Services
IoT and Digital Engineering
Bringing Together IoT and Digital Engineering to Create Rich Experiences
Highlights
- Industry leaders can unlock the power of a new and smarter internet of things (IoT) as four evolving tech mega trends converge during the next few years.
- The next generation of IoT will empower leaders to drive transformative growth through the convergence of software-enabled things, digital twins, artificial intelligence (AI) and generative AI (GenAI), and edge-to-cloud computing with 5G connectivity.
- From autonomous journeys to factories of the future, servitization, energy transitions, and sustainability by design, the deployment possibilities across industries are wide-ranging.
- Businesses can create new revenue generation opportunities with product-as-a-service offerings bound by digital threads of intelligence across their life cycles.
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Toward servitization
Most industrial, manufacturing, asset-heavy, and engineering-oriented value chain leaders are focused on digital-led transformation, and we believe future leaders will be those who can harness next-gen IoT, AI, and related technologies.
The role of IoT is becoming increasingly integral to the evolution of new business and operating models. Businesses are therefore focused on driving value creation and efficient growth through IoT-led digital transformation and engineering innovations. By doing so, they can boost their overall revenue potential in the market while growing their wallet share among existing customers.
From transportation and manufacturing to healthcare, energy, and supply chains, industry leaders are reimagining their businesses using IoT and other digital technologies to create efficiently connected, cognitive, and intelligent value chains. These value chains are geared toward servitization by seamlessly integrating products with services. There is a growing need to transform business operations toward this end by establishing traceability across the as-designed, as-manufactured, as-in use, and as-serviced product management life cycle stages. By deploying a product-as-a-service (PaaS) model with end-to-end life cycle traceability, businesses can efficiently and effectively expand, manage, and continuously enhance their PaaS offerings to drive new value and growth.
Looking forward, a technology revolution can catapult IoT-led transformations with advanced levels of capabilities. A connected future will effectively open the door to new collaborative development possibilities for intelligent and sustainable-by-design enterprises and their ecosystem partners. Business heads of research and development, engineering, manufacturing, supply chain, and sustainability will want to keep a close eye on the four converging tech mega trends of software-enabled things, digital twins, AI and GenAI, and edge-to-cloud computing with 5G connectivity. By doing so, they will be better prepared to seize a competitive edge.
A paradigm shift
Technology-forward businesses that embrace change with an IoT and engineering innovation mindset will be in the best position to seize new business growth opportunities.
The long-term outlook for the enterprise IoT market is continued growth. According to IoT Analytics research, the size of the enterprise IoT market was $269 billion in 2023 with spending indicating a growth rate recovery beginning in 2025 and a CAGR of 15% estimated until 2030.
TCS sees the rapid evolution of software-enabled things, digital twins, AI and GenAI, and seamless edge-to-cloud computing with 5G connectivity as significantly influencing digitalization and contributing to continued growth for businesses during the next few years. We expect a major shift in the business landscape to occur with new opportunities for transformative growth through the convergence of these technologies:
- Software-enabled things: A decade ago, this technology consisted of physical products which were hardwired. Today, the behavior of those products is increasingly controlled through software.
New cars sold today, for instance, generally come loaded with software, but certain features are only visible or enabled if a buyer opts to pay for them. The behavior of a vehicle is, therefore, determined based on changes applied within the software configuration rather than the physical hardware. Another example is readily apparent in our use of everyday consumer appliances and electronics—from smart coffee makers and refrigerators to lights and TVs. Today, we can remotely operate and monitor their use from our mobile phones. Such conveniences, which were once a novelty, are now part of our daily life.
Digital twins: We believe that we have the data needed to digitally replicate potentially any physical product, facility, or process in a virtual world. In effect, the technology is evolving as a “digital twin of everything.” Through today’s advanced data-centric capabilities, the technology can now be used to create a complete and exact replica of a product, as well as the production facility where it is made and end-to-end supply chain processes.
For instance, we can visualize, simulate, and test an automotive or airplane engine in the virtual world before even releasing it in the physical world. Moreover, we can operate it remotely because it is software-enabled. All this is now possible with the technology becoming deeply ingrained in organizations as they scale on their transformation journeys. This level of technological advancement has been enabled by an economic model that clearly shows declining cost points.
