AI enablement in the workplace: from workshops to shared practice
AI enablement gives your teams a shared frame of reference for using AI in their work: hands-on workshops, internal champions and an upskilling plan.
AI enablement moves teams from isolated use of AI to shared practice: knowing where it is reliable and where it is not, applying it to their own tasks and checking what it produces. At Colombani.ai the programme runs over two to eight weeks and combines workshops on business cases, training of internal champions and adoption measured at one and three months. Colombani.ai is a Qualiopi-certified training provider (certificate QUA009472).
Updated
What you receive
Cultural maturity assessment: barriers, appetite, and usage levels per team
Hands-on workshop programme adapted to each role (non-technical, technical, management)
Identification and training of internal AI champions
6-month upskilling plan with adoption KPIs
Internal communication kit: FAQ, best practices, validated use cases
Our method
Cultural assessment
Interviews and internal survey to map maturity levels, barriers, and expectations per team. The assessment distinguishes existing uses, tasks to improve, and internal rules to follow. A baseline is agreed with managers so progress can be tracked after the workshops.
Workshops & experimentation
Hands-on sessions by role, using tools authorised by the organisation and configured for daily work. Participants experiment with a selected task, compare the result against agreed criteria, and identify what requires human review. Exercises use data the organisation has authorised for use.
Champions & relays
Selection and in-depth training of AI leads in each team. They become the first point of contact internally: helping colleagues get started, sharing validated practices, and reporting blockers. Their role and the questions to escalate to business leads or IT are defined.
Follow-up & anchoring
Adoption measurement at 1 and 3 months. Follow-up examines reuse of the selected use cases, output quality, time spent on comparable tasks, and difficulties encountered. Observations are compared with the baseline to adjust the plan. The number of accounts created is not enough to measure adoption.
Who leads the engagement
Ulysse Trin, founder of Colombani.ai, holds the Claude Certified Architect Professional certification, issued by Anthropic, and nine practitioner certifications issued by OpenAI.
Check the certificationsPrice
Each engagement is quoted according to the number of teams and the duration chosen.
Frequently asked questions
What is AI enablement in an organisation? +
AI enablement gives teams a shared understanding of AI's capabilities and limits, how to choose useful applications, and how to check results. It combines awareness, practice on business tasks, and usage rules. Each team then knows which tasks to use AI for and how to check the result.
How long does it take for teams to adopt AI? +
The programme runs over 2 to 8 weeks depending on the teams involved. Workshops provide a chance to test initial uses; lasting adoption then depends on their usefulness, available tools, and management support. Follow-up at 1 and 3 months and the 6-month upskilling plan track progress without guaranteeing a uniform timeline or benefit.
Do participants need technical skills? +
No. The programme is adapted by role: workshops for managers and non-technical teams, others for technical professionals. Everyone leaves with tools configured for their role.
What is an internal AI champion? +
A team member who receives in-depth training and becomes the AI point person for their team. They help colleagues, flag blockers, and ensure continuity after the consulting engagement.
What happens in an AI enablement workshop? +
The workshop starts with a task and an expected outcome. A demonstration is followed by hands-on practice, then a review of the results and their limitations. An illustrative exercise is to draft a summary of a fictional document, check the information included, and identify omissions. Participants derive a reusable method and the checks to perform before sharing the output.
Should we choose a standalone course or an AI enablement programme? +
A standalone course suits an identified skill need involving a tool or practice. An enablement programme fits teams that need to build a shared understanding, experiment, and organise follow-up of actual use. If organisational priorities and prerequisites are still unclear, a maturity audit can help decide where to start.
What is the difference between AI awareness and AI enablement? +
Awareness informs: a talk or short session presents what AI can do, its limits, and its risks. Enablement changes practice: teams apply AI to their own tasks, adopt shared rules, and are followed up over time. Awareness is often the first step of an enablement programme, rarely an end in itself.
Does AI enablement include data literacy? +
To the extent AI use requires it, yes. Participants learn to qualify the data they give a tool: its origin, reliability, confidentiality level, and the rules that apply to it. A data governance programme, with its reference frameworks and owners, is a separate undertaking; the maturity audit helps determine whether it should come before enablement.
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