Customized AI training programs for faculty, staff, and leadership — built on the public ailearning.global curriculum and adapted to your institution's discipline mix, tool stack, policy context, and schedule.
Most off-the-shelf AI training treats teachers as deficient and AI as inevitable. We do neither. Our programs assume your faculty are professionals with judgment worth respecting, and that AI is a tool whose value depends entirely on how thoughtfully it gets used in your specific context.
Structured intake with your sponsor, sample interviews with faculty across experience levels, and a review of your existing AI policy, tool licenses, and IT constraints. We learn your institution before we propose a curriculum.
We adapt the ailearning.global curriculum to your discipline mix, your actual tool stack (Workspace vs. M365, Canvas vs. Brightspace vs. Moodle, the AI tools you've actually licensed), and your policy context. A music conservatory and a business school receive genuinely different programs.
In-person workshops, virtual cohorts, or async self-paced modules on the Smoother Experiences platform — or any blend. Sessions are scheduled around your reality: in-service days, semester cohorts, summer institutes, or distributed across an academic year.
Every participant receives an exercise workbook, a curated subset of our prompt library matched to their roles and disciplines, and reference materials they can actually use after the session ends.
Optional cohort for your internal champions — instructional designers, department chairs, or designated faculty leads — who will continue the work in our absence. Includes facilitator guides and rehearsal sessions.
Scheduled check-ins after delivery (typically at 30 and 90 days), a private cohort space for ongoing questions, and a final readout to leadership on what's working and what isn't.
Honest about scope. Things you might assume are included but aren't:
Sponsor intake, faculty interviews across experience levels, tool and policy review, and a written summary of what we heard before we propose anything. You see our reading of your institution before you commit to scope.
We propose a customized curriculum, schedule, and delivery format with explicit assumptions and trade-offs. You can revise, reject, or rescope before we lock anything in.
First cohort runs as a deliberate pilot — typically a department, a grade band, or a leadership team. We collect feedback systematically and adjust before scaling.
We deliver to the full population using the refined curriculum. Train-the-trainer cohort runs in parallel or immediately after, so your internal champions are equipped before we step back.
30-day and 90-day check-ins with participants, a final readout to leadership, and a written handoff document so the work survives staff changes on your side and ours.
A small liberal arts institution asked for a single in-service day on AI for all faculty. After the needs assessment, we proposed splitting the work: a half-day for skeptics focused on critical evaluation and a separate half-day for early adopters focused on classroom integration, plus a leadership session on policy questions. The pilot department ran first and reshaped the broader rollout based on what the faculty actually asked about, rather than what we'd assumed they would.
That's the norm, not the exception. We address it two ways: the needs assessment surfaces the range honestly, and the curriculum splits sessions or tracks so beginners aren't lost and experienced users aren't bored. Mixing levels in one room without a structure for it is how training engagements fail.
Yes, and we usually recommend it. Leadership sessions cover governance, policy trade-offs, and decision-making questions that aren't useful or appropriate in a faculty workshop. Mixing the two audiences also makes faculty less candid about what they're actually struggling with.
No. We don't accept referral fees, affiliate commissions, or reseller margins from any AI tool vendor. Our tool recommendations reflect what fits your context. If that ever changes, we'll disclose it before the engagement starts — but it hasn't, and we don't intend it to.
Yes. We build async modules on the Smoother Experiences platform when schedule constraints or distributed faculty make live delivery impractical. Async works well for foundational content; the higher-leverage discussions (policy, ethics, discipline-specific judgment calls) still benefit from live time, even if it's a short virtual cohort.
Two things. First, scheduled 30-day and 90-day check-ins are part of the engagement, not an upsell. Second, if you opted into the train-the-trainer track, your internal champions carry the work forward with materials they can keep using. We're not trying to be permanently embedded — the goal is for your institution to outgrow needing us.
Engagements are scoped by audience size, number of cohorts, and delivery format rather than a flat per-seat rate. A single department pilot is meaningfully smaller than a multi-campus rollout, and we price accordingly. Most engagements land between a focused pilot and a full-institution program spanning an academic year; we'll quote specifically after the needs assessment.
The research is clear: one-off workshops don't change practice. Our programs include follow-up support and community of practice to ensure lasting impact.
Training must address the 'why' before the 'how.' Understanding the ethical dimensions of AI makes educators better decision-makers about technology use.
Our training is the opposite of death by PowerPoint. Participants spend 70% of their time doing, not listening. That's how adults learn best.
Training is transformation, not information transfer. Every program we design follows the same principle: engage, enable, inspire, empower, and connect — never just lecture.
Comprehensive AI training designed for educators, by educators. From awareness to mastery.