AI Champions

Prepare people who can introduce AI into your organisation’s work. Over 12 weeks, participants learn the tools, build agents, select initiatives, assess business impact and change processes with colleagues.

Work on a real process with people from your own team.

Price on request · excl. VAT and applicable taxes

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An AI champion understands the technology and knows how to lead change.

Help colleagues use AI, find business opportunities and organise implementation. Choose a ready-made tool, build an agent or propose a process redesign. Make the case to a manager, agree the approach with the team and assess results using business metrics.

Who it is for

Managers andspecialists

Product and project managers, business analysts, L&D, legal, finance, HR strategists, PMO leads, internal consultants. No programming skills are needed; the technical modules start with the basics and move into hands-on prototyping.

What you need first

3things a participant needs
  • Domain expertise — a deep understanding of how your department works.
  • Influence in the team — colleagues and your manager listen to you.
  • Willingness to lead change — to build for others, not only for yourself, and bring them along.

Two parts: AI technology and implementation in your organisation.

How the programme runs

  • FormatOnline workshops and independent practice
  • ContentAI technology and implementation
  • Length12 weeks
  • Group sizeUp to 15 people
  • Support3–9 months, depending on the package

How the stages fit together

  1. 01

    Overview

    The champion’s role and AI in personal work, the team and the organisation.

  2. 02

    Technical foundation

    Models, agents, skills, company knowledge, servers and quality evaluation. Learn to understand the technology and choose solutions for different tasks.

  3. 03

    The path of an initiative

    Process research, initiative selection, hypothesis testing, economics and change management.

  4. 04

    Strategy and next steps

    Priorities, responsibilities and shared working rules, followed by support under the selected package.

The principle

Practise on your organisation’s tasks.

For example, contract approval is delaying sales. Investigate the work of sales, legal and finance, find the constraint and propose a new approval process with AI. Build a prototype, test the hypothesis, assess its effect on the deal cycle and prepare the team for change.

The learning project covers the implementation cycle. Apply those skills to later initiatives, help colleagues and continue developing solutions within your organisation.

What you leave with

Navigate AI technology confidently

Choose models and tools for the task. Build agents, skills and Knowledge Bases, connect external systems and check quality.

Investigate a business process

Use interviews and data to trace a process from start to finish. Find its constraint and assess how AI would affect the whole chain.

Select initiatives

Gather ideas with colleagues and assess value and feasibility. Build a portfolio covering employee support, process redesign, and new products or services.

Make the business case

Connect changes to revenue, cost, quality and throughput. Include AI, evaluation and support costs, and explain the initiative to a manager.

Introduce AI with the people who use it

Involve colleagues, address concerns and teach new practices. Agree roles, organise support and improve solutions through feedback.

The programme, phase by phase

Entry

Preparation and process selection

Independent work before the startAssess readiness, choose a process and gather work examples.

Choose a process from your own work. Gather task and outcome examples, discuss participation with the process owner and manager, and read the introductory materials.

OutputA chosen process, initial data and agreements with the team.

AI technology: understand, choose and apply

Models, tools and AI capabilities

Four hoursUnderstand the technology and choose an approach for the task.

Explore model capabilities and limitations, context windows and causes of errors. Compare ready-made tools, assistants and agent systems. Select solutions by quality, cost and data-handling conditions.

OutputAn evidence-based choice of model and tool, with their limitations understood.

How agents work: an n8n example

Four hoursModel, system prompt, memory, knowledge, tools and interface.

Build an agent in n8n to see how the parts fit together. Connect APIs and MCP, examine context transfer and conversation storage. Compare a fixed workflow, an agent and orchestration of several agents.

OutputAn understanding of agent architecture and how to locate the cause of a failure.

Claude and Codex: skills, subagents and vibe coding

Four hoursConfigure agents for recurring work and building your own tools.

Work with project instructions, skills, connectors and subagents. Transfer context between tasks and divide work among agents. Create documents, spreadsheets and small applications, then check and improve the results.

OutputAn organised way of working with agents and a useful task procedure saved as a skill.

Company knowledge and Context Engineering

Four hoursTurn documents and company experience into knowledge an agent can use.

