From learning about AI to using it meaningfully in your work. An eight-step process. One conversation.
From learning about AI to using it.
This module helps you move from learning about GenAI to using it meaningfully in your real work. It is designed to support practical, applied integration. Starting with small, structured steps that build your confidence, judgement and capability.
You will be guided through a practical, eight-step process that begins with setting a clear intention and ends with taking meaningful, real-world action. Each step is focused, achievable and designed to fit into the way you already work. No technical expertise required.
You will not just try features. You will start shaping how GenAI fits into the way you think, plan and deliver value in your role. This is not about doing everything or doing it perfectly. It is about building momentum through consistent, purposeful action. The goal is to make GenAI part of how you work, not just something you occasionally explore.
Why we are doing this.
Many leaders understand that GenAI has potential but are not sure where to start. They hesitate. They overthink. They wait for perfect conditions. This module is designed to remove that friction by helping you take practical, achievable steps that connect directly to the work you already do. By the end you can.
Move from passive interest to confident applied use of GenAI.
Treat GenAI as a working partner. Not just a prompt engine.
Design small experiments that fit within your existing workflow.
Focus on what is valuable now. Not what is perfect later.
By the end of this module.
Four things you will be able to do.
Initiate and structure an ongoing working relationship with AI as your daily tool.
Build AI into the rhythm of your role by identifying practical, value-aligned use cases.
Design and test a simple integration plan, from insight to action, within a focused, time bound window.
Begin using GenAI as a flexible, responsive partner. Not just a prompt engine.
Eight steps. One thread.
Each step is short. Each builds on the one before. By the end you will have moved from intention to a Day 1 action plan, all inside a single AI conversation.
Name your chat.
A small habit. Big payoff. Every conversation you have with AI gets stored. The ones with names are the ones you can find again. Set the name before you do anything else.
Priming the AI.
What you are doing
You are initiating the collaboration. You open a dedicated chat and state your intent. Making it clear that this will be an ongoing, structured working session. This is called priming. You are setting the tone for how you want the AI to work with you.
Why this matters
Priming signals that you are here to work, not just to experiment. You are establishing the conditions for a more useful, context-aware interaction. The AI begins to treat your inputs as part of a broader journey, not isolated requests. Every response becomes more aligned with your intent and more relevant to your role.
The ten input and output combinations.
Take a screenshot of this slide now. In Step 2 you will upload it to your AI and ask AI to explain what is on the slide.
Deepening the priming.
Take a screenshot of the previous slide showing the ten input and output combinations. Upload it to your chat. Then send the prompt below.
What you are doing
You are reinforcing the kind of working relationship you want to have with the AI. This might involve uploading a file, asking a more open-ended question or showing that you will be working in stages, not just issuing one-off prompts. You are signalling that this will be a process, not a transaction.
Why this matters
This step helps the AI understand that you expect something more flexible, layered and thoughtful. You are training it to stay with you across different formats and phases of thinking. You are not just expanding your perception. You are expanding its pattern of response. The result is a smarter, more adaptive interaction in every step that follows.
Providing context.
What you are doing
You are helping the AI understand the broader situation you are working within. What you are trying to achieve. What constraints or priorities you are juggling. How this task fits into a bigger picture. You are not just giving instructions. You are helping it see the shape of the work.
Why this matters
Context enables relevance. Without it AI can only give generic responses. With it the AI aligns more closely with your thinking and your goals. Providing context is what makes the support useful and applied. Not just accurate.
Generate patterns.
What you are doing
You are beginning to identify meaningful links between AI capabilities and your actual work. You are scanning for alignment. Not yet choosing or committing.
Why this matters
This builds your pattern recognition skills. It helps you see integration as a set of opportunities, not just tasks. You are starting to think systemically. About where AI can enhance, accelerate or augment your work in ways that matter.
Operationalise insight.
What you are doing
You are selecting one idea and turning it into a structured, testable process. Something with steps, logic and a clear intended outcome.
Why this matters
This is where you shift from thinking to designing. A good idea only becomes useful when it is applied in a repeatable way. You are now building working methods, not just collecting insights. Laying the foundation for value creation and scale.
Constrain the effort.
What you are doing
You are setting a clear boundary around what you will work on and for how long. This might take the form of a one-month plan or a defined project window. The goal is to give your AI integration a shape you can commit to.
Why this matters
When everything feels possible, it is easy to do nothing. This step helps you focus your energy by working within a defined scope. It gives structure to your exploration and allows you to make progress without overcommitting. You are designing something realistic, intentional and easy to return to. Even as your priorities shift.
Break it down.
What you are doing
You are translating your plan into a clear set of small, focused actions you can begin right away. This step is about organising your effort so it fits into the rhythm of your work.
Why this matters
Big ideas often stall when they stay too high level. Breaking things down helps you move from thinking to doing without adding pressure. It makes your effort visible, achievable and easier to build on. You are designing your own entry point. One that is practical, intentional and ready to test in real time.
Applied action.
What you are doing
You are initiating execution. This is the moment you act. Taking a clearly defined piece of your AI plan and putting it into use within your actual work. You are no longer planning, testing or thinking. You are delivering.
Why this matters
This step marks the shift from preparation to performance. It moves AI from idea to impact. Application, however small, is where value begins to surface. By putting something into action you gain traction, generate feedback and begin building confidence through results. Integration does not happen in theory. It happens here.
Capture your plan.
Go back to the same AI thread you have been working in. Paste this prompt. Your AI has the context of your role, your 12 responsibilities, your integration plan, your monthly roadmap, your Week 1 plan and your Day 1 checklist. It will help you consolidate.
Share your starting point.
What is your Day 1 action. Where in your role will it land. What is one thing you need to make it work.
About two minutes each. What is the first specific action you are taking with AI this week.
Name the specific responsibility this lands in. Be concrete.
One thing. Permission. Time. Support. Information. Name it out loud.
What you have done.
Not a tour. A working integration plan grounded in your real role, with a Day 1 action ready to go. And the practical pattern of how to brief AI as a working partner.
Set up a working session, not a one-off chat. The AI now treats your inputs as part of a journey.
Listed your 12 responsibilities. The AI now knows the shape of your work, not just the task in front of it.
Three creative ways AI can support you across each of the 10 input output combinations.
Turned one use case into a structured, testable process. A working method, not just an idea.
A bounded plan you can commit to. Realistic. Intentional. Easy to come back to.
A specific, achievable action ready to take. Today or tomorrow. Integration moves from theory to practice.