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    TCS is here to make a difference through technology.

    Leading the way in innovation for over 55 years, we build greater futures for businesses across multiple industries and 55 countries.

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      We’re in it for good, driving positive change for the benefit of all.

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      15 May 2025 TCS Recognized as One of the World’s Top 50 Brands by Kantar BrandZ; Brand Value Soars 28% YoY to $57.3Bn
      14 May 2025 TCS Partners with Khan Bank to Future-Proof its Operations, Enhance Customer Experience and Propel Innovation leveraging AI and ML
      12 May 2025 TCS Partners with Dhofar Insurance Company to Transform its Core Insurance Platform
      View all
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      02 May 2025 TCS Ranked Denmark’s #1 IT Service Provider for Customer Satisfaction in 2025
      11 Apr 2025 TCS Partners with Google Cloud to Accelerate AI-led Transformation in the Retail Sector
      01 Apr 2025 TCS Unveils the TCS Digital Twindex Report for Future-Ready Manufacturing
      View all
    • Analyst recognition

      Recent recognitions

      22 Apr 2025 TCS Ranked #6 Amongst Banking Technology Providers and Recognized as a Regional Leader across all Geographies by Everest Group
      17 Apr 2025 TCS BaNCS Named a Leader Among Wealth Management Products by Everest Group
      01 Apr 2025 TCS Positioned as a Leader in Worldwide Discrete Manufacturing Product Lifecycle Management Strategic Consulting Services and Systems Integration by IDC MarketScape
      View all
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    What we do
    • Overview Press tab for submenu items

      TCS is here to make a difference through technology.

      Leading the way in innovation for over 55 years, we build greater futures for businesses across multiple industries and 55 countries.

      Discover all solutions
    • Industries
      • Banking
      • Capital Markets
      • Consumer Packaged Goods and Distribution
      • Communications, Media, and Information Services
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      • TCS ERP on Cloud
      • ignio™
      • TCS iON™
      • TCS HOBS™
      • TCS Intelligent Urban Exchange™
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      • Quartz™ – The Smart Ledgers™
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  • Who we are
    • Overview Press tab for submenu items

      We’re in it for good, driving positive change for the benefit of all.

      Our expert, committed team put our shared beliefs into action – every day. Together, we combine innovation and collective knowledge to create the extraordinary.

      Discover the difference
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      Extraordinary expertise leads to remarkable results.

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      Want to be a global change-maker? Join our team.

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      Find the latest news about TCS in our Newsroom

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      Discover more
    • Press releases

      Recent Press releases

      15 May 2025 TCS Recognized as One of the World’s Top 50 Brands by Kantar BrandZ; Brand Value Soars 28% YoY to $57.3Bn
      14 May 2025 TCS Partners with Khan Bank to Future-Proof its Operations, Enhance Customer Experience and Propel Innovation leveraging AI and ML
      12 May 2025 TCS Partners with Dhofar Insurance Company to Transform its Core Insurance Platform
      View all
    • News alerts

      Recent News

      02 May 2025 TCS Ranked Denmark’s #1 IT Service Provider for Customer Satisfaction in 2025
      11 Apr 2025 TCS Partners with Google Cloud to Accelerate AI-led Transformation in the Retail Sector
      01 Apr 2025 TCS Unveils the TCS Digital Twindex Report for Future-Ready Manufacturing
      View all
    • Analyst recognition

      Recent recognitions

      22 Apr 2025 TCS Ranked #6 Amongst Banking Technology Providers and Recognized as a Regional Leader across all Geographies by Everest Group
      17 Apr 2025 TCS BaNCS Named a Leader Among Wealth Management Products by Everest Group
      01 Apr 2025 TCS Positioned as a Leader in Worldwide Discrete Manufacturing Product Lifecycle Management Strategic Consulting Services and Systems Integration by IDC MarketScape
      View all
    • Events

      Upcoming events

      11 Jun 2025 TCS and PTC Present the North America Leadership Forum 2025
      04 Jun 2025 Veeva R&D and Quality Summit: Developing Better Health Outcomes
      02 Jun 2025 Siemens Realize LIVE: Discussing Technology and Digital Transformation
      View all
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    • Overview Press tab for submenu items

      TCS works hand in hand with world-leading investors.

