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AI Enablement Lead

Pubblicato il 15-08-2026 - WSP Italy in Torino

What if you could do work that makes a difference?

At WSP, you can.

WSP is a leading engineering and professional services organisation, bringing together expertise across infrastructure, transport, environment, energy, property, and buildings.

Our people work with clients, partners, and communities to address complex challenges and create positive, lasting outcomes. With teams across Central Europe and around the world, we combine local knowledge with global experience to deliver practical and sustainable solutions.

Join a team where your skills, ideas, and experience can help deliver projects that create positive outcomes for communities, clients, and the environment. With opportunities to collaborate across disciplines, access global expertise, and contribute to meaningful work, you'll be supported to develop your career in a way that works for you.

The Opportunity – Build the Future with Us
As an AI Adoption, Experience and Training Lead,



you will lead the enablement side of AI adoption by working with peers to build and deliver training aligned to the overall AI change and communications plan, including targeted “in-the-flow” sessions, office hours, and train‑the‑trainer programs. You will also create the infrastructure that sustains adoption—peer learning communities, role‑based learning paths and assets, a governed knowledge base, and an AI champions network to scale support and reduce ongoing demand on help channels.

Your Impact
- Develop or procure trainings based on AI change and communications plan, working with providers as needed
- Create and moderate collaboration spaces for peer learning and support
- Schedule and deliver training as determined by the overall change enablement plan
- Deliver targeted, in‑the‑flow enablement for priority user groups (sessions, office hours, roadshows)
- Maintain office hours
- Create and publish how‑to guides, FAQs, and quick‑reference assets
- Design and maintain role‑based learning paths, self‑paced modules, in

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