The frameworks behind our work.

The people-and-organization layer of every rollout. ADKAR tracks individual readiness. Kotter sequences the organization. Bridges names the internal transition. Diffusion of Innovations explains why most rollouts stall at the chasm between Early Adopters and the Early Majority.

• ADKAR

  Five conditions every individual needs before a new tool sticks: Awareness, Desire, Knowledge, Ability, Reinforcement. (Prosci)

• Kotter's 8-Step Model

  Eight steps for moving an organization through change — from urgency through to anchoring change in culture. (Kotter Inc.)

• Bridges Transition Model

  The internal psychological journey through change — Ending, Neutral Zone, New Beginning. The "transition" underneath the "change."

• Diffusion of Innovations

  The adoption curve — Innovators, Early Adopters, Early Majority, Late Majority, Laggards.

Training that transfers to the job. ADDIE is the design backbone. Kirkpatrick measures whether anything changed. The Anthropic 4D model specifies what AI fluency means in competency terms. 70-20-10 and Bloom’s decide what mastery means for a given curriculum.

• ADDIE

  The five-phase backbone behind training that transfers to the job: Analyze, Design, Develop, Implement, Evaluate.

• Kirkpatrick's Four Levels

  Four levels for measuring whether training actually worked: Reaction, Learning, Behaviour, Results.

• Anthropic 4D AI Fluency Framework

  Four atomic competencies that survive any model upgrade: Delegation, Description, Discernment, Diligence. (Anthropic)

• Four Metaphors for Working with AI

  Four ways to frame AI in a workflow: Intern, Coworker, Teacher, Coach. (Nielsen / UX Tigers)

• 70-20-10 Model

  Adults learn 70% from experience, 20% from peers and coaches, 10% from formal training.

• Bloom's Taxonomy (Revised)

  Six levels of cognitive depth for specifying what mastery actually means in a curriculum.

Sense-making for the workflow-mapping work. Cynefin gives leadership a vocabulary for why some tasks belong to AI and some don’t. Jobs to Be Done surfaces the job the worker is actually hiring AI to do.

• Cynefin Framework

  A sense-making framework with four domains: Clear, Complicated, Complex, Chaotic — each calling for a different decision posture.

• Jobs to Be Done

  A framing question — what job is this worker hiring AI to do?

Lean and Six Sigma for ops-heavy organizations. DMAIC structures the improvement cycle. Value Stream Mapping reveals the workflow before tool selection — because most AI opportunities are workflow opportunities AI happens to enable.

• Lean Six Sigma DMAIC

  Five-phase process improvement: Define, Measure, Analyze, Improve, Control. AI accelerates Define and Measure.

• Value Stream Mapping

  The Lean technique for seeing the whole workflow before changing any of it.

US, Canadian, European, APAC, intergovernmental. They overlap deliberately. A client operating in the EU has different obligations than one operating in Singapore. We map engagements to the relevant framework set for the client’s jurisdiction.

• NIST AI Risk Management Framework

  The US-issued, internationally adopted reference for identifying and governing AI risk across the system lifecycle.

• ISO/IEC 42001

  The international management system standard for AI — the audit-ready structure for governed AI use.

• AIA — Algorithmic Impact Assessment (Canada)

  Canada's Algorithmic Impact Assessment (AIA) — a structured way to classify AI systems by potential impact.

• OSFI Guideline E-23 — Model Risk Management

  Canada's banking regulator guideline for model risk management — including ML and AI models.

• EU AI Act, Article 4 — AI Literacy

  In force since February 2025 — organizations operating in the EU must ensure sufficient AI literacy among their staff.

• US DOL AI Literacy Framework

  Five federally defined competency areas for AI-literate workers in the US (February 2026).

• Singapore Model AI Governance Framework

  The leading APAC AI governance framework — issued by Singapore's IMDA and PDPC.

• OECD AI Principles

  The first intergovernmental AI standard. The baseline behind most national and regional AI policy.

Three instruments built inside Far West. The Workflow-First Sequence is the operating methodology. The AI-Workflow-Fit Diagnostic classifies each task. The Bearing drafts the Phase 2 strategy from a discovery intake.

• The Workflow-First Sequence

  Map the workflow. Decide where AI fits and where it doesn't. Install the change. Tools last.

• AI-Workflow-Fit Diagnostic

  Task inventory and decision map — where AI absorbs the task, where AI supports it, where AI stays out.

• The Bearing

  A 60-question diagnostic engine that drafts the Phase 2 strategy from a discovery intake.