AI and GenAI: IoT has thrived through its ability to access real-time data-driven insights and predictive analytics using traditional AI. There is an abundance of available data with hyper-connected products, processes, and systems, and the potential for also leveraging contextual information is therefore increasing exponentially. You can now implement a GenAI application with a chatbot interface on top of data to access contextual information across an enterprise. These developments enable more effective and higher-end deployments of AI such as those used for robotics in industrial settings.
45% of executives surveyed believe up to one-half of their employees will be using GenAI daily in three years.
Effectively serving as digital assistants to employees, GenAI tools can also be used to facilitate informed decision making with personalized knowledge augmentation capabilities (learn more about becoming a knowledge-driven enterprise). For instance, you can query a system about optimal points of operation based on historical data or the standard deviation of errors in assessing whether to continue production. Based on the global TCS AI for Business Study Key Findings Report, 45% of CEOs and other senior execs believe up to one-half of their employees will be using GenAI daily in 3 years. This anticipated adoption, however, necessitates an integration of the emerging wave of GenAI capabilities with more established industrial AI and rapidly maturing computer vision capabilities with the IoT capabilities.
4. Edge-to-cloud computing with 5G connectivity: Technology advancements in 5G (and with 6G on the horizon) are enabling better bandwidth, faster speeds, and more cost-efficient management in driving this modern computing paradigm. The ability to process data at the device edge or cloud edge, virtually from any IoT-powered device or industrial equipment with seamless integration to the cloud, enables real-time decision-making capabilities.
Tech mega trends converge
Businesses will have the opportunity to reimagine their value chains through technology convergence, deploying new connect-in-context, predictive, and self-healing capabilities.
While technological convergence will act as a catalyst for change, TCS foresees some industries proactively embracing the evolving trends and leading their markets at greater speed. Industry leaders will create systems, processes, and products based on an advanced set of technology capabilities designed to boost both operational efficiencies and effectiveness.
By connecting in context, IoT networks will become smarter, enabling the right information to be received at the right place and time. They will have the ability to predict future events and outcomes by analyzing and identifying trends based on historical and contextual data in combination with unstructured data. Using GenAI, various forms of unstructured data may also be analyzed¾from sensor and computer vision data sources to knowledge gleaned through logs and books. Equipped with self-healing adaptive tenets, next-gen systems will autonomously detect and fix problems themselves.
Figure 1: Technology convergence is creating new IoT opportunities
The future of IoT possibilities can be illustrated through five strategic deployments:
Autonomous journeys: In the new age of self-driving cars, technology and innovation are converging to reimagine journeys with improved navigation capabilities and safety in preventing collisions. The cars must be able to communicate with each other and make split-second decisions. Advancements in edge computing will effectively eliminate the issue of latency by processing data between cars in real time at the source. This real-time data processing capability applies not only to a mobility context but also factory operations and all forms of software-defined products.
Factory of the future: The manufacturing landscape is witnessing a major shift where connectivity and data are fundamentally changing how factories operate for overall increased efficiency and productivity. Enabled with digital intelligence and neural processing capabilities, smart and connected plant operations will essentially think, sense, and act. They will respond and innovate with greater agility based on evolving market demands, supply chain signals, and personalized product configurations while optimizing production runs with modernized and sustainable operations.
Servitization: Connected service ecosystems will emerge through the seamless integration of solution and software platform providers with product manufacturers across the value chain. The focus is on delivering personalized value in addressing end-user customer needs through pay-per-use or PaaS models. For instance, smart health services and devices will enable the delivery of more personalized care options with remote and self-monitoring capabilities to help people manage various conditions and improve their well-being.
Energy transition: Energy resource consumption and emission patterns among global organizations are rather complex and unpredictable. By combining the use of IoT, edge, and AI-based analytics, businesses will have the data-driven insights needed to build greener value chains and progress their energy efficiency and carbon neutrality goals. Real-time tradeoffs between cost and carbon footprint print, carbon trading, and visibility into the full value chain for carbon intensity will lead to the evolution of an open internet kind of platform for distributed energy exchange.
Sustainability by design: Organizations will satisfy continually evolving customer expectations and drive growth into the future by designing operations with business agility and environmental and social responsibility goals in mind. With access to real-time data across a connected value chain for measurement and analysis, businesses can drive new value creation and seize a competitive advantage while supporting a commitment to environmental and social stewardship. The reengineering of legacy products with carbon-friendly materials will be key to attaining sustainability by design.