      Tata Consultancy Services Limited
      NSE:TCS
      INR
      Discover more FY24-25 debrief
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    TCS Worldwide
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    • Energy, Resources, and Utilities
    • White paper

    The transformative potential of AI for Energy

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    Industry

    Energy, Resources & Utilities This will open an overlay

    Rebalance the energy equation

    We work with energy, resources, and utility businesses to create a smart and sustainable future.
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     about Rebalance the energy equation
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    Related Insights
    Highlights: TCS at DISTRIBUTECH International® 2025
    Know about TCS’ role in this utilities industry event, where we showcased our energy sustainability solutions and hosted sessions on workforce safety and more.
    Events
    02 Jan 2025
    Leveraging Industry 4.0 Technologies for Zero Waste Manufacturing
    Industry 4.0 technologies can be utilized to improve resource efficiency, design zero waste manufacturing, and move towards a sustainable and circular economy.
    White Paper
    17 Oct 2023
    The MW Dispatch Platform: Accelerating NESO's Net-zero Future
    Learn how TCS helped NESO in its drive towards a zero-carbon grid and effectively manage the renewables generation to accelerate the UK’s net zero commitment.
    Case Studies
    16 Oct 2024

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    Shape the future with human-first AI

    AI, along with human creativity and strategic thinking, can redefine business. See how you can harness the power of AI to achieve scalable, sustainable success.
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     about Shape the future with human-first AI
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    Related Insights
    How AI and ML are Reimagining Corporate Governance
    Learn how TCS, in partnership with CGS, built an AI-fueled platform to enhance corporate governance assessments through automation and transform ESG compliance.
    White Paper
    07 Apr 2025
    TCS at NVIDIA GTC 2025
    TCS is a Diamond Sponsor of the NVIDIA GTC AI Conference | March 17-21, 2025, San Jose, California.
    Events
    28 Jan 2025
    TCS AI Spectrum for BFSI: Driving business decision with enterprise adoption of Composite AI
    Read how TCS AI Spectrum for BFSI, powered by Nvidia transforms AI application deployment at scale, ensuring compliance with safety and security regulations while delivering high accuracy and efficiency.
    Solution
    22 Oct 2024

    Highlights

    • As AI demonstrates immense potential to transform every industry, energy companies explore its use to spur innovation and grow revenue throughout the energy value chain— from exploration, and production to sales and marketing. 
    • A multidimensional strategy is key to making AI consumable for an enterprise-grade transformation and to deliver sustained performance.
    • While various aspects need to be considered during the initial stages of developing an AI model to drive a real-time operational AI effectively, access to a multitier architecture and integration to enterprise systems is essential for energy companies. 

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    The impact of AI Optimize or innovate AI in action Case in point A practical roadmap A balanced approach

    Reimagining every sector

    The energy industry is on the cusp of a major transformation, powered by artificial intelligence (AI).

    In the last few years, AI has demonstrated enormous potential to reimagine every industry, with a level of disruption to business models similar to earlier breakthrough technologies, such as smartphones a decade ago. 

    Per TCS’ AI for Business Study, 68% of senior executives surveyed in the energy and resources industry believe AI’s impact on their business model will be greater or equal to that of the internet, and 57% feel optimistic about its potential.

    The study also highlights that 89% of energy and resources executives are prioritizing AI to drive innovation at some level. About the same number of executives are focused on using AI to drive productivity. 

    Energy and resources executives understand the value of AI and how the combination of traditional AI, business intelligence, and generative AI (GenAI) will increase speed and effectiveness of working. The data generation capabilities of GenAI will help improve the quality of decisions and output of various tasks in the industry, accelerating operational transformation.

    Innovation as an objective

    The energy and resources industry focuses more on using AI to spur innovation and grow revenue than most other industries.

    On a 10-point scale between optimization and innovation, energy and resources executives averaged 6.90, compared to an average of 6.71 for all other industries, according to the AI for Business study. 

    82% of respondents at pacesetter—those organizations with stronger financial performance compared to other energy and resources companies in the survey—energy and resources organizations say they are primarily focused on innovation as an objective for AI implementations.

    AI for energy value chains

    The industry has been researching the use of AI for exploration, and production for a long time as well as looking at new use cases for transportation, sustainability initiatives, distribution, and marketing and sales.

    Exploration

    For oil and gas, AI solutions provide many potential benefits to the exploration process. GenAI-assisted well design is one of the leading emerging solutions, which promises more rapid and lower costs in drilling activities. AI tools are assisting geoscientists in complex interpretation tasks, which are, finding more resources in more places. 

