Divisional AI Project Manager

About Kingspan Data Solutions

Kingspan Data Solutions originated in the traditional commercial office sector for raised access flooring and more recently, are supporting the accelerated growth in the data centre industry. As one of the leading raised access flooring manufacturer, supplier and installers across US, Europe, Middle East and Australia, we have been involved in the delivery of a wide range of flooring solutions for some of the most prestigious buildings worldwide. Our Tate brand of data centre products has enabled us to support the leading technology and communication brands who rely on our team who are smart working, agile and offer solutions like none other. We continue to develop innovative products for use in commercial buildings and data centres, supported by our leading engineering, technical and specification team.

Our commitment to sustainability is a key focus area for our business and one we continue to evolve as we grow and in line with our Planet Passionate Strategy. It's an exciting time to join our business that is expanding at pace.

We are seeking an experienced AI Project Lead / Manager to play a critical role in shaping how AI drives efficiency and transformation across the business. This role will act as the bridge between business and technology, identifying and prioritising high-impact opportunities and translating them into scalable AI solutions delivered in partnership with engineering teams and 3rd party vendors.

The ideal candidate will bring a blend of hands-on AI experience, digital transformation expertise, and strong business acumen, with the ability to move seamlessly from problem definition through to delivery and adoption. You will be comfortable moving rapidly from idea to pilot, and from pilot to scaled deployment, ensuring momentum is maintained and value is realised quickly.

A key focus of the role is ensuring every initiative delivers measurable value and ROI, embedding AI into core workflows in a way that is practical, scalable, and aligned with business objectives.

Key Responsibilities:

AI Opportunity Identification & Pipeline Ownership

Work with functional leaders to surface high-value ideas and convert them into structured use cases.

Proactively identify opportunities to apply AI across business functions by analysing workflows, inefficiencies, and manual effort.

Build and maintain a prioritised pipeline of AI initiatives based on impact, feasibility, and ROI.

Continuously generate new ideas by combining business insight with emerging AI capabilities

Business-Technology Translation

Act as the primary interface between business stakeholders and engineering teams.

Translate business problems into clear AI requirements, use cases, and solution briefs.

Partner closely with AI engineers and 3rd party vendors who design and deploy the solutions.

Ensure alignment between intended business outcomes and technical delivery.

Project Leadership & Delivery

Lead the end-to-end lifecycle of AI projects:

Use-case definition

Business case & ROI modelling

Requirements gathering

Pilot design and rollout

Deployment coordination with engineering

Own project governance

Ensure delivery is focused on business value not just implementation.

Measurement, ROI & Value Realisation

Define success metrics upfront for every AI initiative (e.g. time saved, cost reduction, revenue uplift, accuracy improvements).

Build robust frameworks to measure:

Adoption and usage

Productivity gains

Financial impact / ROI

Track performance post-deployment and ensure benefits are realised and sustained.

Establish consistent reporting to demonstrate value and inform prioritisation.

Continuously refine use cases based on performance data.

Adoption, Change & Business Enablement

Drive adoption of AI solutions through structured rollout, training, and engagement.

Identify change impacts and ensure solutions are embedded into daily workflows.

Develop playbooks, usage guidance, and best-practice frameworks.

Support teams to integrate AI into how they work - not as a bolt-on.

Experimentation & Continuous Improvement

Maintain a pipeline of pilots and rapid experiments with new AI tools and approaches.

Work with engineers and 3rd party venfors to test, validate, and scale solutions quickly.

Stay up to date on emerging AI technologies and assess practical business applications.

Ensure a balance between experimentation and measurable outcomes.

Solution Standardisation & Global Rollout

Ensure solutions are documented, repeatable, and ready for deployment across regions.

Develop onboarding packs and training materials for scaling.

Maintain consistency while enabling regional adaptation.

Governance, AI Policy & IS Alignment

Ensure all AI initiatives are aligned to Group and Divisional AI governance, data policies, and IS standards from the outset.

Identify when IS engagement and approvals are required and plan accordingly.

Define data sensitivity, risk level, and compliance requirements at use-case stage.

Own coordination of IS engagement from a business and delivery perspective.

AI Steering Group

Own the end-to-end process for AI Steering Group submissions, including pilots and go-live approvals.

Define and coordinate all required inputs for decision-making, including:

Business case and ROI projections

Success metrics and measurement approach

Use-case definition and scope

Risk, governance, and compliance considerations

Consolidate inputs from engineering, IS, and business stakeholders into a clear, decision-ready pack.

Present AI initiatives to the Steering Group, clearly articulating:

Expected value and impact

Risks and mitigations

Readiness for pilot or scale

Own tracking of decisions, actions, and follow-ups from the Steering Group.

Ensure all initiatives meet approval before pilot and go-live.

Kingspan Data Solutions is an equal-opportunity employer. We encourage applications from candidates of all backgrounds and experiences.

Join us in our mission to make a difference through exceptional solutions.