GenAI-based value
Applying a GenAI-based context to value creation can help to visualize the tremendous potential that awaits with next-gen IoT.
When it comes to enabling and driving value creation through IoT, traditional AI combined with the advances in GenAI are emerging as a powerful technology duo. While operational efficiency and productivity gains are still important benefits to realize, the journey to value does not end there.
The arrival of GenAI will help deliver on the promise of IoT and unlock new game-changing potential for driving improved operational performance and engineering innovation. Leveraging personalized knowledge augmentation capabilities will drive new value creation by improving strategic thinking and decision-making across an enterprise.
The spectrum of progressive business benefits to be realized, for instance, may include improved:
- Productivity not just in software development but also in enabling workforces and machines to perform at higher levels and more autonomously for better throughput.
- Performance with products tested in complex scenarios and for the enhancement of yield, superior quality, and waste elimination.
- Engineering innovation by enabling a shift-left and moving testing to earlier in the new product development cycle.
Keys to realization
While the transformative possibilities of IoT are limitless, there are also business risk and impact considerations that must be addressed to successfully participate in a connected world.
To realize value with an IoT-led transformation, three key considerations include:
Security risks: The convergence of information technology (IT) and IoT/operational technology (OT) systems in creating a connected value chain can introduce new security vulnerabilities. Wherever there are touchpoints along the value chain between the digital IT and physical IoT/OT realms, there are potential attack points.
As industry leaders look to deploy next-gen IoT capabilities, the overall potential benefits versus the risks and costs must be carefully weighed and justified. They must assess what business and operational activities need to be conducted at the edge and the infrastructure requirements versus what should be processed and stored in the cloud or inside a closed premise.
Climate impact: Environmental protection and sustainability goals are a top priority for any socially responsible business today. Businesses must therefore ensure that their IoT strategy is future-ready and sustainable by design to contribute toward the global agenda for net zero carbon emissions.
According to the World Economic Forum’s Internet of Things Guidelines for Sustainability report, IoT is among the largest enablers for responsible digital transformation, but sustainability goals must be considered early on in the design phase of IoT projects to realize their full potential. The report estimates that by 2030, industrial IoT alone could add up to $14 trillion in economic value with the potential increasing as consumer and public sector IoT use are included.
Responsible AI: Businesses must consider how they will manage the change of introducing AI and GenAI into the real world in a sensitive, ethical, and responsible manner to facilitate the acceptance of a collaborative human-machine workforce. They must help employees understand the potential process and performance improvement benefits of leveraging a personalized AI augmentation capability to work smarter rather than viewing it as an existential threat.
But empowering employees with AI capabilities, in turn, creates a potential risk that they could expose an enterprise’s competitive engineering intelligence. Safeguards must therefore be implemented to support the responsible use of AI among employees.
Because there are tradeoffs with any of these considerations and no straight answers, applying a strategic and comprehensive approach to an IoT-led transformation is paramount to help ensure success.
Journey to transform
When envisioning a path to transform through IoT, businesses must focus on the dual objective of creating value from an economic and competitive differentiation perspective.
The planned investment in edge/IoT computing is expected to rise from 45% to 48%, according to the findings of a recent TCS Global Cloud Study conducted among senior executives. This uptrend is based on the percent who, at the time of the survey, had increased their investments in the past 12-24 months compared to their intended investments in the next 12-24 months. As businesses invest in building an IoT infrastructure and capabilities to support their operations into the future, they must step wisely.
Starting with value discovery, business stakeholders must convene to assess their needs and prepare a roadmap by identifying and prioritizing their IoT initiatives through a top-down, holistic approach. Progressing to the value realization step in the journey, the business will then structure and enable the technology backbone to deploy the IoT strategy. At this point, research and development converges with business and operating models. Reaching the value optimization stage, the focus shifts to enhancement, support, and ongoing maintenance.
Figure 2: Move from value discovery to realization and optimization
As the four tech mega trends of software-enabled things, digital twins, AI and GenAI, and edge-to-cloud computing with 5G connectivity converge to create the next generation of IoT, new opportunities for business value creation and sustainable growth will rapidly emerge. Business leaders who start preparing for their IoT-led transformations today will gain an edge in their industries.