    The current direction is to use AI to automate geoscience interpretation from seismic to well evaluation. Infusion of AI in the energy industry can improve reservoir simulation and modeling. By analyzing voluminous data, AI algorithms can generate accurate models of underground reservoirs, allowing energy professionals to make more informed decisions about drilling and development strategies. AI can enhance subsurface images captured through seismic surveys by creating 3D models and using fewer seismic data scans, avoiding the need for repeated data acquisitions.

    Production 

    Applying AI in upstream operations such as field operations and maintenance, drilling optimization, asset surveillance, and equipment recalibration enables an organization to reduce unplanned outages, increase uptime and minimize revenue loss. 

    Digital twin-infused AI enables predictive maintenance of on-field assets and equipment and helps ensure employee safety, including that of on-field technicians. In drilling, wells have already been drilled by drilling rigs, without human intervention. The limiting factor for the broader application of AI is the amount of data and energy required for a complete drilling operation using AI.

    GenAI/AI can address the challenges associated with navigating and analyzing vast volumes of data from disparate sources generated by different asset management systems, global information systems, monitoring systems and derive actionable insights related to drilling operations. In the process, GenAI-powered solutions can address the challenges associated across the entire drilling process lifecycle such as rig site preparation, drilling, cementing and testing, well completion, and fracking.

    Transportation

    AI-powered solutions can help optimize supply chains by autonomously monitoring assets like oil and gas pipelines distributed across geographies. It can enhance the functionalities of supervisory control and data acquisition (SCADA) systems by analyzing patterns of large volumes of operational data and providing actionable alerts to ensure adherence to industry-specific key performance indicators. 

    AI-assisted bots can be trained on images and videos of defects in pipelines such as corrosion and cracks, which can improve the speed and accuracy of defect detection and prediction in pipeline integrity processes. Layering AI models on top of traditional hydraulic simulation methods can significantly improve understanding of flow dynamics in pipelines to drive productivity, efficiency, and capacity utilization of assets. 

    Refining

    Refineries are growing increasingly sophisticated in pursuit of more efficient and sustainable operations. Control systems are becoming more capable and intelligent. AI can enable such sophistication with tools such as intelligent workbenches for safe and efficient operations. Machine learning applications are providing more current and detailed information on operations through applications such as AI-assisted mass balancing.

    Sales and marketing

    AI can enable energy consumers and industrial customers to analyze customer energy usage and buying patterns. Consumers benefit from intelligence at the point of sale. Industrial customers take advantage of customized B2B intelligent AI applications that help lower delivery costs. 

    38% of energy and resources executives are interested in using AI to enhance engagement with their market initiatives beyond chatbots, according to the TCS AI for Business Study.

    When it comes to customer engagement, while chatbots for sales and product support remain important to energy and resources companies, their use is being supplanted by other AI-driven means to accomplish these goals. 

    31% of respondents in the AI study say they are looking to use AI for more personalized interactions with their products and services while another 24% say that AI will help obtain insights to analyze customer behaviors and data. 

    Field service management is another area benefiting from this use case of AI for experience enhancement. AI equips those in customer-facing positions with intelligent troubleshooting support and contextual knowledge repositories. 

    Natural language models can guide customers through self-help processes that offer accurate customized responses, and personalized assistance can aid responses to more complex inquiries. AI can also help efficiently monitor and analyze social media data to identify potential adverse events and product quality complaints. 

    Most (63%) energy and resources executives believe AI will augment and enhance human capabilities—not replace them, with AI enabling people to focus on higher-value activities that require creativity, empathy, and strategic thinking. 

     

    What it takes

    A tailored fit and not a one-size-fits-all solution will ensure success.

    Transforming the potential of AI into sustained performance requires a multidimensional strategy and an enterprise architecture optimized for cost, quality, security, and privacy that also ensures compliance with regulations.

    Built on the principles of an industry-led, cloud-fueled, and ecosystem-enabled foundation, an AI strategy that considers the entire organization is required to make AI consumable for an enterprise-grade transformation. 
     

    Considerations for successful AI implementations


    These four principles underlay the path of AI potential to performance, a phased roadmap that builds upon and reinforces each stage—Assist, Augment, Transform (see figures below).

    This image shows the TCS path of AI potential to performance, a continuum that builds upon and reinforces each stage, which includes the assist, augment, and transform stages. In the assist stage, machines boost human capabilities; in the augment stage, humans and machines collaborate, and in the transform stage, machines elevate and humans innovate.

    Case in point

    Though A look at AI infusion into the daily activities of a field operator. 

