Leadership Development
Your people are already using AI. This is about using it well
Most AI training explains what the technology is, and within a week almost nothing about the work has changed. AI in Practice runs at three levels instead, because the decision a chief executive has to make and the task an analyst has to finish are not the same problem. Each level has a published agenda and works on the organisation’s own material.
What this includes
- Three levels: 1.5 days for senior leaders, 2 days for managers, 1 day for employees
- Agendas and modules published below, not held back until contracting
- Participants work on their own tasks, not case studies
- Facilitated in Vietnamese or English by consultants based in Vietnam
The problem this solves
Adoption is not the issue. People in your organisation are already pasting work into an AI tool, usually without telling anybody. The issue is that nobody has agreed what it is good for, nobody is checking the output, and nobody has written down what should never go into it.
That gap does not close with a policy document or a demonstration of features. It closes when the people doing the work have tried it on their own tasks, seen where it fails, and formed a judgement they can apply the next day.
Three strands, at every level
Strategy
Where AI changes the economics of the business, what gets prioritised, and what the organisation is prepared to govern.
People
The culture and the skills. What a workforce believes about AI decides whether any of it is used, and belief is not fixed by a memo.
Execution
Pilots that run, measures that hold, and workflows that are genuinely rebuilt rather than described in a slide.
Why this is urgent now
The gap is not between organisations that know about AI and organisations that do not. It is between awareness and applied capability, and it is measurable.
37%
Feel future-ready
Only 37% of professionals say they feel fully future-ready for the AI transition. The rest are improvising.
No.1
Driver of change
AI is now the single largest driver of workplace transformation globally, ahead of every other force reshaping work.
2.4x
Innovation rate
Organisations that actively build AI skills report a 2.4 times higher rate of innovation than those that do not.
ROI
Productivity uplift
Measurable return shows up in productivity metrics where adoption is deliberate rather than left to individuals.
Source: The Adecco Group, 2025 Global Workforce of the Future Report.
Three levels, run separately
Each level is a complete programme and can be run on its own. Most organisations start with the leadership level, because a manager cohort that goes first will design pilots the executive team has not agreed to fund.
Leadership Journey
Focus
Strategic alignment, sponsorship and governance
At this level the question is not how to write a prompt. It is where AI changes the economics of your business, what you are prepared to govern, and what you will say to a workforce that is quietly worried about its own jobs. The session is built to move a leadership team from anxiety to a decision.
Participants leave with
- A stated AI ambition for the organisation, and the strategic pillars under it
- A workable governance model covering risk, accountability and approval
- A 90 day execution plan with owners against each item
- A communication position for the workforce, agreed before the rumours start
What you have at the end
A single agreed AI ambition for the organisation and a prioritised roadmap with named accountability.
Agenda
Day 1, morning
The landscape and the competitive shift
Separating what the technology does from what it is claimed to do, and what each type actually changes in the economics of your industry.
Day 1, afternoon
Mapping the opportunity
A working session across strategy, customer, productivity and people. Ends with the use cases ranked, not listed.
Day 2, morning
Leading the change
Designing the operating model, confronting the unmanaged AI use already happening, and deciding where a human stays in the loop.
Customised to your sector before delivery.
Manager Journey
Focus
Operationalising, piloting and coaching the team
Managers decide whether any of this reaches the work. They sit closest to the tasks and carry the most pressure to deliver more with the same headcount. This level goes past general prompting into workflow analysis: taking a team’s actual process apart, finding where the friction is, and rebuilding it around what the tools can and cannot be trusted with.
Participants leave with
- A method for deconstructing a workflow and spotting where automation is worth attempting
- Advanced role-specific prompting, practised on the manager’s own recurring work
- A designed pilot with defined success measures and a feedback loop
- A way to handle the fear of replacement in a team without dismissing it
What you have at the end
Managers able to identify high value pilots, run them safely, and coach a team through a change to how the work is done.
Agenda
Day 1, morning
Fluency and functional use cases
Hands-on work with the tools that matter to the function in the room, whether that is HR, finance, marketing or operations.
Day 1, afternoon
Workflow analysis and redesign
Mapping the process as it runs today, finding the friction, and redesigning it around human and machine working together.
Day 2, morning
Pilot design and measurement
Putting the pilot in writing: scope, owner and stop conditions. Agreeing what counts as success, in time saved or quality improved, before it starts rather than after.
Day 2, afternoon
Leading a team through it
Handling resistance honestly, and setting the team protocols for data safety and quality control that the organisation will actually follow.
Customised to your sector before delivery.
Employee Journey
Focus
Productivity, confidence and safe use
A practical, fast-moving day aimed at immediate application. It works on the writing, analysis and preparation that fill a normal week, and it puts data safety in from the first session rather than as a closing slide. Participants leave having built something they will use on Monday.
