Our 20x ROI Commitment
This workshop gives your leadership team a practical way to start with AI, and it is built to get you moving quickly: you leave with initiatives you can act on straight away. We are confident enough in that to put a number on it. If the initiatives your team leaves with do not represent at least 20 times the cost of the session, we will run it again for you at no cost, or give you the equivalent in consulting days to keep exploring AI in your business.
AI-First Thinking is a facilitated executive immersion for leadership teams. It runs as half a day, at your site, and it ends with a working artefact: a set of AI initiatives your own leaders have built, scored and sorted, well suited to becoming your AI roadmap for the next six to twelve months.
Almost Everyone Has Started With AI, and Maturity Varies Widely
McKinsey's The State of AI research, published in March 2025, found that 71 percent of organisations regularly use generative AI in at least one business function, while only 1 percent believe AI is fully integrated into the way they work. Almost everyone has started, and organisations vary significantly in how far they have taken it.
In our experience what separates them is rarely budget or tooling. It is that most organisations are not sure how to look for opportunities beyond personal productivity. They know the opportunity is there. They are much less clear on how to spot it in their own work, in their own processes, on an ordinary Tuesday. This session is built to close that gap, and your leaders leave with the toolkits we use to find those opportunities, so the search carries on after we have left the room. It is built for organisations of any size, including those well below the scale that usually justifies a strategy programme.
The Outcome is Your AI Roadmap
Every table leaves with its own list of AI initiatives, scored against a common set of dimensions and sorted into an order the room can defend. The list belongs to you.
What the Workshop Covers
Four modules, with breakouts between them where the room practises what we have just covered. You leave with a good list of initiatives, and, more to the point, knowing how to keep finding and prioritising them yourselves once we have gone.
What's Possible Today with AI
We start by getting everyone in the room to a common view of what the tools already do. A leader who has only ever asked AI for one draft of one email will only ever bring forward one-email-sized ideas, so this is the foundation the rest of the day rests on. We want the room bold enough to propose things that go well past what Microsoft 365 Copilot on its own would solve.
Seeing It Work Beats Being Told It Works
This is the seed planting part of the day. We build AI agents for a living, so rather than describing them on a slide we bring working ones into the room and run them. People need to see what is possible before they can picture it inside their own function, and that is what makes the breakouts productive.
The Anatomy of an AI-Enabled Process
Nearly every opportunity follows one pattern: something starts the work, an agent carries the middle, and the result lands somewhere. Once a room can see that pattern, candidates start surfacing in work people have done the same way for years without ever questioning it. This is where the long list gets built.
From a Long List to a Shortlist You Can Defend
Scoring each idea, converting the judgement that lives in people's heads into rules an agent could apply, and sorting what survives into a shortlist with a defensible order to it.
Themes We Work Through on the Day
A handful of ideas do most of the work in this session. Each one changes the kind of opportunity people go looking for, and each one tends to reset an assumption the room walked in with.
Your Expertise Is the Multiplier
Prompting skill has a ceiling. Depth of business knowledge does not. This is usually the point at which the senior people in the room realise they are the scarce input, which changes how they think about skilling their teams.
Tacit Knowledge Is the Real Data Problem
Most organisations believe they have to fix their data before they can start. For agents the barrier usually sits somewhere else entirely: in the judgement your people apply every day and have never written down.
AI, Automation and Integration Are Different Things
Separating the three keeps a long list from turning into a set of integration projects with six-figure price tags. It also identifies the ideas that need no AI at all, which is a cheaper and faster answer when it is the right one.
Good Enough Beats Perfect
Building the first version is fast. Getting to the point where you trust it is the work. We show the room where the effort actually goes, and why a person stays in the loop while that trust is being built.
The Case Studies We Bring Into the Room
The published research on where AI is heading is useful and we draw on it, and it also dates quickly: a report describes what the technology could do when it went to print. We have been building with it this month, so what we run in the room is what the technology does now.
So we bring a blend: agents we have built ourselves, and work we have seen across the industry that speaks to the problem in front of you.
Recognition makes a room lean in and start volunteering its own examples so we bias towards case studies from your own industry. The pattern underneath an opportunity travels between sectors far more readily than the sector detail does, so we always include a handful from outside it as well. Teams that only ever look at their own industry tend to build a narrower list.
We agree the shortlist with you before the day. More of our own delivery work is set out in our client project case studies.
