Chief Digital Officer

The Chief Digital & AI Officer will define and implement the AI and digital strategy for the roads, metro, rail and water businesses at Adani. The role calls for a visionary strategic orientation, the ability to drive change, execute for results, and lead cross-functional data and engineering teams.

The ideal candidate is an entrepreneurial, strategic and analytically driven leader with deep expertise in AI, Machine Learning, Generative AI and data architectures — and with genuine knowledge of infrastructure project delivery and O&M. The mandate is to use AI and digital to compress project schedules, protect EPC margin, improve safety on site, and maximise asset uptime, toll revenue integrity and water network efficiency, ushering in an AI-first operating model across the portfolio.

Education & Certification

• Bachelor's or Master's degree in Artificial Intelligence, Data Science, Computer Science, Information Technology, Engineering or Business Administration.
• Certifications in AI/ML (Deep Learning, MLOps), Digital Transformation or Cloud AI architectures (Azure/AWS/GCP) will be a strong advantage.
• Engineering background (Civil, Mechanical, Electrical or Electronics) is preferred given the project environment.
• 18–22 years of experience overall, with 6–8 years in a senior digital, AI or technology leadership role.

Roles and Responsibilities

• AI-Driven Strategy: define and implement a clearly defined AI and digital transformation agenda aligned with the business strategy across project development, construction and O&M.
• Operationalising AI: design, deploy and run AI-enhanced processes — schedule risk prediction, cost overrun early warning, computer vision for progress and safety, leak detection, traffic and revenue forecasting — with ownership of business outcomes.
• Project and Asset Intelligence: establish integrated digital project controls and BIM-based digital delivery so the CEO has one trusted view of every project, and O&M assets are managed on condition rather than calendar.
• Revenue and Network Integrity: deploy analytics for toll and ETC revenue assurance and for non-revenue water reduction across water assets.
• Cultural Transformation: inculcate a culture that is AI-first, data-led, agile and attuned to algorithmic thinking — including among site engineers, project directors and subcontractor teams.
• Thought Leadership & Governance: provide thought leadership to senior stakeholders on AI as a lever for growth, and establish robust AI governance, data privacy and ethical AI frameworks.
• Technology Advocacy: educate the business on emerging AI trends (GenAI, LLMs, Edge AI), opportunities, competitive threats and new algorithms that can differentiate delivery and operations.
• Modernisation & AI Infrastructure: make build-vs-buy decisions for AI models and data platforms; convert legacy systems into AI-ready applications through integrated, scalable data architectures (data lakes, MLOps pipelines) spanning ERP, project management, BIM, tolling, SCADA and HSE data.
• Portfolio & Partner Ecosystem: manage the AI/digital portfolio with shared accountability for value creation and ROI; grow internal capability and manage an ecosystem of AI vendors, EPC partners, ITS/tolling OEMs, hyperscalers and start-ups.
• Talent Development: build a world-class team of data scientists, ML engineers and digital experts, supported by embedded digital leads at project and asset level.
• Stakeholder Management: influence and align the CEO, CFO, project directors, concessioning authorities, lenders and partners to ensure timely delivery of AI solutions.

Sector Knowledge (Mandatory)

• Hands-on experience in highways, metro, rail or water infrastructure — with a developer/concessionaire, major EPC contractor, authority, or a firm serving them.
• Working knowledge of infrastructure commercial models — HAM, BOT (Toll and Annuity), TOT, EPC and O&M concessions — and how digital affects IRR and EPC margin.
• Comfort with project delivery mechanics: BOQ and quantity certification, RA bills, EOT and variation claims, independent engineer processes and milestone payments.
• Practical exposure to ITS/ATMS, tolling and FASTag ecosystems, SCADA for water and transit, and BIM common data environments.
• Familiarity with NHAI/MoRTH, metro rail authority and urban water reporting frameworks.

Behavioural Skills

• Visionary strategic orientation with a strong AI-first mindset.
• Change management and AI adoption expertise.
• Executive maturity, ethical AI advocacy and an analytical point of view.
• Entrepreneurial spirit and resilience.
• Collaborative, driven, and capable of demystifying complex AI concepts for business leaders.

Technical Skills

• Deep experience in defining an AI vision and data roadmap for large-scale businesses.
• Track record of working with CEOs and management teams to shape business requirements for algorithmic automation and digitalisation.
• Proficiency with ML algorithms, Generative AI applications, MLOps and familiarity with Python, R or equivalent.
• Experience setting up secure, enterprise-grade AI boundaries, data sovereignty controls and modern cloud/edge infrastructure.
• Ability to continuously scout for new AI breakthroughs, edge computing capabilities and emerging enterprise technology.
• Experience applying AI and computer vision across distributed field environments with limited connectivity and a subcontractor-heavy workforce.