IT Head of Digital & AI Acceleration Factory

Core Accountabilities

1. Define and Lead the Transformation Agenda

- Translate enterprise strategy into a clear Digital & AI transformation vision, roadmap, and investment portfolio.

- Identify and prioritize the highest-value opportunities for AI, automation, data, and digital transformation.

- Establish the transformation principles, ambition, and execution model required to scale beyond individual use cases.

- Act as a senior thought partner to business and functional leaders on how AI and digital technologies can fundamentally reshape their operating models.

2. Build the Digital & AI Acceleration Factory

- Establish and lead a scalable Digital & AI Acceleration Factory / AI CoE operating model.

- Create the mechanisms to move opportunities rapidly from ideation → experimentation → proof of value → industrialization → enterprise scale.

- Build the right combination of internal capabilities, strategic partners, and technology platforms.

- Establish reusable capabilities, assets, patterns, and methodologies to accelerate delivery and reduce duplication.

3. Drive Business Transformation and Value Realization

- Own the realization of measurable business outcomes from the Digital & AI portfolio.

- Lead end-to-end process re-engineering , using AI, automation, data, and digital technologies to fundamentally improve how work gets done.

- Establish clear value metrics and benefits realization for every major transformation initiative.

- Focus on outcomes such as productivity, cost efficiency, quality, cycle time, employee experience, and business agility—not simply technology deployment.

- Ensure successful pilots are systematically converted into scaled, sustainable business capabilities.

4. Build the Transformation Organization

- Define and build the organization, talent, and capabilities required to execute the transformation agenda.

- Establish multidisciplinary teams spanning transformation, product, engineering, AI/ML, data, automation, architecture, and change management.

- Develop a forward-deployment model that embeds transformation capability close to the business.

- Build a high-performance culture characterized by speed, experimentation, accountability, reuse, and measurable outcomes.

5. Orchestrate Business and Technology

- Establish an integrated operating model across Business, Digital & AI, Cloud, Data, Cybersecurity, Infrastructure, Architecture, and other technology functions.

- Partner with functional leaders, who own the business “what” and “why,” while the transformation organization provides the capabilities and execution engine.

- Work closely with the Transformation Office / PMO to align the Digital & AI portfolio with broader enterprise transformation priorities.

- Create strong executive alignment and remove organizational barriers to transformation.

6. Establish the AI and Digital Governance Model

- Define the governance model required to scale AI responsibly and economically.

- Establish standards for architecture, platforms, data, AI, security, privacy, model management, and responsible AI.

- Prevent uncontrolled technology proliferation while enabling innovation and speed.

- Embed governance, risk management, cybersecurity, and compliance throughout the transformation lifecycle.

- Ensure the organization is prepared to meet evolving AI regulatory and responsible-use requirements.

7. Create a Scalable Economic Model

- Establish a transparent investment and funding model aligned to business value.

- Ensure Digital & AI resources and investments are connected to measurable outcomes and business ownership.

- Drive continuous optimization of technology consumption, partner spend, platforms, and engineering capacity.

- Balance speed of innovation with disciplined capital allocation and sustainable economics.

8. Scale Transformation Across the Enterprise

- Establish reference implementations in priority functions and use them as models for broader enterprise adoption.

- Develop a repeatable approach for scaling successful solutions across functions, geographies, and business units.

- Drive organizational adoption, change management, and workforce enablement alongside technology implementation.

- Build enterprise AI fluency and transformation capability so that the organization becomes progressively less dependent on individual projects or external partners.

What will you gain?

It’s stimulating work in a supportive and diverse team environment. You’ll work with inspiring and passionate people. We’ll equip you with new capabilities. You can enrol in the ArcelorMittal University and mentoring programmes to develop new skills, knowledge, and fresh perspectives. You also have unlimited access to the ArcelorMittal Learning Platform to boost your development.

What are we looking for?

These are the things we look for. Don’t be put off if you can’t tick every box.

- Master’s degree (Computer Science, Engineering, Data / AI or related)

- 15+ years of experience

- Previous experience in Senior level position

- Strong relationship with business partners

- Proven track record building and running an AI / Digital transformation

How We Recruit

We are committed to building an inclusive organisation where everyone feels supported and valued. We need people with all sorts of backgrounds, experiences, perspectives, and personalities to help us decarbonise the life of steel. Every person who applies to join ArcelorMittal receives equal employment opportunities, regardless of ethnicity, gender, socioeconomic background, sexual orientation, age, disability, and any other protected status.

This is a fantastic opportunity to grow and develop. You will have the satisfaction of starting and completing projects that will make a tangible difference to people, communities, and planet.

If this interests you, we’d love to talk.