI training and adoption
We run hands-on sessions built around the work your people actually do. Then we stay for the part most training skips: helping what works spread safely across the organization.
Most AI training fails in a predictable way. People leave a session interested, try a few things on their own, and a month later use has either stalled or scattered into habits nobody can see. Joust pairs training with the structure that makes it stick: a small group of trained champions, a shared set of approved tools and prompts, clear rules about data, and a regular look at what people are really using.
Training gives individuals new skills. It rarely changes how an organization works. A few enthusiasts adopt the tools in isolation, others never start, and some paste information into tools they shouldn't. Nobody collects what worked, so every team solves the same problems separately.
The organizations getting real value treat training as the start of a rollout, not the whole thing. They run small experiments on real tasks, gather feedback, and scale the practices that hold up.
If people don't adopt it, the impact is zero. Adoption is the part of any technology rollout that gets the least planning.
Ron Davis, founder of Joust
For executives and decision makers: what AI does well, where it fails, where the risk sits, and what to fund first.
Hands-on sessions using the tools you already license, whether that's the assistant built into your productivity suite or a standalone tool from one of the frontier labs. Every exercise uses tasks people handle each week.
A small group from each team or site gets deeper training and regular office hours, and becomes the first place colleagues go with questions.
Approved prompts, custom assistants built on the tools you already use, and short how-to guides, kept in one place and updated as tools change.
Acceptable use, data handling, what never goes into a prompt, and how to review AI output before anyone relies on it.
A short survey before and after, periodic check-ins on usage, and estimates of time saved, so you can see what is worth scaling.
A short staff survey and a few conversations to find where time goes and which tasks are good candidates.
A leadership briefing, then role-based sessions, in person or virtual.
Champions test new approaches on real work for several weeks, with office hours and a channel for questions.
What works goes into the shared toolkit and the next round of sessions. What doesn't gets dropped.
You can start with a single briefing or workshop. The program grows only if the results justify it.
Schools, districts, and public agencies face the same adoption problem with stricter rules about student and resident data. We work inside the platforms you have already approved, and keep sensitive records out of general-purpose tools.
Sessions are designed around the realities of the job: a principal between meetings, a teacher with one prep period, an office with a small IT team. Training can run organization-wide, by site, or by department, and it can support the professional development schedule you already have.
Sessions are led by Ron Davis, who spent thirty years moving from junior developer to CTO. He has trained Air Force and Marine Corps teams on AI tools and briefed Pentagon leaders on AI adoption. The people who design your program also deliver it.
Yours. We build sessions around the platforms your organization already licenses and has approved.
Yes. We deliver in person across the San Francisco Bay Area and virtually anywhere.
Workshops typically run 60 to 90 minutes. Leadership briefings run about an hour.
We set clear rules for what can go into which tool, align practices with your existing data agreements and policies, and keep sensitive records in approved systems only.
No. Many organizations start with one briefing or one workshop and decide what comes next based on what they see.
Tell us who needs training and what you want to change. We'll suggest a sensible place to start.
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