Department-Level AI Adoption Programme

Why Individual Training Is Not Enough

Sending individual staff to AI training does not produce department-wide adoption. The skills do not transfer reliably to colleagues, the workflows that would benefit from AI remain unchanged, governance questions go unanswered, and the trained individuals revert to previous habits when they return to an environment that has not changed around them.

Department-level adoption requires a structured programme that addresses skills, workflows, culture, and governance simultaneously — with management involvement, peer champions, and metrics that track whether adoption is actually happening.

Programme Structure

Phase 1: Discovery and Scoping. We meet with department leadership and a cross-section of staff to understand current workflows, identify the highest-value AI use cases for this specific department, and assess the current state of AI awareness and capability. This produces a programme plan with defined cohorts, a delivery schedule, and measurable outcomes.

Phase 2: Leadership and Champion Preparation. Before broader rollout, we work with managers and a small group of volunteer AI champions within the department. Champions receive deeper training and become the first point of contact for colleagues with questions during rollout. Managers understand what to expect and how to support adoption in their teams.

Phase 3: Role-Based Training Delivery. Structured training delivered in cohorts grouped by role type — not a single generic session for the entire department. Policy staff, administrative staff, communications staff, and technical staff each receive content relevant to their actual tasks. All training uses the AI tools the department has deployed, with examples from the department's own work.

Phase 4: Workflow Integration. The training transfer gap — the failure of skills learned in a classroom to take hold in actual work — is addressed through guided workflow integration. We work with teams to redesign specific recurring tasks to incorporate AI, produce prompt libraries for common use cases, and establish review processes for AI-assisted work.

Phase 5: Governance and Ongoing Practice. We help the department establish the internal governance it needs for ongoing AI use: acceptable use guidelines, escalation procedures for uncertain AI output, a process for identifying new AI use cases, and a rhythm for refreshing staff skills as tools evolve.

The Government Context

Federal departments adopting AI tools must do so within the framework established by the Treasury Board Secretariat — including the Directive on Automated Decision-Making, the Directive on Service and Digital, and the emerging requirements of Canada's voluntary Code of Practice for Generative AI. We incorporate these requirements into programme design so that adoption is compliant from the outset rather than requiring remediation later.

For departments subject to Official Languages Act obligations, we ensure that AI tools are used appropriately in bilingual service contexts and that staff understand the verification requirements for AI-assisted content in both official languages.

The Healthcare Context

Healthcare organisations adopting AI tools must navigate privacy legislation, professional regulatory standards, and clinical governance requirements. Our healthcare adoption programmes address the specific obligations on regulated health professionals using AI in clinical or administrative settings, including documentation requirements and the distinction between AI-assisted decision support and AI-generated clinical advice.

The Education Sector Context

Post-secondary institutions and school boards adopting AI tools face particular complexity: different policies apply to student-facing versus staff-facing use, academic integrity frameworks must be updated, and instructors require support in both using AI themselves and teaching students to use it appropriately. We design programmes that address this complexity rather than ignoring it.