Participants leave with
- Time recovered from repetitive low value tasks, typically several hours a week
- A reliable prompting method, practised until it is habit rather than memorised
- A clear line between what may go into a public tool and what may not
- A personal library of reusable prompts and small automations
What you have at the end
People who use AI daily for routine work with confidence, and who know what must never be pasted into it.
Agenda
Morning
Essentials, and myth-busting
How these systems actually produce an answer, why they invent things while sounding certain, and what that means for anyone relying on the output.
Morning
The prompting lab
Hands-on iteration on drafting, summarising, analysing data and generating options, using the participant’s own work.
Afternoon
Building your toolkit
Assembling a reusable prompt library and wiring it into email, meetings and document preparation so it survives the week after the session.
Customised to your sector before delivery.
Start here
Not ready for a programme? Start with a free 45 minute briefing
A short briefing delivered into a leadership meeting you are already holding, on the practical realities of adoption rather than on the technology. It usually takes about that long to find out whether your leadership team is anywhere near agreement on what AI is for.
There is no charge for it and no obligation attached. It is a briefing rather than a sales presentation, it needs no preparation from you, and booking one commits you to nothing.
- Free, with no obligation to book a programme
- Delivered into an existing meeting, in Vietnamese or English
- No preparation required from your team
How we measure whether it worked
Training that cannot be measured tends not to be repeated. Three measures are agreed with the client before delivery, and the manager level builds the tracking for them.
- Time saved. Hours recovered on the specific tasks a cohort worked on, measured against the same tasks before the programme.
- Innovation rate. Pilots designed and launched in the months after delivery, which is the practical test of whether managers changed anything.
- Risk reduced. A fall in unmanaged AI use, because people now have a sanctioned way to do what they were already doing quietly.
Where it goes wrong, and how we teach people to see it
The dangerous failure is not the obvious error. It is the fluent, plausible, well-formatted answer that is wrong in a way a busy reader will not notice. A manager who has never been shown that pattern has no reason to look for it.
We run those cases on purpose. Participants check output against something they already know to be true, and build the habit of asking what evidence sits behind an answer before it goes anywhere near a client or a board paper.
How we run it in Vietnam
Facilitated in Vietnamese or English by consultants based here, with examples drawn from the sectors our clients operate in rather than from imported material. Mixed-language cohorts are common.
Content is customised to the client’s sector before delivery. We run this programme with clients in finance, manufacturing, pharmaceuticals and technology, and the use case work is built from the examples and constraints of the sector in the room.
AI in Practice is one of more than ten established programmes built from a catalogue of more than fifty modules, so it can run on its own or sit inside a wider development programme where AI capability is one of several things a cohort needs.
Common questions
How long does each level take?
The Leadership Journey runs for 1.5 days, the Manager Journey for 2 days and the Employee Journey for 1 day. Each is a complete programme in its own right, and the full agenda for all three is published on this page rather than held back until contracting.
Which level should we start with?
Usually the leadership level. A manager cohort that goes first will design pilots the executive team has not agreed to fund, and the momentum is lost while approval is sought. Where a leadership team has already aligned, starting with managers is the faster route.
What do participants leave with?
Work they have built and tested using their own real tasks. Leaders leave with a stated AI ambition, a governance model and a 90 day plan. Managers leave with a designed pilot and its success measures. Employees leave with a reusable prompt library and clear data safety limits.
How do you measure the return?
Three measures agreed before delivery: time saved on the specific tasks a cohort worked on, pilots designed and launched in the months afterwards, and the reduction in unmanaged AI use once people have a sanctioned way to work. The Manager Journey builds the tracking.
Can the programme be delivered in Vietnamese?
Yes. AI in Practice is facilitated in Vietnamese or English by consultants based in Vietnam. Mixed-language cohorts are common, and materials are prepared in the language the group will actually work in.
How is this different from buying online AI courses?
Online courses build awareness, which is not the constraint. This builds capability. Sessions are facilitator-led and worked on your own live tasks, so people leave with a designed pilot, a rebuilt workflow or a tested prompt library rather than a completion certificate. Course licences also tend to go unused; a facilitated cohort does not.
Can the content be customised to our industry?
Yes. Use cases and examples are built for the client’s sector before delivery rather than adapted in the room, and the module agenda is adjusted where a function needs more or less of a given topic.
Is the 45 minute briefing really free?
Yes. There is no charge for the briefing and no obligation to book a programme afterwards. It is delivered into a meeting you are already holding, needs no preparation from your team, and is a briefing on the practical realities of adoption rather than a sales presentation.
Do participants need a technical background?
No, and none is assumed. The programme is built for business leaders and their teams rather than for data scientists. The work is about judgement, economic impact and how people behave around a new tool, in plain language.
Tell us the situation, not the service
Describe what you are dealing with. If we can help, we will explain how.