ONGC.
India's largest oil and gas producer is investing in artificial intelligence across its operations and is drawing on external research expertise to inform how these technologies are adopted.
India's energy sector is entering a defining phase in its adoption of artificial intelligence, and Oil and Natural Gas Corporation (ONGC), the country's largest integrated oil and gas enterprise, is among those moving most decisively. In early 2026 the company committed to a major digital transformation programme powered by artificial intelligence, valued at â¹125 crore and spanning dozens of locations nationwide, with predictive maintenance and intelligent automation among its central pillars. Its engineering and technology teams have separately been developing artificial intelligence and machine learning models for anomaly detection, failure forecasting and real time operational decision support.
In line with this momentum, ONGC convened a focused technical session on the application of artificial intelligence in the oil and gas industry, with particular emphasis on predictive maintenance and digital transformation. The session was led by technology leader and researcher Dr. Satyasri Akula, whose work centres on the practical integration of intelligent systems into complex industrial operations.
A Session of Practical Depth
Held on 24 April 2026 at ONGC's Mumbai Regional Office, the session brought together 124 participants, comprising internal audit professionals, artificial intelligence and technology practitioners, and business stakeholders from across the organisation.
Rather than offering a broad overview, the discussion concentrated on concrete applications relevant to a large operator: intelligent asset monitoring, equipment reliability, early anomaly detection, and the governance frameworks required to deploy these systems responsibly. A central theme was the transition from reactive and scheduled maintenance toward predictive approaches, in which models continuously interpret signals from temperature, pressure and vibration sensors to anticipate failures before they occur.
Akula presented this evolution not as a replacement for human expertise but as a means of strengthening it, with machine learning monitoring complex systems at scale while engineers and auditors contribute the context and judgement that operational decisions demand. Participants described the engagement as both insightful and immediately relevant, noting the clarity with which advanced technical concepts were connected to the day-to-day realities of asset management and operational risk.
Potential Value for ONGC
The case for the approaches discussed is increasingly well established. Published industry research, including analysis by McKinsey, associates predictive maintenance driven by artificial intelligence with reductions in unplanned equipment downtime in the range of 30 to 40 percent, and maintenance cost reductions of 10 to 30 percent, alongside measurable improvements in asset utilisation.
For an organisation of ONGC's scale, where a single day of unplanned downtime on critical equipment can carry considerable cost, the integration of the research and methods presented by Akula could translate into meaningful operational and financial value. The potential gains include fewer unplanned failures, more efficient maintenance scheduling, improved equipment availability, and stronger alignment between operational data and decision making. While such figures reflect industry benchmarks rather than guaranteed outcomes, they illustrate why predictive maintenance features so prominently in ONGC's current digital agenda, and why the methods explored in the session hold particular significance for the organisation's long-term objectives.
An Ongoing Conversation
The session highlighted a shared recognition: the integration of AI in oil and gas is no longer a distant possibility, but an evolving reality shaped by continuous learning and collaboration.
For Akula, the experience underscored the value of engaging directly with industry professionals, where ideas are not just presented, but examined, questioned, and refined through dialogue.
In many ways, the interaction reflected the beginning of deeper, ongoing conversations on how intelligent systems can reshape the future of energy operations.
Dr. Satyasri Akula is a technology leader, researcher and author working at the intersection of artificial intelligence, digital transformation and strategic management. With over a decade of experience in enterprise technology and digital leadership, she has been actively involved in driving large scale transformation initiatives across industries. Her doctoral research focuses on the impact of digital innovation and adaptive strategy on organisational growth, and her work spans intelligent decision systems, business strategy and emerging technologies. She is associated with organisations including the IEEE and is the author of "Leadership: The Art of Inspiring Others." Her work continues to focus on enabling organisations to navigate complexity through innovation, data driven thinking and leadership grounded in purpose.
