Mastering Corporate AI Implementation

Your people are already using AI. What the organisation lacks is a way to tell which of those uses are worth scaling, which quietly waste money, and which create exposure. This course prepares you to be the person who answers that. You will learn to identify the processes where AI genuinely pays, to scope a project so that its cost and timeline are known before it, and to drive adoption through internal champions rather than a top-down rollout that stalls in the second month. Verification is treated as part of the design rather than as an afterthought, so that results can be checked before anyone relies on them, and the AI Act obligations of human supervision and traceability are mapped onto the workflows you propose. You leave with a roadmap for your own organisation, drafted during the day. The course also sets out the three roles an organisation needs in order to use AI seriously, working with assistants, automating processes, and working directly with data, so that you can see which of them your own organisation is missing and where to send people next.  

By the end of the training, participants will be able to:

• Identify the processes in your own organisation where AI adoption produces measurable value, and those where it does not

• Scope an AI project so that needs, timeline, cost and success criteria are defined before work begins

• Design workflows with verification and a human review step built in, not added later

• Establish an AI champion network that carries adoption across teams

• Map AI Act obligations, in particular human supervision and traceability, onto your own workflows

• Produce a corporate AI roadmap for the first ninety days

Contents (7 Hours):

1. Opportunities and constraints: what AI adoption looks like when it works, and the recognisable ways it fails.

2. Types of AI solution: what each costs, what each requires, and what each is actually for.

3. Identifying where AI adds value: process selection criteria (Exercise on participants' own processes).

4. Scoping: needs, timeline, cost, and defining what success will be measured against.

5. Designing for verification: building the checkpoint and the human review step into the workflow.

6. Governance in practice: AI Act obligations, ethics, confidentiality, and responsible use.

7. The AI champion network: selecting, equipping and supporting internal enablers (Exercise).

8. Building your roadmap: each participant drafts a ninety day plan for their own organisation.

Professionals who want to change not only their own work but how their organisation uses AI: managers, partners, project leaders, innovation officers, consultants, and the people who end up driving adoption inside their teams whether or not it is in their job description. No technical background required.