Training & Education

Generic AI training wastes your team's time with consumer tool tutorials and abstract concepts that don't translate to institutional realities. Our AI Fundamentals & AI in Practice curriculum curates the best available content and contextualizes it specifically with rural use cases and scenarios. It is hands-on, practical and applied AI learning.

Wayfinders is a different kind of AI education program: instead of adults writing lessons that go stale before they reach a classroom, students write them. Each year, a cohort of high school fellows researches, builds, and teaches an AI literacy curriculum to the next group of students coming up behind them. Those students then become next year's builders and teachers.

The model works because teaching is one of the most effective ways to learn something deeply. When students have to explain a concept to their peers, they have to understand it first, and decades of education research bears this out. The tools and norms around AI change too fast for a textbook written once a year by someone outside the classroom to keep up, so here the people closest to the technology decide what's worth teaching, sequence it, and deliver it — with a standing team of education, technical, and ethics advisers guiding them.

The core ideas — what AI is, how to think critically about its output, the ethics of using it responsibly — stay stable from year to year, while the specific tools and workflows get rebuilt annually to track where the technology actually is. Every version is dated and credited to the students who wrote it.

Wayfinders started as a rural-focused program, but the model travels well beyond that context — a natural fit for any community that has historically had its curriculum written by people outside it, Indigenous communities in particular, where students authoring and owning their own material speaks directly to self-determination.

Rural workforce training programs often suffer from curricula built around outdated employer needs.

AI Wayfinders Workforce Edition puts workers in the architect's seat. We interview employers to identify the AI and role-specific skills with the highest near-term hiring impact, then co-design the training sequence with employee participants, ensuring every module maps to a real job requirement. The applied content is co-developed by the incumbent workers being trained and anchored in the specific tools, tasks, and secure production environments of participating employers.

A standing team of instructional, technical, and governance advisers builds the learning and validation model: competency areas and their progression; safety, security, governance, and data-handling standards; AI evaluation skills; mapping to industry-recognized credentials; and an employer-validation workflow that gates each module before publication.

A Concrete Example

Over a 12-week cycle, a software engineer learns to use AI coding tools safely within the employer's secure development environment and applies those skills to a real task, reviewed by a senior engineer and instructional designer. Once validated, the workflow becomes a reusable learning module for future cohorts. By the end of the cycle, the engineer has earned a credential, improved workplace performance, and contributed employer-validated training content.

Open-Source & Configurable

New instructional resources developed through Wayfinders will be made available under a Creative Commons Attribution (CC BY 4.0) license, enabling broad adaptation by other employers, training providers, and regional partnerships. An accompanying implementation guide will document the competency-identification process, curriculum-validation methodology, and employer-engagement framework to support high-quality replication.

The AI Ignition Program combines three integrated services that take institutions from strategic assessment to measurable pilots with sustained implementation capacity.

The Result: Pilot programs launched within 90 days that demonstrate enrollment gains, efficiency improvements, or cost reductions — and institutions equipped with the skills, network, and momentum to scale what works.