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Staff Writer, Automation & ITOps Content Director Watson IoT Digital twins enable continuous monitoring, simulation and analysis of an object, product or system over the course of its lifecycle, from design and production to maintenance and decommissioning. They can also incorporate external processes and critical variables that affect an asset’s performance. A key feature is real-time, two-way data exchange between the object and its virtual replica, helping ensure that simulated conditions accurately reflect the physical world. Enterprises can also connect multiple digital twins to model more complex systems in service of a larger digital transformation or Industry 4.0 strategy. By providing insight into how an object functions in the present—and projecting how it might behave in future scenarios—digital twins help organizations improve efficiency, accelerate innovation and make data-driven, informed decisions. Common use cases include process optimization, predictive maintenance, supply chain optimization and product development. Many modern digital twin providers, including Siemens, General Electric, Nvidia, IBM, Bentley and Microsoft, offer a full suite of services. Packages might include hardware layers (such as sensor kits), data processors, synchronization services, simulation engines, analytics platforms and visualization dashboards. But enterprises with more specialized applications might instead take a modular approach, choosing several services to match their needs. Digital twins can represent virtually any object, from buildings and bridges to cars, airplanes, historical artifacts and even the earth. They might also model complex systems such as traffic patterns, weather events, healthcare treatment plans and factory operations. Finally, in more experimental contexts, digital twins might be based on real or imagined people, complete with modeled voice, appearance and personality traits. Digital twins are now widely used across industries: A 2023 Strategic Market Research study found that roughly 75% of businesses employ them in some capacity. These initiatives can be costly and resource-intensive. But for many enterprises, they are worth the investment: 92% of companies who deploy digital twins report returns above 10%, while over half report at least 20% return on investment, according to a 2025 Hexagon survey. Industry newsletter Stay up to date on the most important—and intriguing—industry trends on AI, automation, data and beyond with the Think newsletter. See the IBM Privacy Statement. Your subscription will be delivered in English. You will find an unsubscribe link in every newsletter. You can manage your subscriptions or unsubscribe here. Refer to our IBM Privacy Statement for more information. While digital twin workflows vary widely across industries and applications, most include these fundamental steps: An enterprise might begin by equipping a physical object with an array of sensors, which capture its performance, condition and operating environment. In IoT contexts, an organization might deploy “smart objects,” which often come preinstalled with built-in sensors that can continually collect and share data. In IT settings, teams can build digital representations of applications, software and computers (virtual machines) using virtualization technologies. They can then deploy software agents to collect data at or near the digital asset for monitoring and analysis. A virtual model is a digital replica of an object or system, built using the data gathered from its real-life counterpart. It is embedded with key attributes that help it realistically react to variables such as environmental conditions and interactions with related systems. For example, a digital twin of an airplane turbine not only simulates wear and failure at the same rate as it’s real-life counterpart but also accounts for aerodynamic forces during flight and the influence of connected engine and hydraulic components. This detailed modeling helps ensure that the digital twin can reliably simulate how its real-life counterpart might respond under a range of conditions. Live data integration enables continuous, real-time communication between the digital twin and its physical counterpart. This dynamic feedback loop can help organizations optimize performance, enhance system reliability and implement predictive maintenance—when teams anticipate issues ahead of time, reducing downtime and extending asset lifecycles. Enterprises often automate the data exchange process, freeing them up to tackle higher-level strategic tasks. Digital twins enable teams to run safe, cost-effective experiments within a virtual environment. For example, in a manufacturing context, a team can simulate how an assembly line upgrade might affect performance and efficiency. Or it might test whether a more affordable packaging option can withstand the rigors of shipping and distribution. By exploring a range of “what-if” scenarios, digital twin platforms help teams improve operational efficiency and enhance product quality without the risks and costs associated with real-world testing. Analytics engines can suggest certain operational changes—such as scaling cloud capacity, production volume or team budgets—to help teams optimize performance and spending. They might also integrate with customer relationship management (CRM) platforms and enterprise resource planning (ERP) tools to streamline production workflows and customer funnels. See how IBM Maximo and Microsoft Cloud bring digital twin technology to life, helping organizations improve safety, optimize performance, and drive innovation at scale. Both simulations and digital twins help teams replicate and test scenarios in a digital environment. But while digital twins mirror a real-life object and its specific traits, simulations often exist entirely in the virtual world without an immediate connection to real-world systems. Put another way, simulations are static; they run predefined scenarios with no built-in mechanism to transmit their findings to a physical system. In contrast, digital twins can dynamically reflect real-time conditions while at the same time sending information to the physical systems they represent. Another distinction is that digital twin solutions can connect multiple assets and systems, instead of evaluating them in isolation. Teams can seamlessly add or eliminate components to mirror real-life scenarios, determining how changes to one asset might impact the wider ecosystem. 