AI and Innovation Manager – DNV Industrial Services (Remote)

Role Purpose

The AI & Innovation Manager drives the adoption development and commercialisation of AI and digital solutions across DNV Industrial Services.

The role ensures that innovation supports both:

• Operational excellence improving delivery efficiency scalability and data visibility
• Service differentiation and growth introducing AI and digital solutions as new revenue streams and value-adding services for clients

Key Responsibilities

1. AI & Digital Solutions for Service Growth

• Identify opportunities to introduce AI and digital solutions as new services or value-added offerings for clients.
• Support development of AI-enabled service concepts that strengthen DNV Industrial Services value proposition.
• Contribute to differentiating Industrial Services in the market through digital and data-driven offerings.
• Support go-to-market activities by helping translate innovation into practical customer value.

2. Innovation for Operational Excellence

• Drive adoption of AI and digital tools that improve delivery efficiency and scalability across global operations.
• Identify and prioritise opportunities to automate and streamline workflows such as planning reporting scheduling and document management.
• Support the transition towards data-driven and AI-enabled ways of working.

3. Cross-BA & Group Collaboration

• Maintain strong and continuous engagement with DNV Group AI Digital and Innovation teams.
• Actively collaborate with other DNV Business Areas to identify reusable solutions and joint offerings.
• Promote adoption of existing Group and BA solutions within Industrial Services.
• Identify opportunities for joint innovation and cross-selling.

4. Digital Platforms & Ecosystem

• Act as operational product owner for the developed digital platforms.
• Drive global adoption and continuous improvement aligned with business needs.
• Ensure integration with ERP and other digital systems supporting delivery.

5. Data & Analytics Enablement

• Promote the use of data dashboards and analytics in decision-making.
• Improve visibility of delivery performance and operational insight.
• Support development of scalable data foundations for future AI initiatives.