Before committing AI investment
Identifies high-value opportunities grounded in how staff actually work, alongside the barriers that could limit their value. Gives investment discussions a practical evidence base.
— Operations & Process
AI Readiness Assessment
Assesses AI readiness through anonymous staff evidence, identifying where AI can improve day-to-day work and the practical barriers that could prevent those gains.
- Operations & Process
- Human review built in
- Traceable reasoning
- Runs anywhere
1–2 weeks → ~15 minutes
For one complete, review-ready pass
No coding required
- Input
- Anonymous staff responses to a consistent set of readiness questions
- Output
- AI readiness report
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~1–2 weeks per run
— USE CASES
What people use AI Readiness Assessment for
Testing leadership assumptions
Examines whether proposed AI priorities reflect staff experiences of lost time, tool limitations and data dependencies. Supports findings with anonymous quotations rather than attributed individual responses.
Understanding uneven organisational readiness
Assesses evidence across six readiness dimensions to reveal gaps that could hinder adoption. Gives advisers a clear account of current AI use, practical constraints and staff concerns.
Preparing a client readiness discussion
Produces a readiness report with findings subject to human approval. Gives the advisory team evidence-backed opportunities and blockers to discuss with the client.
What it works from
- Anonymous staff responses to a consistent set of readiness questions
- Concrete examples of working practices and lost time
- Staff accounts of data and tool dependencies
- Evidence of current AI use and staff concerns
What you get back
- AI readiness report
- Assessment across six readiness dimensions
- High-value AI opportunities
- Practical blockers to adoption and value delivery accepted by a human reviewer
— HOW IT BEHAVES
How AI Readiness Assessment produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Human sign-off before the write-up
The run pauses for a person to confirm the process steps that matter before the deliverable is composed.
Composed as work product
Findings on the end-to-end process are written up as a document that reads like professional output, with each claim tied back to a process step.
Criteria-based analysis of every process step
Each process step is assessed against explicit criteria you control, so the same standard is applied across the end-to-end process on every run.
Grounded in your own process documentation and operational data
The run works from process documentation and operational data you supply, so conclusions about the end-to-end process are anchored to your evidence rather than general model knowledge.
Why this is expensive by hand
AI investment decisions often rely on leadership assumptions rather than evidence from the people doing the work. Before committing AI investment is the typical trigger — identifies high-value opportunities grounded in how staff actually work, alongside the barriers that could limit their value. Gives investment discussions a practical evidence base. Get it right and the conclusion holds up in the room; get it rushed and it gets picked apart. Either way it costs roughly 1–2 weeks of experienced attention.
How this Skill produces it
Skillsize turns that work into a Skill: you supply the material, and what comes back is aI readiness report, with assessment across six readiness dimensions. The criteria, ordering and review points that make the answer trustworthy are encoded in the Skill itself — which is the difference between a structured method and a prompt someone pastes in. Net effect: 1–2 weeks down to ~15 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Who it's for
- Operations and continuous improvement leads
- Transformation and automation teams
- Service delivery and shared services managers
- Consultants running process diagnostics
Run it in Skillsize — or export it anywhere
AI Readiness Assessment exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
More Operations & Process Skills
Browse the full library →Operations & Process
Operating Model Mapper
Maps how an organisation actually operates using anonymous accounts from its people, producing an evidence-backed diagnostic of responsibilities, decisions, handoffs and duplicated effort.
Operations & Process
Project status digest
Reads a set of weekly status notes for progress, blockers and RAG, charts the trend, and writes an executive digest focused on trajectory.
Operations & Process
IT Change Advisory Engine
Reviews a proposed change against your change policy and returns a governed advisory decision — approve, approve with conditions, defer to the change board or reject — weighing risk, blast radius and rollback, with a change manager sign-off required before anything reaches production.