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    TCS is here to make a difference through technology.

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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
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      23 Apr 2025 TCS Partners with Google Cloud on Agent-to-Agent Interoperability Protocol to Drive Future-Ready Enterprises
      11 Apr 2025 TCS Partners with Google Cloud to Accelerate AI-led Transformation in the Retail Sector
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      01 Apr 2025 TCS Positioned as a Leader in Worldwide Discrete Manufacturing Product Lifecycle Management Strategic Consulting Services and Systems Integration by IDC MarketScape
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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.

      Discover all solutions
    • Industries
      • Banking
      • Capital Markets
      • Consumer Packaged Goods and Distribution
      • Communications, Media, and Information Services
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      • ignio™
      • TCS iON™
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      • Quartz™ – The Smart Ledgers™
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  • Who we are
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      We deliver excellence and create value for customers and communities.

      Our expert, committed team put our shared values into action – every day. With the best talent and the latest technology we help customers turn complexity into opportunities and create meaningful change.

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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
      23 Apr 2025 TCS Partners with Google Cloud on Agent-to-Agent Interoperability Protocol to Drive Future-Ready Enterprises
      11 Apr 2025 TCS Partners with Google Cloud to Accelerate AI-led Transformation in the Retail Sector
      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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      TCS works hand in hand with world-leading investors.

      Tata Consultancy Services Limited
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      Discover more FY24-25 debrief
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    TCS Worldwide
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    • Manufacturing
    • White Paper

    Next generation manufacturing enterprise: powered by GenAI

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    Manufacturing This will open an overlay

    Future-Ready Manufacturing: Partnering in your journey to a sustainable manufacturing enterprise

    As the manufacturing value chain faces disruptions, know how TCS’ framework drives innovation and AI technology in manufacturing for better agility and growth.
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     about Future-Ready Manufacturing: Partnering in your journey to a sustainable manufacturing enterprise
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    02 Jun 2025

    Highlights

    • There is a tremendous potential for GenAI opportunities in the manufacturing sector – from copilots for plant operators and product design to supply chain optimization and net zero goals.
    • For manufacturers to fully exploit the potential of AI, it is essential to have access to a multitier architecture optimized for cost, quality, security, and privacy.
    • Built on the principles of an industry-led, data-fueled, and ecosystem-enabled foundation, we offer an ‘enterprise-wise’ AI approach designed to make GenAI consumable for an enterprise-grade transformation.

    On this page

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    The architecture inpage
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    A new era Push the boundaries Our GenAI vision A use case The architecture The TCS advantage

    Transformative potential

    The excitement of generative artificial intelligence (GenAI) going mainstream has prompted a sense of urgency to tap into its immense potential.

    The opportunities for the manufacturing sector are abundant—from copilots for product design and maintenance to supply chain optimization and net zero goal realization.

    But while many discussions start and end with enhanced productivity, an even greater value lies in the ability to unlock and democratize knowledge. Reimagining ways of working and augmenting humans with advanced knowledge capabilities can transform tacit knowledge into elite decision making and high-performing innovation superstructures.

    Creating a difference

    Many manufacturers are already experimenting with AI technologies, to a greater or a lesser degree.

    In the TCS 2023 Global Cloud Study, nearly three-fourths (73%) of manufacturing respondents said they increased investments in artificial intelligence (AI) and machine learning (ML) in the past one to two years and more than three-fourths (76%) said they planned to invest in AI and ML in the next one to two years.

    Among other use cases for GenAI, manufacturers are currently exploring:

