Chief Digital Officer

The Chief Digital & AI Officer will define and implement the AI and digital strategy for the thermal generation 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 thermal power operations. The mandate is simple: use AI and digital to improve plant availability, lower heat rate and auxiliary power consumption, tighten the fuel chain and make plants safer, ushering in an AI-first operating model across the fleet.

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 (Mechanical, Electrical, Instrumentation or Power) is preferred given the plant 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 generation business strategy, with leadership commitment, resource allocation and disciplined execution.
• Operationalising AI: design, deploy and run AI-enhanced processes — predictive maintenance, combustion and mill optimisation, computer vision, autonomous operations — to drive efficiency, profitability and growth, with ownership of business outcomes.
• Fuel and Asset Intelligence: digitise the coal and ash value chain end to end and deploy AI blending and reconciliation advisories that protect generation economics.
• Cultural Transformation: inculcate a culture that is AI-first, data-led, agile and attuned to algorithmic thinking — including at the plant floor, with shift engineers and unit heads.
• 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 operations.
• Modernisation & AI Infrastructure: make build-vs-buy decisions for AI models and data platforms; convert legacy plant and enterprise systems into AI-ready applications through integrated, scalable data architectures (data lakes, MLOps pipelines) spanning DCS, SCADA, historian, CBM and ERP data.
• Cyber Security of OT: ensure secure AI and data boundaries across plant control environments, with segmentation and access governance appropriate to critical national infrastructure.
• 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, OEMs, hyperscalers and start-ups.
• Talent Development: build a world-class team of data scientists, ML engineers and digital experts, supported by digital champions at each station.
• Stakeholder Management: influence and align the CEO, CFO, plant heads, regulators and partners to ensure timely delivery of AI solutions.

Sector Knowledge (Mandatory)

• Hands-on experience in thermal power generation — with a utility/IPP, or in a senior role with an OEM, EPC or consulting firm serving thermal generators.
• Working knowledge of the thermal value chain: coal handling, milling, boiler and turbine operation, condenser and cooling, ash handling, FGD and grid evacuation.
• Comfort with generation metrics — heat rate, PLF/PAF, auxiliary power consumption, declared capacity, forced-outage rate — and the levers behind each.
• Practical exposure to DCS, SCADA, historians and condition-monitoring systems in multi-OEM plant environments.
• Familiarity with CEA, CERC/SERC, Grid-India scheduling and MoEFCC emission norms.

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 to industrial data — anomaly detection, remaining-useful-life, soft sensors and process optimisation — in live plant environments.