3D models are static representations of an object at a single point in time. Organizations can use them to understand what an object looks like, but not how it behaves. On its own, a 3D model can’t assess future scenarios or represent real-time conditions. However, 3D models often serve as a foundational component of both digital twins and simulations, providing accurate visual and spatial representations of physical assets or processes. Although teams can build connected twins (networks made up of linked digital twins) to capture a wider view of system performance, these networks are typically used to optimize asset lifecycles within a single production environment. Digital threads, meanwhile, are often broader in scope, connecting data across multiple departments, processes and environments to capture an organization-wide view of assets and systems. Digital threads can centralize data from multiple production environments so it’s accessible to stakeholders across the organization. Ultimately, digital threads are ideal for gaining a holistic view of the organization’s interlocking systems, while digital twins are better suited for fine-tuning individual assets and processes. It’s common for several types of digital twins, each offering a different layer of magnification, to co-exist within a single production environment. The four main types include: Component twins, also called part twins, replicate individual components, offering a granular level of insight into specific parts. For example, a component twin might use an array of sensors to mirror a valve in an oil pipeline, a motor in a wind turbine or a turbocharger in a car. Asset twins replicate complete functional units, often made up of two or more components, and show how these components interact in real time. Asset twins might replicate an oil pipeline valve system (made up of multiple valves and pipes), a wind turbine drive train (made up of a motor, gearbox and shaft) or a car’s turbocharging system (made up of a turbocharger, intercooler and compressor). System or unit twins enable enterprises to understand how assets fit together to form a larger, integrated system. They provide visibility into asset interactions while identifying opportunities for performance enhancements at the system level. System twins might mirror a segment of an oil pipeline (made up of multiple valve and pump systems), a wind turbine (made up of motors, blades and control systems) or a vehicle powertrain system (including the engine, transmission and driveshaft). Process twins provide the broadest view, revealing how systems work together across a production facility, supply chain or operational workflow. Process twins can help ensure that the entire production environment, not just specific components, is operating at optimal efficiency. Process twins might replicate an end-to-end oil distribution network, an energy-generating wind farm or an automotive manufacturing process. Digital twins give enterprises greater visibility into complex systems along with the flexibility to explore multiple operational configurations before committing real-world resources to them. Major benefits include: Digital twin solutions help enterprises experiment with different product designs, workflows and manufacturing processes within a virtual testing environment, accelerating innovation and reducing time to market. For example, aerospace engineers can build digital twins of experimental aircraft, each with different wing and propulsion designs, to determine which iteration shows promise for further development. This approach is far more cost-effective, and safer, than building and testing physical aircraft prototypes for each proposed design. After a new product has gone into production, digital twins can help mirror and monitor systems to achieve and maintain peak efficiency throughout the manufacturing process. Teams can also identify cost-cutting opportunities without interfering with current workflows. For example, an enterprise can test out a more affordable material or manufacturing process in the virtual environment—and determine whether it can maintain performance and emissions standards—before rolling it out on a wider scale. Digital twins can also use historical data for predictive maintenance (forecasting which assets are likely to fail before an error occurs). In complex modern systems, a single malfunction or asset failure can cause widespread disruptions, especially if teams struggle to identify the root cause. For example, a small circuit that controls cooling fans in a data center might fail, triggering overheating that takes an entire server rack offline. Digital twins can address this problem by reflecting the real-time condition of individual components, including sensors, circuits and capacitors. By continuously communicating with the physical system, a digital twin can detect early warning signs, such as abnormal temperature spikes, and anticipate imminent failures. This capability helps teams act early, avoiding downtime and costly errors. To remain competitive, enterprises must quickly scale operations to accommodate shifting product demand, economic conditions and strategic priorities. Traditionally, scaling up or down is a slow, arduous process, requiring teams to carefully validate new systems before rolling them out across the organization. Digital twins make this process faster and less risky by providing a virtual environment where teams can safely adjust parameters and test configurations ahead of universal deployment. Digital twins can also connect to live systems, enabling them to continuously transmit scaling adjustments to their physical counterparts in real time. For example, digital twin platforms might use algorithms to automatically add or remove cloud nodes during usage spikes to reduce traffic bottlenecks and maintain stable performance. Many industries rely on digital models to make sense of complex systems, spur innovation, maintain equipment and optimize efficiency. Digital twins are used extensively in the following industries and applications: Organizations can use digital twins to model jet engines, locomotive engines, electricity-generating turbines, utility assets and other power-generating systems. Digital twin platforms can establish time frames for regularly scheduled maintenance, detect hardware irregularities and enable testing of new components. They can also facilitate the transition to renewable energy by monitoring