    AI-powered field operator reimagines the process of field operations and maintenance in upstream operations of oil and gas organizations by enabling on-field technicians to collaborate across the enterprise for accessing work logs, SOPs, safety data, and troubleshooting drilling equipment.

    This helps in predictive maintenance of on-field equipment and assets, enabling an oil and gas organization to unlock business benefits such as achieving operational efficiency, reducing operating costs, preventing revenue loss due to unplanned outages.

    ai

    The illustration demonstrates how the AI-powered Field Operator can assist in the predictive maintenance of on-field equipment and assets. GenAI can help a field operator automate and transform various critical functions such as extracting critical information from production logs; alerting to maintenance activities and assisting in planning to providing the precise troubleshooting sets and repairs, extracting the required information pertaining to safety and regulations and presenting the information in an easy-to-understand manner and generating professional content enabling better collaboration.

    The multi-layered AI architecture

    How do energy organizations prepare themselves for an AI evolution? 

    Data is integral, as is a cloud foundation to scale and optimize AI outcomes. The data volumes required to drive a real-time operational AI effectively must be part of the infrastructure consideration. Further, energy organizations have unique regulatory, compliance, and data privacy requirements, which must be factored in during the initial stages of developing an AI model.

    Finally, developing a robust business case can be challenging when quantifying the business benefits and costs of AI is difficult. Energy consumption to train larger AI models is significant and must be evaluated in accordance with the business benefits. Any AI solution must start with a value-augmentation opportunity for the business; prioritizing top-down structures, rather than starting with technology adoption.

    For energy organizations to fully capitalize on AI’s potential, access to a multitier architecture and integration to enterprise systems is essential. The dimensions of AI applicability in the AI architecture for the energy value chain can be segmented into four layers.

    Figure 3: A high-level AI architecture for Energy

    This image shows a multi-layered, multi-tiered AI architecture and framework for energy use cases. The bottom-most layer predominantly enables the computing, network, and storage as a foundation together with public and hybrid clouds, and the existing enterprise IT and systems of record. The layer above enables foundational large language models (LLMs) for a variety of knowledge management use cases. The next layer constitutes AI-enabled purposive and contextual task agents that enable various moving parts of AI, such as fine-tuning of AI models on an ongoing basis, establishing the necessary guardrails for responsible and ethical implementation of AI, and a strong ML and LLM capability for continuous learning by the models. The final layer comprises task agents that seamlessly interact with each other with a human-in-the-loop for validation, verification, and disambiguation.

    Making AI pervasive

    A balanced approach is critical to success in AI adoption.

    AI is not plug-and-play technology with a one-size-fits-all strategy, and the findings from the energy industry executives reflect their varied approaches to AI. More than a third favor establishing an enterprise-wide AI strategy—but a little over a quarter are content to hold back and see how others in their industry apply the technology before making any major moves. 

    Only 3% of E&R executives in our survey say AI is a differentiating factor for business transformation and 23% have only just begun to explore AI. Most of the respondents say they have a long way to go to realize transformational outcomes.

    AI adoption needs to be pervasive across the organization and at three levels. 

    • Process operations level: Day-to-day operations, especially where knowledge extraction or synthesis is involved, are low-hanging fruits that demonstrate the success of AI infusion. Companies now accept that AI can rapidly improve both productivity and effectiveness of such processes. Enterprises are currently more active in AI infusion at this level, both to prove applicability via proof of concepts and in terms of targets for production deployments.
    •  LOB level: In a few advanced companies, lines of businesses (LOBs) are seeking opportunities to transform and create significant business value in activities driven by insights, for example, in areas like customer and partner experience. They have started integrating AI into operations at a business unit level.
    • Enterprise or strategy level: Top management and board initiatives intervene to define a company level strategy and roadmap for AI. 

    Enterprises have set up committees for this purpose, and the path to responsible AI adoption through an institutional, policy-driven approach is gaining pace. 

    The merging of reasoning and recognition intelligence into AI models offers tremendous potential to help companies reimagine entire value chains and transform the way they do business. A strategic, business-first approach is essential for successful AI implementations and enterprise-wide adoption. 

    EXECUTIVE CHAMPIONS

    Jan Johansson
    Industry Advisor, Upstream Oil and Gas

    Tom Franklin
    Industry Advisor

    Dipayan Mitra
    Client Partner

    Shalini Manchanda Mehtani
    Head of Industry Offerings, AI.cloud

    Dibyatanu Banerjee
    Lead ERU, Industry Offerings, AI.cloud 

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