    • Product design and development: GenAI can accelerate product development and time to market by generating requirements and concepts based on market analysis and customer buying patterns. In the design stage, engineers can model and test prototypes, sifting through parameters such as weight, costs, and durability to reach the best possible outcomes.
    • Supply chain management: Production planners and supply chain analysts can create comprehensive models and simulations of demand and supply, creating and re-creating endless inventory scenarios to optimize carrying costs and availability. Visual layouts can help determine efficient storage and provide alternate inventory storage designs.
    • Plant operations: Orchestrating the processes and workflows contained within a single plant is challenging, let alone synchronizing multiple facilities across the globe. GenAI lets operators and planners identify more efficient processes, layouts and schedules, and allocate resources, such as machines, labor, and materials to minimize bottlenecks and reduce waste. Alerts and sensors can help detect potential errors and failures in real time to improve quality control.
    • Sales and marketing: From cold calls to close, GenAI can help elevate employee performance across the sales cycle. Dynamic pricing and offers, hyper-personalization, and more accurate lead qualification can help achieve timely, cost-effective sales and marketing processes. Contract generation and intelligent copilots can efficiently guide sales teams through closing processes.
    • Distribution: Even the simplest fulfillment process can contain dozens of logistical details around transportation routes and schedules. GenAI can help sift through dynamic factors like weather, fuel prices, river capacity and traffic conditions to minimize costs and carbon emissions, automatically adjusting based on demand forecast and unexpected delays. 
    • After-sales service: GenAI can augment those in customer-facing positions by arming them with intelligent troubleshooting support and contextual knowledge repositories. Natural language models can guide customers through self-help processes that offer accurate customized responses, enabling staff to focus on more complex inquiries.

    It is important to note that in all these examples, intelligent technologies are a copilot for humans, not a replacement. GenAI will augment humans in their day-to-day work, empowering them to make consistently better decisions and truly innovate in a way that transforms the entire organization.

    In Figure 1, we list these six focus areas, along with relevant use cases and target personas, and the potential benefits GenAI can bring to each.

    The image shows a table of six focus areas for product design and development, supply chain management, manufacturing and operations, sales and marketing, and aftersales services, and also includes relevant use cases and target personas, and the potential benefits GenAI will bring to each.

    The image shows a table of six focus areas for product design and development, supply chain management, manufacturing and operations, sales and marketing, and aftersales services, and also includes relevant use cases and target personas, and the potential benefits GenAI will bring to each.

    Figure1

    Focus areas for GenAI

    Close
    Figure1
    The image shows a table of six focus areas for product design and development, supply chain management, manufacturing and operations, sales and marketing, and aftersales services, and also includes relevant use cases and target personas, and the potential benefits GenAI will bring to each.

    Our vision

    Transforming the potential of GenAI into sustained performance is not a one-size-fits-all solution.

    It requires a multidimensional strategy and an enterprise architecture optimized for cost, quality, security, and privacy. In short, it requires a tailored fit—not a one-size-fits-all solution.

    With extensive experience in working with hundreds of global companies, we take a best-practice approach to help manufacturers master the delicate balance of opportunity and risk to ensure successful GenAI outcomes.

    Built on the principles of an industry-led, data-fueled, and ecosystem-enabled foundation, we offer an ‘enterprise-wise’ AI approach designed to make GenAI consumable for an enterprise-grade transformation.

    Figure 2 shows the four principles of an AI approach, which includes industry-led, data-fueled and ecosystem-enabled principles, and a culminating fourth principle of an enterprise-wise approach.

    Figure 2 shows the four principles of an AI approach, which includes industry-led, data-fueled and ecosystem-enabled principles, and a culminating fourth principle of an enterprise-wise approach.

    Figure2

    “Enterprise-wise” AI adoption approach

    Close
    Figure2
    Figure 2 shows the four principles of an AI approach, which includes industry-led, data-fueled and ecosystem-enabled principles, and a culminating fourth principle of an enterprise-wise approach.

    These four principles underlay the TCS path of AI potential to performance, a continuum that builds upon and reinforces each stage: assist, augment, and transform (see Figure 3).

    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.

    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.

    Figure3

    TCS AI Continuum – Manufacturing

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    Figure3
    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.
    The image shows an AI evolution in action along the continuum of the assist, augment, and transform stages.

    The image shows an AI evolution in action along the continuum of the assist, augment, and transform stages.

    Figure4

    An AI evolution in action

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    Figure4
    The image shows an AI evolution in action along the continuum of the assist, augment, and transform stages.

    GenAI in action – a manufacturing use case

    We empower manufacturers to jump-start their GenAI-led business reimagination journey.

    For example, TCS infuses GenAI into the daily activities of plant operators as a co-pilot template to help solve pressing business challenges like troubleshooting and maintenance.

    This image shows the daily activities of a plant operator persona and how those activities vary when looked at within a current state and then a future state when GenAI is infused into those activities.