How We Help You Score and Prioritise AI Opportunities
The method itself is one of the things you take away. Your team learns a repeatable way to score and rank AI ideas, so the next set can be prioritised long after the session, without us in the room.
A Structured Way to Rank What You Found
Every idea on the shortlist is scored the same way, across seven dimensions: business impact, frequency, scope for automation, build effort, safety, the handovers involved, and how readily people will adopt it.
Scoring on a common basis is what turns a list of good ideas into an order you can defend. Organisations standing up an AI Centre of Excellence use the same matrix as the gate every new idea passes through, so proposals arrive scored instead of argued one at a time on the strength of whoever is presenting.
We Also Introduce the Three B's
Beachhead, Boost and Breakthrough: three buckets that turn a scored list into a sequence.
They exist because a score on its own says nothing about what an organisation is ready to absorb. Ordering the work this way is as much a change management decision as a technical one, and it is what stops a programme stalling in its second year. We walk the room through how the two fit together.
Who Should Be in the Room, and How It Runs
- Format. Half a day, run at your site. We can flex the length where there is a reason to, and half a day is what we recommend: it keeps the session dense, and it limits the opportunity cost of having your executive team out of the business.
- Who attends. Leadership team members, and the domain experts who know your business intimately and are looking to improve it.
- Group size. Up to around 30 people, seated at tables. Each table becomes a working group for the breakouts, so the room is set up that way from the start.
- Prerequisites. None. We do ask that attendees are already confident Copilot users, and if they are not, Australia's best Microsoft 365 Copilot training is the place to start.
- What we prepare. We shortlist the case studies for your sector, build live agent demonstrations to run on the day, and work with your subject matter experts beforehand to understand your existing technology landscape, who will be in the room, and what your organisational priorities are.
- What you leave with. Your long list, your scored shortlist ordered into a roadmap for the next six to twelve months, and one candidate idea per table that could start within a month.
- What happens next. Coaching days to work the shortlist properly, or an implementation engagement to build the first candidate. Neither is a condition of running the session.
AI-First Thinking sits alongside Hypergen Rails, the governed methodology we use when a shortlisted idea turns into a custom build.
Frequently Asked Questions
What is AI-first thinking?
AI-first thinking is the habit of asking what a workflow would look like if it were designed around AI agents from the start, instead of asking which existing steps could be done faster. It moves a leadership team from personal productivity, where individuals use tools like Microsoft 365 Copilot to work faster, to organisational effectiveness, where whole workflows run differently because an agent carries the repetitive load.
How is this different from AI awareness training?
An awareness session explains what AI is and what the tools do. AI-First Thinking is pitched past that and is built around working breakouts in which your own leaders produce a set of AI initiatives specific to your business. The output is a scored shortlist your team owns, so the session is judged on the quality of that list rather than on what was covered.
Do we need to fix our data before beginning with AI?
Usually not. Data quality matters for analytics, but generative AI works well on unstructured material such as emails, documents, transcripts and policy exceptions. The barrier most organisations hit is that the judgement their people apply is undocumented rather than that their database is untidy. Capturing that tacit knowledge is one of the themes the session is designed to surface.
Who should attend an executive AI workshop like this?
Leadership team members together with the domain experts who know the business intimately. The depth of business knowledge in the room sets the quality of the ideas that come out of it. A session attended only by executives tends to produce a thinner list than a session that also includes the people who handle the exceptions every day.
What happens after the session?
Most organisations take one of two paths. Coaching days work the shortlist properly with the teams that own each idea and get something started. An implementation engagement builds the first candidate, usually with a person reviewing every output while the quality is validated. Neither is a condition of running the session, and the roadmap is yours either way.
How long does an AI-First Thinking session take?
Half a day, run at your site. We can flex the length where there is a reason to, and half a day is what we recommend. It keeps the content dense, and it limits the opportunity cost of having an entire leadership team out of the business for longer than the session needs.
How does this compare with an AI strategy engagement from McKinsey, BCG or Bain?
We respect that work and we draw on it: the research those firms publish on AI adoption is useful, and we take the trends in it into the room with us. What we bring is the best of both worlds, top-tier consulting thinking with the experience only builders have. It means we can work with organisations well below the scale that justifies a tier-one engagement, and that what we demonstrate is what the technology does now rather than what a report described when it went to print.
Ready to Build Your AI Roadmap?
Tell us who would be in the room and what your leadership team is trying to work out. We will choose the case studies and build the live demonstrations for your sector before the day.