Why was it time to get the AI journey moving?

The company was already using AI — but one department at a time, not together. To the question “how does your department use AI”, everyone had an answer — but the answers differed from one another. The question “how do we use AI together” had never been asked, so it had no answer.

This was not a lack of ambition. The will was there, experiments had been run, and there was no shortage of enthusiasm. But without a shared view of the situation and direction at the organisational level, the experiments remained isolated dots.

In practice, this meant the company needed concrete guidance on how to move forward on its AI journey — not more inspiring presentations about what AI could do.

What goals were set for the project?

The goal was that after the project, the company would have:

• A clear vision and understanding of what AI means for this organisation in particular
• A roadmap for how to reach the goals that were set
• A plan for moving forward in a controlled and structured way
• A culture of continuous learning — and the building of people’s skills under way

One big principle guided the whole engagement: no inspiration without control, and no control without inspiration. Building AI capability requires both, side by side — enthusiasm alone leads to scattered experiments, control alone kills the spark.

How did we approach the work?

The engagement was built around three phases:

Phase 1 — AI and change readiness assessment

We ran a staff survey, reviewed existing documentation and interviewed key people. Among other things, the assessment looked into:

• current AI use and shadow AI
• the organisation’s capacity for change
• concrete use cases
• trust in leadership and psychological safety

The purpose of the assessment is to uncover the causes and effects and the blind spots that are hard for an organisation to spot on its own — especially when people are involved.

Phase 2 — Leadership workshops

Workshop 1: A shared understanding. We opened up, in plain language, what AI — and agents in particular — can do today, and identified the opportunities, risks, limitations and boundary conditions (values, vision, data protection). We also went through what kind of leadership and governance AI calls for.

Workshop 2: A shared vision and an AI use case map. We went through the results of the staff survey, built a shared “why” story and goals, and created a use case map of where AI could be put to work across departments and processes. We also identified the tasks that will remain with people.

Workshop 3: Leading the transformation. We covered how the leadership team works as one team across departmental lines, what good leadership means in the age of AI, and refined the roadmap into practical actions.

Phase 3 — Final report

The final report brought together:

• findings from the workshops and from the AI and change readiness assessment
• a preliminary use case map
• a roadmap for a controlled and considered start to the AI journey
• a 360° view of the organisation’s readiness for transformation from four angles: people, governance, leadership, and tech and data

The engagement lasted around three months and was carried out in early 2026.

What did the project deliver?

The concrete deliverables:

• an AI and change readiness report to support the leadership’s decision-making
• an AI use case map by department and by process
• a roadmap for a controlled start to the AI journey
• a 360° view of readiness for transformation (people, governance, leadership, technology)

The end result gave the company what they had been looking for: concrete guidance on how to move forward — not just an analysis of the situation.

In the client’s words

“Your services in general — and the workshops too — have been exactly what we expected to get. Concrete guidance on how to move forward on our AI journey.”

— Client representative, COO, technology industry

What did we learn?

During the project — and in other similar engagements — several lessons became clear that apply more broadly to starting an AI journey:

• Everything starts with a shared view of the situation — until leadership is on the same page, nothing else can move forward in a systematic way
• Staff surveys reveal the blind spots an organisation cannot see on its own — especially when it comes to trust, shadow AI or psychological safety
• A framework tested in practice saves time, as leadership can focus on their own business instead of building a model from scratch
• The biggest challenge in applying AI is not the technology, but making it part of the business, leadership and decision-making

Who will find this case useful?

This case is especially relevant for:

• Large enterprises (as defined by the EU — roughly 250–800 people) whose AI journey has started more slowly than their ambition would suggest
• The technology industry and other traditional sectors, where change requires a shared view among leadership and getting people on board — both at the same time
• Leadership teams that want to start the AI journey in a controlled way — not by trying out individual tools here and there

How does a similar engagement usually proceed?

This engagement reflects Astu Labs’ standard model for getting an AI transformation started:

1. AI and change readiness assessment — staff survey, documentation review, interviews with key people
2. Workshops for leadership and internal AI teams
3. Final report — findings, use case map, roadmap and a 360° view of readiness

In calendar time this typically takes around 2–3 months — tight enough to keep the momentum, loose enough that between workshops there is time to digest the thinking and look at the business in a new light.

Considering something similar?

If the AI journey in your organisation has stayed at the level of ambition and you are looking for concrete guidance on the next steps, this framework may be a good fit for you.

→ Book a 30-minute conversation — we’ll go through where you stand and whether a similar approach would fit your situation.