M.A.I. Consulting
Service 03 of five

Team AI Training

“How should AI be used in my role?”

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01 Readiness Assessment02 AI Use Policy03 Team Training04 Fluency Support05 Agents, Skills & ToolsAll five services
The situation

Staff have completed general AI courses and still ask what is appropriate in their own role.

A licence was bought, or a session was run, and the material did not match the documents on anyone's desk. Completion is low and nothing in the work has visibly changed.

Among UK charities, 76% now use AI tools, up from 61% a year earlier, while the barriers small charities name most are limited digital skills (48%) and lack of training (44%) source. The constraint is not access to tools. It is knowing which tasks to give them and how to check what comes back.

What you hold at the end

A working playbook for each department, and a change in what the team does next week.

See a complete sample playbook for a fundraising team →

Capability levels

Seven levels, and the training days between them.

We scope training by where a team starts and where it needs to reach. The days below are delivery days for the programme itself, before department labs. Levels 1 and 2 are starting points, not destinations: reaching level 3 is the shortest engagement we take, whether the group begins at 1 or at 2.

Level
What the person can do
Days to reach
What we plan against
1
Has not used an assistant for workLevel 1Level 1. No working use of an assistant. Staff here often hold the strongest reservations, which is useful: the objections are specific and can be answered with their own documents.Nothing to unlearn. The first day is the one that changes the most.
starting point
Where people begin, not something we train to.
2
Asks for a summary, a search or a first draftLevel 2Level 2. Occasional use with no shared method. The output is unpredictable because the input is, and nobody can say which prompts worked. This is where most organisations actually sit.Uses it occasionally, without a method. Results vary by person and by day.
starting point
Where people begin, not something we train to.
3
Writes a full brief: role, audience, constraints, format, sourcesLevel 3Level 3. Structured prompting and verification. The person specifies the work as they would for a colleague, gives the source rather than a description of it, and checks figures, facts, language and defensibility before anything leaves the team. This is the floor we train to.our floorGrounds the request in the real document, iterates on the prompt, applies the four checks before sending.
3 days
Time saved on the tasks in scope: 20 to 35%
4
Sets up projects, custom instructions and skillsLevel 4Level 4. Persistent set-ups. Projects hold the reference documents; custom instructions hold the standing rules; skills hold the house method. The quality of a task stops depending on who asked.Stops re-briefing. The context, house style and rules are loaded once and reused by whoever runs the task.
5 days
Time saved on the tasks in scope: 30 to 45%
5
Delegates multi-step work to agents and runs workstreams in parallelLevel 5Level 5. Delegated work. An agent carries a job from brief to draft while the person supervises rather than types. Parallel workstreams become possible, which is where the working day changes shape.Hands over a whole job rather than a single step, and works on several at once.
6.5 days
Time saved on the tasks in scope: 40 to 55%
6
Builds agents and skills for colleagues, and reviews their outputLevel 6Level 6. Building for others. This is the level that makes capability survive turnover, because the method stops living in one head. It is the right target for champions and team leads, not for everyone.Becomes the person the department relies on: designs the set-ups, connects the sources, checks the work.
8 days
Time saved on the tasks in scope: 45 to 60%
7
Runs agentic work from the terminal, without writing codeLevel 7Level 7. Terminal-based agentic work with no coding background. Claude Code operates on folders of files rather than one conversation: renaming and restructuring hundreds of documents, running the same review across a year of reports, producing a repeatable pipeline. Worth it for a small number of people in an organisation, and transformative for those few.Batch work across many files, repeatable pipelines, tasks no chat window can hold.
10 days
Time saved on the tasks in scope: task-dependent
What the percentages are, and are not. They are planning assumptions, not promises, and they apply to the tasks in scope rather than to a whole job. We set them from published field experiments: 40% less time on professional writing tasks at higher rated quality Science, 2023, 14% more output across 5,179 support agents and 34% for the least experienced NBER, 2023, and 25% faster on realistic knowledge work HBS, 2023. Every engagement times its own tasks before the first lab and again at ninety days, and that number replaces this one.
Why the gains are not linear. Level 3 is where most of the risk disappears, because verification enters the work. Level 4 is where the time starts compounding, because nothing is briefed twice. Level 5 changes what a person can hold at once. Levels 6 and 7 pay off through other people and through volume, so they are worth buying for a few staff rather than for everyone. The same study that measured a 25% speed gain found AI users 19 points worse on a task chosen to sit outside the tool’s competence HBS, 2023, which is why every level above 2 is taught with its own refusal cases.

Levels are set per group, not per organisation. A fundraising team at level 2 and a leadership team at level 4 are trained separately and priced separately. Price a level in the estimator →

Examples

The general module, and what a department lab covers.

The general module sets the shared rules. Each lab applies them to one department's real tasks and documents.

General module · all staff

Seven parts, one sitting

  • The rules in practice. What your policy permits, with which data, on which tools.
  • Delegation. Which tasks to hand over, which to keep, and the red lines for beneficiary and donor data.
  • Description. Three prompt patterns: role, audience, constraint and format; give the source document; let the tool interview you first.
  • Discernment. The four checks before an output is used: figures, facts, language, defensibility.
  • Diligence. What to log, what to disclose, who owns the result.
  • Practice. Two exercises on tasks every department shares, on your approved tools.
  • Close. The shared playbook and where questions go afterwards.
Department lab

Programmes and monitoring

Tasks: donor narrative reports from field notes and the previous report; indicator wording for a logframe; synthesis of survey free-text.
Red line: no beneficiary names, case details or locations below district level in any tool.

Department lab

Fundraising and partnerships

Tasks: first drafts against a funder's template; eligibility checklists from a call for proposals; donor research summaries.
Red line: no figure accepted without recomputation against the budget file.

Department lab

Finance and administration

Tasks: budget narratives from the spreadsheet; procurement comparison tables; procedure drafts.
Red line: no bank, payroll or supplier identifiers in any prompt.

Department lab

Human resources

Tasks: job descriptions and interview question banks; staff-facing policy explanations; onboarding material.
Red line: no candidate or employee personal data, and no screening decision delegated to a tool.

Department lab

Communications and advocacy

Tasks: press releases and social copy in the house voice; translation drafts for review; briefing notes from long reports.
Red line: nothing published without a named owner and a source check.

Department lab

Leadership and governance

Tasks: board paper summaries; decision memos with options; scenario notes.
Red line: strategic and personnel decisions are not delegated, and AI use in board papers is disclosed.

Legal, protection and safeguarding, IT and procurement are scoped the same way: a short task inventory with the team lead, then a lab on those tasks.

How we get there

A task inventory, a lab, and a page written with the team.

  1. Task inventory. A short interview with each team lead: what the department spends its week on, and which of it repeats.
  2. General session for all staff on the shared rules and the four competencies.
  3. A 90-minute lab per department on that team's real tasks and real documents, run by the person who scoped the engagement.
  4. The playbook is written in the lab, with the team, then cleared against your policy.

Everything follows the four competencies of the AI Fluency framework published by Anthropic with Rick Dakan and Joseph Feller source. The framework is public, so the method can be checked against it.

Typical duration: Three to ten delivery days, spread across two to six weeks, plus a lab for each department.

Price

Fixed price and fixed scope, agreed in writing.

Priced on the level you are training to, the size of the organisation and of the departments involved, and how many departments need their own lab and playbook. Individuals and organisation representatives are priced per person for courses of fewer than ten participants.

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Thirty minutes establishes whether this is the right service.

If a different one fits better, or none does yet, we will say so on the call.

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