From using AI
to leading it

Start with the work, not the software

EuroCham Vietnam asked for something practical: help people use AI in their jobs, then help them think through what that use means for their organisations. Registration was capped at one attendee per company, which made the room a cross-section of European business in Vietnam — pharmaceutical and consumer-goods multinationals, logistics operators, real-estate and construction firms, law firms, an international NGO, and manufacturers and consultancies across more than fifteen sectors.

A pre-series survey asked for real use cases, tools people could apply, and a clearer idea of where to start. So the series ran in that order. First, work with the technology. Then, work through the decisions that come with leading its use.

The finding

The opening poll asked participants to place their organisations honestly on an adoption scale. Eight said Experimenting. Eight said Piloting. Twelve said Scaling — by self-assessment, the most AI-mature room I had worked with in any sector.

Not one placed their organisation at Embedded.

That empty column is the corporate AI problem in miniature. These companies are adopting — many are scaling — but none would claim AI has become how the organisation actually works. Individuals are learning fast. The institutions around them aren’t. The series was built for that gap.

One real task. Two ways to tackle it

The same poll showed why a three-hour session for this room could not teach to the middle: there was no middle. Participants running n8n automations and local models sat beside participants using AI to check the grammar in their emails. Copilot led the tool count — enterprise IT had made its decision — but “agents” was already among the most-cited answers.

Session one, AI Is Already in the Building, put everyone on the same task: brief a new colleague on the biggest challenge facing your team. Some built a structured prompt, ran it, inspected the output and refined it into something reusable. Others turned the same task into a persistent assistant that carries its instructions and context. Both routes used the same four questions — what to delegate, how to describe it, how to judge the result, and what responsibility stays with the person. A final segment took participants from idea to working app prototype.

The point was not to teach everyone one tool. It was to give the n8n user and the grammar-checker a structure that stretched both.

The sessions used the 4Ds — Delegation, Description, Discernment, Diligence — from the AI Fluency Framework by Rick Dakan and Joseph Feller, developed with Anthropic.

Put judgement under pressure

The series was published with a commitment: session two would be redesigned around what session one revealed. Participants asked for AI-assisted decision-making, local and on-device models, and what all this means for jobs. Session two, Leading AI in Your Organisation, was built from those requests.

The Saigon Bottleneck

Two million dollars of inbound components are about to be frozen at Cat Lai Port. The board wants answers. You have an AI. Over four decision points, each choice moved a live scorecard — operational integrity, regulatory risk, budget — and made delegation and accountability concrete: what do you let the AI do, what do you check, and who owns the consequences?

The rest of the session connected that experience to research, agent oversight and on-device AI, and closed with a governance worksheet: your exposure, your delegation boundaries, your accountability arrangements. The progression across the series was from using AI on an individual task to deciding how it should operate in an organisation.

They wanted more

After session one, demand led EuroCham to expand session two to forty seats — a bigger room, more capacity — and fill it.

EuroCham’s post-series feedback reported 4.8 out of 5 for overall satisfaction and 4.9 for the trainers. The most consistent request was for more time and more hands-on, real-life exercises. Participants also asked for follow-on work on AI for data analysis, and on privacy, security, reliability and over-reliance.

The Saigon Bottleneck is a simulated business situation, not a client incident. Feedback figures as supplied by EuroCham for the series; they describe participant response, not subsequent company performance.

What this demonstrates

The frameworks on this site were built in higher education and have been tested on diplomats, accountants, governing bodies and police commanders. This series was the corporate test: thirty-five companies, fifteen-plus sectors, maturity ranging from grammar-checking to agent-building, in a room convened by the European business community’s own chamber. Same problem underneath. Same gap between individual capability and institutional absorption.