Your team has the AI tools. Now make them useful.
Most organisations have rolled out Copilot, ChatGPT, Claude or Gemini. Far fewer have changed how people actually work with them. This practical session closes that gap in half a day.
From occasional chatbot use to repeatable business workflows
Access is not adoption.
Buying licences is the easy part. Value appears when people know which mode to use, provide useful context, check the answer and turn good individual experiments into repeatable team workflows.
of organisations using generative AI say they have fundamentally redesigned at least one workflow.
People use expensive systems as occasional search boxes and drafting assistants.
Fast output creates confidence before sources, calculations and assumptions have been checked.
Useful ideas remain inside individual chats instead of becoming shared workflows.
Teams need clear boundaries for data, permissions, approvals and external actions.
People leave able to do the work.
This is a working session. Participants use their own tools, apply the methods to real tasks and build something they can continue using after the training.
Select the right mode and tool
Know when to use chat, reasoning, deep research, document creation, an agent or a scheduled workflow.
Check what matters
Test sources, assumptions, calculations, completeness and consistency before relying on an output.
Create repeatable capability
Turn one good result into a controlled workflow the wider team can use and improve.
Foundation first. Application immediately after.
The content is tailored to your organisation, sector, AI platform and data policy. The structure remains durable even as individual tools and product names change.
Working effectively with AI
- Choosing between chat, reasoning, research and agent modes
- Personal instructions, reusable context and project workspaces
- Prompt structure, task architecture and context management
- Research, evidence hierarchy and source checking
- Verification, evaluation and managing uncertainty
Workflows, agents and control
- Working with documents, spreadsheets, presentations and email
- Designing repeatable multi-step workflows
- Agents, automation and connected business systems
- Data classification, permissions and prompt injection
- Human approval, monitoring and workflow ownership
Test the simplest ROI assumption.
Time saved is capacity, not automatic cash. The value appears when that capacity is redirected into client work, better decisions, faster delivery or less rework.
Illustration assumes 46 working weeks, a 37.5-hour week, 25% employment on-costs, a five-hour session and a £2,000 training fee.
This is an operating-capacity illustration, not a promise of cash savings. It excludes additional value from faster sales work, improved quality and work that was previously impractical.
This is an operating-capacity illustration, not a promise of cash savings. Actual time savings may exceed three hours a week. It also excludes additional value from faster sales work, improved quality and work that was previously impractical.
“Guy initially undertook an AI training session with our leadership team and, given the efficiencies we now see, we invited him back to train the wider team.”
Clear pricing. Scope where it matters.
The standard team session is deliberately straightforward. Larger cohorts, multi-session programmes and implementation work are scoped separately.
Corporate team session
A practical 4–5 hour session built around your tools, policy and real work.
- Pre-session discovery
- Tailored programme and exercises
- Live workflow or tool build
- Supporting materials
1:1 online working session
A focused online session built around your role, recurring tasks and current AI use.
- Personal working methods
- Instructions and context
- A practical workflow
Use cases, agentic workflows and scale
For teams ready to move beyond individual productivity into deeper use cases, connected agentic workflows and consistent adoption at scale.
- Prioritise and design high-value use cases
- Build and test agentic workflows
- Governance and team-wide adoption
Guy Weaver
Training from an operator, not a manual.
I spent more than 20 years across KPMG corporate finance and Praetura Ventures. I now use AI daily in live advisory, analysis, transaction and content workflows.
The training is grounded in that work. It is designed for professionals who need practical business application, credible judgement and sensible controls rather than a tour of software features.
What firms normally ask.
The session is agreed around your operating environment before delivery. These are the points most organisations want settled first.
Do we all need to use the same AI platform?
No. The method is platform-independent. Examples and exercises are adapted to the tools your organisation has approved and deployed.
How do you handle data security?
Your AI and data-security policy is reviewed before the session. Exercises use permitted information and the training covers classification, permissions and appropriate human oversight.
Can the session be delivered online?
Team sessions can be delivered in person or online where appropriate. One-to-one sessions are delivered online.
Is this suitable for non-technical teams?
Yes. The session is designed for business professionals. It focuses on judgement, working methods and practical application rather than coding.
Tell me where your team is with AI and what you want them to do better.
I will tell you whether a single session is enough, whether the requirement needs a wider programme, or whether the timing is wrong.