Start from your situation
Executives often tell Ramon that their teams now use AI in ways the executives do not. He describes that conversation in Loop Engineering: the AI skill executives need next. The place to start depends on whose work has to change first.
| Your situation | Start with |
|---|---|
| Our people have AI tools but use them unevenly. | A half-day or full-day Practical AI Workshop on their own recurring tasks |
| Our leadership team needs a shared view before it sets direction. | An executive briefing, a format of the Practical AI Workshop |
| Our executives need to use AI on their own work first. | Executive AI Coaching |
| A workshop worked, and the practice now needs to hold. | A multi-week program, with practice on live work between sessions |
| Our managers do not follow up on how AI is used. | A Practical AI Workshop with a named manager accountable for the outcome |
| Our board needs to understand AI before it oversees it. | An executive briefing for the board |
| We do not know where we stand. | The AI Readiness Assessment: up to 20 questions across 5 areas, ending with a decision brief |
| The work has exposed a workflow problem or an investment decision. | Resolve a business problem |
Start with a Practical AI Workshop
The workshop is the usual starting point for a team. It runs in 4 formats, each on the team's own recurring tasks.
| Format | Duration | Suits | People leave with |
|---|---|---|---|
| Executive briefing | 60 to 90 minutes | An executive team or board | A shared view of what AI can and cannot do in your business |
| Half-day workshop | Half a day | One team with shared recurring tasks | A written method for each task covered |
| Full-day workshop | 1 day | A team or function with several kinds of work | Written methods and agreed checking rules |
| Multi-week program | 4 weeks, 1 session a week | A team that needs the practice to hold through a work cycle | Methods used on live work and reviewed each session |
Capability at 3 levels
| Level | Formats | Outcome |
|---|---|---|
| Executive capability | Executive briefing or Executive AI Coaching | Leaders agree priorities and make decisions. |
| Team capability | Half-day workshop, full-day workshop or multi-week program | People use approved tools on real work. |
| Organisational capability | Champions, and ongoing adoption and enablement | The organisation keeps internal playbooks, named owners, follow-up and measured use. |
Executive capability comes first
In Ramon's view, executives who have not used AI on their own work cannot judge where it helps or how to govern it. Daily use on their own papers, decisions and updates builds that judgement. The executive briefing and Executive AI Coaching are built for this.
When executives use AI openly and talk about what worked, their teams treat it as expected practice. Ramon covers this in his article on culture and AI adoption.
AI tools we work with
We work with Microsoft Copilot (formerly Microsoft 365 Copilot), ChatGPT, Claude and Gemini. Sessions use the tool your organisation has approved, under the settings it has configured. People practise in the environment they will use at work.
The same model can behave differently in different products. Each product sets how much reasoning the model applies and what information it can reach. Part of building capability is knowing those settings in your own tool.
How capability grows
Capability usually grows from:
- an executive briefing to Executive AI Coaching, when leaders need to move from understanding to decisions
- a single workshop to a multi-week program, when people understand the tools but their work has not changed
- coaching to champions and adoption, when useful practices need to spread and last
- these programs to Resolve a business problem, when they expose a specific workflow, investment decision or implementation blocker.
How progress is measured
Measure whether people still use the new methods weeks after the sessions end. Then check whether accepted output is better and whether the whole task, including checking and corrections, takes less time. Set the baseline before the work starts so you can measure the change.
Attendance and tool use measure activity. Time saved becomes a business result when someone decides what work it moves to and which measure that work changes. Ramon sets out the measures in AI productivity gains: measuring real impact.
Voluntary use is a useful signal. People who keep using a method without being asked have found it worth the effort. Review the measures with the accountable manager a few weeks after the sessions end.
How the work runs
Every capability engagement starts with a conversation about whose work has to change, which tasks matter and which tools are approved. It ends with written working methods, a manager who follows up and a measure of use. You provide a person who owns the outcome, people who can bring real tasks and access to the approved tool.
Capability work does not include an organisational audit, a strategy roadmap or building software. Those sit under Resolve a business problem.
Frequently asked questions
How do we know capability is improving?
Capability is improving when people keep using the new methods, accepted output improves and the whole task takes less time. How progress is measured sets out each measure.
What happens if capability work uncovers a bigger problem?
The work moves to Resolve a business problem, where we scope the workflow, investment decision or implementation blocker as the next stage. Applied AI Australia advises and Acquire Intelligence™ delivers, as one engagement from diagnosis to working change.
Which AI tools are most effective for leadership teams?
The most effective tool is the one your organisation has approved, used daily on the leaders' own work. Our guide to choosing between Microsoft Copilot, ChatGPT, Claude and Gemini sets out what each vendor states about business data.
Our staff already use ChatGPT informally. What should we do?
Find out which tasks people use it for and what information goes into it. Then move that work onto an approved business account with settings your organisation controls. Where one workflow depends on it, the Operational AI Audit follows that workflow from input to accepted outcome before any software purchase.
Do the AI tools use our data to train their models?
In their business tiers, Microsoft, OpenAI, Anthropic and Google each limit the use of customer content for model training, on terms that differ by product. Microsoft states that Microsoft Copilot prompts, responses and Graph data are not used to train foundation models. OpenAI states that ChatGPT Enterprise, Business and Edu data is not used for training by default. Anthropic states that prompts, data and results on its enterprise offering are not used to train its models by default. Google states that Workspace content is not used for generative AI model training outside your domain without permission. Where data location matters, OpenAI states that eligible ChatGPT Enterprise and Edu customers can store content at rest in Australia. These statements cover business tiers only, so capability work uses your organisation's approved business accounts. Confirm the settings in your own tenancy.
Tell us whose work has to change first and which tools you have approved.