Your team doesn't need another
ChatGPT tutorial.
On-site workshops that teach business process owners how to identify, evaluate, and implement AI at the process level — where the real operational leverage lives.
The AI training your team has received so far is almost certainly useless.
Most corporate AI training programmes teach people how to write better prompts for ChatGPT. That is like teaching a factory foreman how to use a calculator and calling it a digital transformation.
The real question is not whether your people can use AI tools — they already can, and they will figure out the rest. The real question is whether your organisation understands where AI creates genuine operational leverage at the process level. Which workflows should be automated? Which decisions can be augmented? What data are you sitting on that you have never been able to use?
That is what we teach. Not tools. Thinking.
- —How to write better prompts
- —Overview of AI tools on the market
- —Generic use cases from other industries
- —Theoretical frameworks with no action plan
- Map your actual processes for AI opportunity
- Build business cases with real ROI numbers
- Define implementation roadmaps you can act on
- Leave with a prioritised AI project portfolio
We teach the thinking that comes before the technology.
Every AI implementation that fails does so for the same reason: the organisation started with the technology and worked backwards to the problem. They bought a tool, assigned it to IT, and hoped for transformation.
The organisations that succeed do the opposite. They start with the process — the actual workflow, the actual bottleneck, the actual cost. They understand the problem deeply before they evaluate any solution. And they involve the people who own the process, not just the people who manage the servers.
You leave with a concrete, prioritised roadmap. Not a slide deck.
"The companies that will lead in AI are not the ones with the best tools. They are the ones whose people understand where the tools belong."
Four modules. Two days. One clear roadmap.
Each module builds on the previous one. By the end of day two, your team has a prioritised AI implementation portfolio they can act on immediately.
AI Process Landscape — Where Does AI Actually Work?
We strip away the hype and teach your team to see AI through the lens of business processes. Not every process benefits from AI. This module gives your team the framework to tell the difference.
Key Topics
- 1 The AI opportunity matrix: automation vs. augmentation vs. generation
- 2 Process characteristics that predict AI success
- 3 Where AI fails — and why most pilot projects never scale
- 4 Mapping your current process landscape for AI readiness
- 5 Data requirements: what you need vs. what you think you need
- 6 Hands-on exercise: mapping three of your actual processes
Building the Business Case — From Process Pain to ROI
Knowing where AI works is not enough. Your board needs numbers. This module teaches your team to build defensible business cases that connect process improvements to financial outcomes.
Key Topics
- 1 Quantifying the cost of manual processes (time, error, opportunity)
- 2 AI implementation cost structures: what things actually cost
- 3 ROI frameworks that work for AI projects specifically
- 4 Risk assessment: technical, organisational, and regulatory
- 5 Build vs. buy vs. partner: when each approach wins
- 6 Workshop exercise: build a real business case for your highest-value process
Implementation Strategy — From Roadmap to Reality
Most AI roadmaps die in the drawer. This module focuses on the practical mechanics of turning AI strategy into delivered projects — vendor selection, team structures, change management, and the governance frameworks that keep AI projects on track.
Key Topics
- 1 The 90-day AI pilot framework: how to prove value fast
- 2 Vendor evaluation: what to look for and what to avoid
- 3 Internal team structures that support AI adoption
- 4 Change management for AI: the human side of automation
- 5 Integration patterns: connecting AI to your existing systems
- 6 Workshop exercise: design your 90-day pilot plan
AI Governance & Scaling — Building for the Long Term
One successful AI project is a proof point. A portfolio of AI projects that scales across the organisation is a transformation. This module covers governance, ethics, data strategy, and the organisational architecture needed to sustain AI adoption.
Key Topics
- 1 AI governance frameworks for mid-market and enterprise
- 2 Data strategy: building the foundation for continuous AI value
- 3 EU AI Act compliance: what you need to know
- 4 Ethical AI: practical guidelines, not theoretical debates
- 5 Scaling from pilot to portfolio: organisational patterns
- 6 Final exercise: build your prioritised AI project portfolio
Built for the people who own the processes and the people who fund them.
Our workshops are designed for mixed audiences — bringing decision-makers and process owners into the same room with the same language and the same methodology.
C-Suite & Directors
You need to understand where AI creates strategic value — not just tactical efficiency. You need a framework for evaluating AI investments and a roadmap your board will approve.
Typical Attendees
Process Owners & Department Heads
You own the workflows that AI will transform. You know the bottlenecks, the workarounds, and the institutional knowledge that never got documented. You are the bridge between strategy and reality.
Typical Attendees
IT & Digital Leaders
You will be asked to evaluate, procure, and integrate AI solutions. You need to understand the infrastructure requirements, integration patterns, and governance frameworks before the requests start arriving.
Typical Attendees
Two days. Your office. Your actual processes.
Pre-Workshop Brief
1 week beforeWe review your organisation's process landscape, systems, and strategic priorities so the workshop content is tailored to your reality.
Day 1: Assessment
Full day on-siteModules 1 and 2. Your team learns to evaluate AI opportunities and builds business cases using your actual processes.
Day 2: Strategy
Full day on-siteModules 3 and 4. Implementation strategy, governance, and the final exercise: building your prioritised AI project portfolio.
Post-Workshop Delivery
1 week afterYou receive a documented AI readiness report with your prioritised project portfolio, business cases, and recommended next steps.
You leave with a portfolio, not a slide deck.
Every workshop ends with a concrete, prioritised AI project portfolio — built by your own team, using your actual processes, during the workshop itself. This is not a theoretical framework. It is a document your leadership team can take into the next board meeting.
More importantly, your team leaves with a shared language and methodology for evaluating AI opportunities independently. You will not need us to tell you where AI fits — you will see it yourselves.
What you walk away with
- 1 Prioritised AI project portfolio with business cases for your top 3–5 opportunities
- 2 AI readiness assessment for your key business processes
- 3 ROI models built on your actual operational data and costs
- 4 90-day pilot plan for your highest-priority AI project
- 5 Vendor evaluation framework tailored to your requirements
- 6 AI governance guidelines customised for your organisation
- 7 A shared internal language for evaluating future AI opportunities
Your team is ready. They just need the right framework.
In a 30-minute call, we can scope your workshop — tailoring the curriculum to your industry, your processes, and your strategic priorities. No slides. No sales pitch. Just a conversation about where AI fits in your organisation.