Design a Knowledge Base with entities, relationships, facts, rules and examples. Explore how to load and update materials, use retrieval-augmented generation (RAG) and trace answers to sources. Handle contradictions, access restrictions and processing costs.

OutputKnowledge prepared for an agent and the ability to check which sources support its answer.

An agent on a server: access for the team

Four hoursUnderstand what an AI solution needs beyond a personal laptop.

Move an agent to a server, connect a model through an API or proxy and configure a Telegram or web interface. Work through access, keys, logs and maintenance. Identify decisions to agree with IT and who will support the solution.

OutputAn understanding of a deployed solution and its operating requirements.

Agent setup, evaluation and quality control

Four hoursAssess reliability and learn to improve agent performance.

Build an agent harness: the context, skills, tools and checks that support the agent’s work. Set autonomy boundaries, keep a Decision Log and prepare reference examples and evaluation tests. Investigate errors and verify that rule or model changes have not degraded the result.

OutputA way to assess agent quality, control changes and organise further development.

Implementation: processes, economics and people

Workshop 1: discovery — where AI belongs in the process

Four hoursFind business opportunities and gather ideas with colleagues.

Conduct interviews and examine the process from start to finish. Find constraints and record initiatives with a business metric, data and owner. Compare value and feasibility, and check whether improving one stage would overload the next.

OutputA process map and a list of tasks to investigate.

Workshop 2: the pilot plan

Four hoursChoose one initiative from the shortlist and design the pilot.

Define participants, data, timing and metrics. Agree in advance which results would justify continuing the work.

OutputA pilot plan and a way to compare AI output with expert decisions.

Workshop 3: agent architecture

Four hoursDefine how the agent will work in the selected process.

Check data availability and describe sources, tools and human participation. Prepare examples for quality evaluation.

OutputAn agent architecture and a set of evaluation examples.

Business module: economics and business metrics

Four hoursConnect AI use to business results and justify the investment.

Calculate model, infrastructure, checking and support costs. Assess effects on revenue, quality and throughput. Consider how to use freed time and distinguish measured effects from hypotheses.

OutputAn estimate of costs and expected value, with assumptions explained.

Business module: change management

Four hoursHelp people adopt AI and establish new ways of working.

Address colleagues’ concerns, management support and team incentives. Plan training, change roles and working rules, and appoint a process owner. Organise feedback, support and the spread of useful solutions.

OutputAn implementation plan, roles and agreements with the team.

Strategy and discussion

Discussion: strategy and portfolio

Four hoursConnect individual initiatives to a company plan.

Explore Deploy, Reshape and Invent: tools within functions, redesign of whole processes and new business models. Assemble a portfolio, allocate resources and ownership, and agree shared working rules and a way to revisit priorities.

OutputPriorities and concrete actions for the next month.

After the programme · Support by package

Support for champions introducing AI at work.

Review results, difficulties and next steps in follow-up meetings. The duration and frequency of support depend on the package.

  • Monthly meetings on implementation, business results and team difficulties.
  • Quarterly reviews of company readiness and the improvements needed next.
  • Peer learning and joint review of difficult tasks.
  • Updates to materials and settings based on use in practice.

The basic package covers up to 12 participants and three months of support. The extended package covers up to 15 and six months of support. The strategic package includes nine months of support and a second training cohort.

AI Champions in practice

Training tied to real work, with a path from prototypes to production.

15 champions trained

Haleon

Fifteen people from marketing, finance, R&D and operations worked on AI projects drawn from their own jobs. The programme included hands-on development and support after training; the first agents went into production.

Read more about the Haleon engagement on the case studies page.

How to join

The main format is a programme built around your company. If you have only a few people to train, ask us about a future open group.

In-house

Participants work on processes from their own functions, with modules adapted to your industry.

Talk through a programme

Request

Plan an AI Champions programme for your company.

If you need the programme shaped around your function and context, tell us what the problem is. We can discuss the cohort, the support they need and possible dates on a call.

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Let’s
work together

Tell us what your team needs to learn, build or change. We’ll help you choose a training programme or plan implementation.

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See the work

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Read the cases
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