AI lacks the background.
Short, vague requests omit the audience, constraints and source material. The employee spends time correcting a generic response.
AXIOM ANALYTICS / HANDS-ON CORPORATE AI TRAINING
AI is available.
Make it useful.
Equip your employees to work confidently with AI.
Then teach them to connect it to the work they do.
AI Leap Forward builds practical capability through guided exercises, workplace examples and repeated practice. Learn to give AI the right context, examine its output and turn everyday tasks into reusable ways of working.
4.5–5 hours Foundation workshopHands-on Learn by doingOne-day advanced courses Department-specific learning
WHY THIS COURSE MATTERS
Access to AI is a start.
Using it well is a skill.
Employees may already ask AI questions. Many still struggle to get relevant answers, use company information effectively, verify results or carry a useful approach from one task to another.
Useful tasks remain manual.
Documents, spreadsheets and presentations are handled separately, even when they could share the same context.
Outputs need judgement.
Employees need a way to check claims, spot missing information and choose what data may be used safely.
AI LEAP FORWARD / FOUNDATION
Build a skill your team
can use the next day.
A guided workshop for corporate employees. The organising principle is context: every new technique shows another way to give AI the information it needs.
Understand the task
Choose a suitable AI use case, identify the desired outcome and recognise where human judgement is needed.
Give useful context
Explain the role, background, audience, constraints and examples. Practise improving a weak request.
Apply and verify
Work with actual task formats, review the result and refine it against a clear standard.
THE RCG FRAMEWORK
Role. Context. Goal.
A clear brief for AI.
RCG gives employees a repeatable structure for asking AI to help. It keeps the task, background and required output explicit.
Role
What perspective or expertise should AI use? Example: act as a sales operations analyst.
Context
What does it need to know? Supply the data, definitions, audience, constraints and a suitable example.
Goal
What should it deliver? Define the task, format, length and what a useful result must include.
COMPARE TWO BRIEFS
Analyse this sales data.
The request leaves the audience, definitions and expected output unclear.
Prepared example. This comparison does not call a live AI model.
BUILD CONTEXT IN DIFFERENT WAYS
Better input.
More relevant work.
Context does not have to be a long typed prompt. Participants practise several ways to provide background and reuse it.
Speak the brief
Use voice to explain the situation naturally. Add the details that typing often leaves out, then check the captured instructions.
Attach source material
Use approved documents, spreadsheets and reference examples. Ask AI to ground its work in those sources and identify what is missing.
Work within a project
Organise related files and instructions around a continuing task so follow-up requests can refer to shared context.
Show what good looks like
Provide an approved sample, template, tone or output structure. Explain which elements AI should preserve or adapt.
Refine through dialogue
Ask follow-up questions, correct assumptions and request clarification before committing to an output.
Create reusable instructions
Explore custom GPTs or reusable task instructions with approved reference knowledge and clearly defined boundaries.
PRACTICAL WORKPLACE APPLICATIONS
From a useful answer.
To a useful deliverable.
Excel and data analysis
Explore data, ask questions, prepare formula suggestions and charts, and review findings using AI and Copilot where available. Verify totals, definitions and calculations.
PowerPoint and communication
Turn approved material into a presentation outline or draft slides. Use Copilot where available, then refine the narrative, facts and brand presentation.
Simple webpages with Sites
Describe a page’s audience, purpose, content and visual direction. Create a simple page, inspect the result and practise requesting changes.
Documents and everyday writing
Draft emails, summaries, reports and structured notes using the relevant audience, source material and tone.
Custom GPTs and repeatable tasks
Explore how reusable instructions and reference files can support recurring work with consistent expectations.
Connected information
Demonstrate approved app connections where supported. Discuss source access, permissions and the context needed for useful analysis.
Exercises are selected around the group’s needs. Tool features, subscriptions and organisation settings are checked before the session.
INTRODUCING AUTOMATION
Repeat the useful work.
Connect the next step.
Give a task a rhythm.
Explore supported ChatGPT scheduled tasks for recurring briefings or reminders. Define the objective, timing and expected result.
Give each step a purpose.
Demonstrate a pipeline around ChatGPT or model APIs: approved input, analysis, reviewed output and a recorded action through supported connections or workflow tools.
Decide what may run.
Distinguish generating a summary from sending a message or changing a record. Set permissions and approval points for actions.
Illustrative demonstration
Read approved sample data, prepare an analytical summary and route it for review. Where the selected environment supports the required connections, demonstrate an authorised delivery step.
A scheduled task is not a universal file-processing or email pipeline. Connected workflows depend on the selected tools, supported actions and permissions.
HOW THE CLASSROOM WORKS
Practise. Compare.
Refine. Apply.
Short explanations
Introduce one concept, show a workplace example and move into practice.
Guided exercises
Participants create prompts, add context, inspect outputs and discuss what changed.
Role-relevant examples
Use tasks from the team’s work so employees can see where the method applies.
What employees leave able to do
Brief AI using RCG, build context from multiple sources, choose suitable workplace tasks, review outputs and identify opportunities for repeatable workflows.
What the organisation gains
A shared method for using AI, clearer expectations for output quality and a starting point for more consistent adoption across teams.
Measure progress through output quality, rework, completion time and repeated use on agreed tasks.
AI LEAP FORWARD / ADVANCED
Build on the foundation.
Apply AI within your function.
One-day courses for core teams of 8–10. Each stream uses a practical case study to teach transferable AI and workflow skills.
Sales
Learn through prospect research, qualification, reviewed outreach, reply handling and meeting coordination.
Explore the Sales streamMarketing
Use brand context to connect campaign planning, content preparation, approvals and performance review.
Explore the Marketing streamHR
Learn through candidate records, CV evidence, approvals and interviews; transfer the method across HR.
Explore the HR streamFinance
Learn secure document analysis, invoice review, receivables coordination and evidence-based reporting.
Explore the Finance streamThe examples support learning. The courses build team capability and classroom prototypes; production implementation is a separate step.
RESPONSIBLE USE IS PART OF THE SKILL
Use judgement.
Protect the context.
Learn to recognise when information is sensitive, when a result needs verification and when a person must make the decision.
- Use organisation-approved accounts and tools
- Share only authorised, necessary information
- Check facts and source references
- Verify spreadsheet calculations
- Review external communication before sending
- Keep consequential decisions with accountable people
Who is the foundation course for?
Corporate employees who want a practical approach to everyday AI use. It suits teams with mixed experience and does not require coding knowledge.
Do we need to know AI already?
The foundation workshop starts with the basics and builds through guided exercises. Advanced streams are best suited to participants comfortable with everyday AI tools.
Will every tool be covered in every session?
The core method is RCG and context building. Hands-on applications are selected for the group’s priorities, available tools and workshop time.
Can examples reflect our business?
Yes. Agree the team’s tasks and approved sample material before the workshop. Fictional data can be used where company information is sensitive.
What should participants bring?
A laptop, access to the agreed tools and one or two workplace tasks they want to improve. Required subscriptions, permissions and sample files are confirmed in advance.
AI LEAP FORWARD / AXIOM ANALYTICS
Help your team take
its next step with AI.
Start with the foundation workshop. Build towards department-specific workflows when your team is ready.