    This image shows the daily activities of a plant operator persona and how those activities vary when looked at within a current state and then a future state when GenAI is infused into those activities.

    Figure5

    Case in point: GenAl infusion into the daily activities of the plant operator

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    Figure5
    This image shows the daily activities of a plant operator persona and how those activities vary when looked at within a current state and then a future state when GenAI is infused into those activities.

    *Potential benefits based on TCS' experiential and contextual knowledge, domain expertise and internal model estimates; actual results may vary.

    Navigating the complexity

    How does a manufacturer prepare itself for an AI evolution?

    The design of an AI solution must start with a value-augmentation opportunity for business; prioritizing top-down structures, rather than starting with technology adoption. Further, it is critical to make the model safe. Manufacturers need to establish a governance model for information security, regulatory compliance, and bias mitigation.

    A multi-layered architecture: TCS AI architecture for manufacturers

    For manufacturers to fully exploit the potential of AI, it is essential to have access to a multitier architecture and integration to enterprise systems. The dimensions of AI applicability in the AI architecture in manufacturing can be segmented into four layers, as shown in Figure 6.

    This image shows a multi-layered, multi-tiered AI architecture and framework for manufacturers.

    This image shows a multi-layered, multi-tiered AI architecture and framework for manufacturers. The bottom-most layer predominantly enables the compute, network and storage as a foundation coupled with public and hybrid clouds, and the existing enterprise IT and manufacturing systems of record such as enterprise resource planning (ERP) systems, manufacturing execution system (MES), and product lifecycle management (PLM). The layer above enables foundational large language models (LLMs) for a variety of knowledge management use cases—auto or aero LLMs, sourcing and procurement data lake, and warranty analytics and insights embedded in a frictionless DevSecOps ecosystem. 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 interact with each other in a seamless fashion with a human-in-the-loop for validation, verification, and disambiguation.

    Figure6

    TCS AI Architecture for Manufacturers

    Close
    Figure6
    This image shows a multi-layered, multi-tiered AI architecture and framework for manufacturers.
    • The bottom-most layer predominantly enables the compute, network, and storage as a foundation, coupled with public and hybrid clouds, and the existing enterprise IT and manufacturing systems of record such as enterprise resource planning (ERP) systems, manufacturing execution system (MES), and product lifecycle management (PLM).
    • The layer above enables foundational large language models (LLMs) for a variety of knowledge management use cases—auto or aero LLMs, sourcing and procurement data lake, and warranty analytics and insights embedded in a frictionless DevSecOps ecosystem.
    • 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 interact with each other in a seamless fashion with a human-in-the-loop for validation, verification, and disambiguation.

    The TCS advantage

    Our strong partnerships help manufacturing organizations successfully navigate GenAI transformations to drive sustained performance.

    Deep domain and contextual expertise TCS has a vast expert pool of industry experts with well-established experience in multiple manufacturing functions, from plant operators, to dealer managers to production planners, to help identify, build and support the latest and fittest solutions and technologies for clients.

    Cross-industry experience: Today’s businesses are more interconnected than ever before and need cross-industry expertise and leading practices. Working with customers across industries such as travel and transportation, retail and insurance brings an end-to-end holistic view of enterprise business functions and knowhow.

    Enterprise AI at scale: Our 3P strategy – patents, products, and platforms – and more than 150,000 trained associates help us enable enterprise AI at scale.

    Partner ecosystems: Scale and accelerate the path to value through a network of joint solutions and established hyperscaler partnerships, an elaborate TCS COIN™ ecosystem, and co-innovation facilities such as TCS Pace Port™.

    Evolving solutions: To help accelerate the journey, TCS leverages its contextual knowledge and expertise to enable multiple purpose-built solutions for manufacturers that incorporate GenAI technologies.

    EXECUTIVE CHAMPIONS

    Anupam Singhal
    President, Manufacturing, TCS

    Nidhi Srivastava
    Vice President and Head of offerings, AI.Cloud, TCS

    Subhash Sakorikar
    Chief Strategy and Transformation Officer,
    Manufacturing, Energy, and Resources, TCS

    Siva Ganesan
    Senior Vice President and Head, AI.Cloud, TCS

    Naresh Mehta
    Chief Technology Officer, Manufacturing, TCS

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