# Manager, Technology Planning & Governance at ADNOC

ADNOC is hiring a Manager, Technology Planning & Governance in Abu Dhabi, United Arab Emirates. Level rates it Works on AI ●●●○; you can [apply on ADNOC](https://jobsbylevel.com/go/bf50d267-c830-462e-95be-877313e423f3?utm_medium=ai-agent).

AI Level 3, AI centrality 65 out of 100. Abu Dhabi, United Arab Emirates.

## Details

- Company: [ADNOC](https://jobsbylevel.com/companies/adnoc)
- AI level: AI Level 3 (score 65 out of 100)
- Location: Abu Dhabi, United Arab Emirates
- Posted: October 22, 2026
- Apply: https://jobsbylevel.com/go/bf50d267-c830-462e-95be-877313e423f3?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=manager-technology-planning-governance-at-adnoc-1c25d2

## Prepare for this job

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## Description

Job Purpose The AI Transformation Manager leads the refinery AI transformation agenda by identifying, prioritizing, orchestrating, and embedding AI and data-driven initiatives that deliver measurable business value. The role acts as the bridge between business functions and technical teams, ensuring that AI opportunities are converted into practical, scalable, and value-generating solutions. The position drives the transformation pipeline across operations, maintenance, engineering, reliability, planning, energy, supply chain, Inspection and support functions by maintaining a robust use case portfolio, aligning stakeholders, enforcing delivery governance, and supporting adoption and scale-up. Key Accountabilities A. AI Transformation Strategy & Roadmap Lead the refinery AI transformation agenda in alignment with business priorities and enterprise digital strategy. Translate strategic objectives into a structured AI transformation roadmap and prioritized portfolio. Identify high-value opportunities for AI, analytics, automation, and intelligent decision support across refinery functions. Support the transition from isolated pilots into scalable deployments with repeatable value delivery. B. Use Case Identification & Prioritization Engage business stakeholders to identify pain points, opportunities, and transformation themes suitable for AI deployment. Evaluate opportunities using value, feasibility, data readiness, implementation effort, and risk criteria. Develop concept notes, business cases, initiative charters, KPIs, and expected-benefit logic for shortlisted opportunities. C. Cross-Functional Delivery Leadership Orchestrate end-to-end delivery of AI initiatives in coordination with operations, maintenance, engineering, Digital teams. Track milestones, manage interdependencies, remove barriers, and escalate issues when required. Ensure initiatives progress through idea assessment, design, pilot, deployment, adoption, and scale-up. D. Value Delivery & Performance Management Define expected business outcomes and benefit-realization logic for each initiative. Monitor progress against value targets such as throughput, yield, energy, reliability, maintenance cost avoidance, HSE improvement, labor productivity, or margin uplift. Provide clear leadership reporting on initiative health, delivered value, forecast value, and implementation status. E. Change Management & Adoption Drive stakeholder readiness and business alignment for AI-enabled changes in workflows, decisions, and operating models. Coordinate communication, awareness, training, and adoption actions required for sustained use. Help embed AI solutions into day-to-day operating and management routines rather than leaving them as stand-alone tools. F. Governance, Standards & Risk Management Apply required AI governance, risk, compliance, and control processes for AI initiatives. Coordinate with cybersecurity, data governance, architecture, legal, procurement, and HSE stakeholders as needed. Support responsible, safe, and business-aligned use of AI in refinery environments. G. External Collaboration & Vendor Management Support development of scopes of work, technical and business requirements, proposal evaluation, and vendor delivery monitoring. Ensure external partners remain aligned with refinery needs, data constraints, operational realities, and value expectations. Role Interfaces and Delivery Context Internal Interfaces Refinery operations; maintenance and reliability; process engineering / technical services; planning and economics; energy management; HSE; IT / OT / cybersecurity; finance; procurement; and leadership forums. External Interfaces Refinery operations; maintenance and reliability; process engineering / technical services; planning and economics; energy management; HSE; IT / OT / cybersecurity; finance; procurement; and leadership forums. Typical Initiative Themes Process optimization, AI-enabled decision support, predictive analytics, operator

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