AI Ideation Workshop
An in-company, hands-on session that turns AI possibilities into tangible impact. You bring the business challenges. We bring the structure, the data scientists, and the AI superpowers.
The Workshop
AI is no longer a distant future. It is an everyday tool. Yet many organizations struggle to put it to work, because success takes more than technology. It takes a real business problem, an internal champion, and a culture and infrastructure ready to adopt. The AI Ideation Workshop is built around exactly those conditions.
In a single facilitated session we bring your people into one room, surface the operational pain across functions, and translate it into AI use cases that are realistic and worth building. You do not need a data strategy or a technical background to take part. You leave with a ranked, costed shortlist and a plan attached.
Why now
AI is an everyday tool, but many organizations still struggle to implement it. Three barriers explain most of the failures. The workshop is built to remove each one.
The Outcome
Not a deck to file away. A set of decisions your team made together and can act on the next morning.
The Method
The workshop runs in-company, on your site and just for your team. We can start at any time of day, ideally around 10:00 depending on the location. Four phases move the room from raw frustration to a prioritized action plan, and the durations below flex with the size of your group.
Opening
A short introduction, a working definition of AI, and the three challenges that block most AI initiatives: no real business problem, no internal champion, and an organization not ready to adopt.
Phase 1 · Individual
Using the User Story Canvas (role, task, blocker, cause, emotion), each participant writes at least two stories: one about their own role and one about a colleague's. Topic cards prompt ideas. Any problem is fair game, not just the obviously technical ones.
Break
Phase 2 · Groups of 3 to 5
Groups pick the stories worth solving, receive their AI Super Power cards, and brainstorm solutions as a wish list, with cost and feasibility set aside for now. A data scientist joins each group.
Included
Phase 3 · Groups
Teams pitch their use cases, then the room votes with colored sticky notes across three lenses:
Break
Phase 4 · Groups
COMPUTD scores the votes and plots each use case on an impact-feasibility matrix. The room confirms the ranking, discusses the least feasible ideas, and agrees which use cases fit the organization's priorities and culture.
The Toolkit
A shared deck of AI capabilities gives non-technical teams a concrete vocabulary. Each card maps a real problem to what AI can actually do, so use cases stay grounded.
Spot data points that deviate from the norm, from overheating machines to unusual readings.
Predict future demand and required resources by learning patterns from historical data.
Read what a request actually means, not just what it says, for example a quote versus a complaint.
Group data, machines, or issues by shared traits so common problems can be tackled together.
Sort items into predefined categories, such as approved or rejected parts on a line.
Follow digital traces through a process to reveal where work slows down and where it flows.
Order tasks by impact and urgency, for example which machines need maintenance first.
Check automatically that each step follows the rules, flagging skipped or missing actions.
Turn data into a clear visual view so a situation can be judged at a glance.
Judge automatically whether something meets set criteria, from suppliers to output.
Fill gaps in incomplete data so a reliable picture still emerges.
Understand and generate language, so operators query complex manuals in plain words.
Delivered
Manufacturers have already run the session and walked out with a clear next step. Here is what came out of the room.
Six people, from the owner to shop-floor programmers, turned tool-management, planning, and forecasting gaps into four use cases. The room ranked a tool-management system as the clear priority and left with a four-phase roadmap.
An industrial-engineering team split into two groups and turned production and quality challenges into four use cases, from automated planning to AI-driven end-of-line inspection, each scored on impact and readiness.
The Fit
Teams wrestling with tool management, machine planning, quality control, and forecasting that still runs on spreadsheets and instinct.
Organizations with fragmented data and reactive workflows that want to find the repetitive, scalable tasks AI can genuinely lift.
Owners and directors who want a structured, honest read on where AI pays off before committing budget to a build.
Mixed rooms of business and technology roles, from strategy and sales to engineering and IT, where the best use cases come from people who see the problem from every side.
Why attend
A grounded way to put AI to work in your business, not a set of slides about the technology.
Data scientists at the table, guiding every step from raw problem to scored use case.
Use cases shaped around your organization and the constraints it actually operates under.
Get started
We run the workshop in-company, on your site, for 8 to 16 people from across your business and technology teams. Lunch is included, and we can start at any time of day, ideally around 10:00 depending on the location. We come to you, facilitate the session, and leave you with a ranked shortlist and a roadmap.