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.

Delivery Process

Step 1: Discovery and Programme Design (Weeks 1–3). We conduct structured conversations with department leadership and a cross-section of staff to understand the workflows, the AI tools being deployed, the current level of AI capability, and the specific concerns or resistance we should expect to address. We produce a programme plan with defined cohorts, a delivery schedule, success metrics, and a risk register for adoption challenges.

Step 2: Leadership and Champion Preparation (Weeks 3–4). Before any broader rollout, we run a targeted preparation programme for managers and the first cohort of volunteer AI champions. Managers complete a half-day session on leading AI adoption in their teams. Champions receive an accelerated version of the full programme and are prepared to support colleagues during rollout.

Step 3: Role-Based Training Delivery (Weeks 4–12). We deliver training in cohorts grouped by role type. Each cohort session runs 3–4 hours with hands-on practice integrated throughout. Between sessions, participants complete assignments applying what they have learned to their actual work. A programme manager from our team monitors completion rates and provides coaching to participants who are struggling.

Step 4: Workflow Integration and Governance Handoff (Weeks 10–16). As training delivery completes, we work with teams to embed AI into specific recurring workflows, produce the department's prompt library, and establish governance structures. The department leaves the programme with an operating manual covering acceptable use, escalation procedures, and the process for identifying new AI use cases.

Typical Engagement

Duration: 8–10 weeks for teams of up to 80 staff; 4–6 months for departments of 100–300 with multiple role types and workflow integration components.

What the client needs to provide: Department leadership committed to the programme and available for the Leadership Preparation phase; a volunteer cohort of 3–6 potential AI Champions; scheduled calendar time for training cohorts (3–4 hours per session, 2–4 sessions per cohort group); access to the AI tools being deployed.

What Remolda provides: Full programme design, all training facilitation, champion development, prompt library construction, workflow redesign support, governance documentation, and success metrics tracking at 30 days and 6 months post-programme.

Technology & Integrations

Department adoption programmes are built around the specific AI tools your organisation is deploying. We work with Microsoft 365 Copilot environments (including Copilot for Teams, Word, Outlook, and SharePoint integration), Google Workspace Gemini, Slack AI, Notion AI, and sector-specific platforms. For government departments, we train on GC-approved AI tools and GCdocs-integrated workflows. For healthcare organisations, we work with AI modules in EMR platforms including EPIC and Cerner where available, and administrative AI tools integrated with healthcare information systems. For post-secondary institutions, we work with AI tools integrated with LMS platforms. All training uses the real tools in the participant's actual work environment — never sandboxed demos.

Canadian Regulatory Context

Department-level AI adoption in Canadian regulated sectors must be compliant from the outset. For federal departments, the programme design incorporates the Directive on Automated Decision-Making, the Official Languages Act obligations for bilingual staff using AI in service delivery contexts, and the Policy on Government Security constraints on what may be entered into cloud-hosted AI systems. For healthcare organisations, the programme addresses the obligations of regulated health professionals using AI in clinical and administrative settings under PHIPA and equivalent provincial health information legislation, and the professional regulatory guidance applicable to specific professions including physicians, nurses, and allied health professionals. For post-secondary institutions, we address both the staff obligations under PIPEDA and institutional obligations around student data, incorporating applicable guidance from provincial privacy commissioners on the use of AI tools that process student information.

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Further reading: AI Transformation Fails Without Culture | AI Training for Corporate Teams