grid demand, simulating new asset configurations and forecasting grid trajectories. Physics-based digital twin systems can help engineers design durable, safe and cost-effective structures, including buildings, drilling platforms, canals, dams and bridges. They can, for example, determine whether a particular bridge can withstand heavy wind, rain and traffic, giving engineers the opportunity to alter their design before construction begins. Digital twins can also provide visibility into already-built structures, for example by revealing how key systems—such as plumbing, HVAC, electrical and security—interact inside an office building. These insights can help inform building information modeling (BIM) systems, which use digital representations of a structure to manage its construction and maintenance. In manufacturing, digital twins (often equipped with AI capabilities) can enhance quality control, supply chain management and error detection by providing oversight across a product’s end-to-end lifecycle. For example, an electronics manufacturer can build a digital replica of a factory floor, reflecting the real-world location’s inventory levels, production schedules, equipment statuses and other operational data. Digital twins can generate key health insights through disease progression forecasting, which predicts how patients might respond to various treatment options, and through enhanced diagnosis, which uses highly detailed modeling to pinpoint how interactions between organs and body systems can impact health. They can also help hospitals optimize their operations—including staffing, scheduling and equipment maintenance—and can facilitate the transition to personalized healthcare, where treatments are customized to match individual patients’ needs. Digital twins are used extensively in auto design, both to improve vehicle performance and to increase production efficiency. For example, vehicle designers can conduct extensive safety and emissions testing with virtual replicas before benchmarking real-life vehicles. Civil engineers and urban planning experts use digital twins to simulate how pedestrians and vehicles move through cities. City models often incorporate 3D and 4D spatial data, IoT object data and AI-powered analytics to simulate how new policies, infrastructure upgrades or transportation systems might impact the built environment. Digital twins play a key role in smart cities, which use IoT-connected devices to continuously collect and share data that can be harnessed to improve quality of life and sustainability. The concept behind digital twin technology dates to the 1960s, when NASA built physical replicas of its spacecraft to study how they might respond to different conditions before sending their real-life counterparts into orbit. In 1970, when an onboard explosion threatened the lives of the Apollo 13 crew, NASA relied on these models to explore different rescue scenarios from the ground, according to the administration’s Technical Reports Server. While these early efforts used physical copies instead of virtual ones, they paved the way for what would eventually become known as “digital twins.” In 2002, scientist and business executive Michael Grieves conceptualized a product lifecycle management (PLM) framework that links a physical product with its virtual counterpart through continuous data exchange. Eight years later, NASA’s John Vickers officially coined the term “digital twin” in a NASA technical roadmap, building from Grieves’ “mirrored spaces” concept. The digital twin market is rapidly expanding, according to a Fortune Business Insights report. It’s expected to grow from USD 24.5 billion in 2025 to USD 259.3 billion by 2032, with industries such as smart cities, aerospace, healthcare and manufacturing driving growth. New and emerging digital twin capabilities include: Generative AI can predict how systems might react in the future based on both historical and real-time datasets. This capability empowers teams to make better-informed operational decisions and investments. AI technologies can also help digital twin systems optimally scale and provision resources without human intervention. Instead of automating only rote, repetitive tasks, AI models can use digital twins to make longer-term, multi-step decisions. For example, they can anticipate how a component failure might cascade through the network, affecting neighboring assets and systems; alert relevant teams each time a component needs maintenance; recommend network enhancements so that failures are less likely to occur; and in some cases, implement operational changes entirely on their own. Like software as a service (SaaS), digital twin as a service (DTaaS) is becoming a popular choice for enterprises. The delivery method enables organizations to quickly implement and scale digital twins through the cloud, without having to program them from scratch or maintain the servers they live on. Developers are designing digital twins capable of mirroring human behaviors and cognition. Digital doppelgängers can be used for both personal applications (such as legacy preservation or audience engagement) and professional ones (such as training employees or automating repetitive tasks). They can also be useful in research contexts. For example, researchers can perform experiments with synthetic users to simulate how real-life humans might respond to new products and features. Enterprises can then aggregate these findings to project population-level trends. Learn how the CMMS market is evolving as organizations focus on digitizing maintenance, boosting asset reliability and improving real-time visibility. Identify the best asset performance management (APM) software that fits your needs. Learn how your organization can achieve significant value by using IBM Maximo to manage its fleet of assets. Increase uptime, improve productivity, reduce maintenance costs and build more resilient operations with IBM’s unified asset management solution. Discover how Sund & Bælt uses IBM’s Maximo software to monitor and manage its critical infrastructures. Learn how VPI pushes forward on the path to net zero with IBM Maximo software. Transport for London keeps the public moving safely, reliably and sustainably when it centralizes its maintenance efforts on IBM Maximo software. Streamline the maintenance, inspection and reliability of your critical equipment and infrastructure by leveraging generative AI, advanced analytics and the Internet of Things (IoT). Power smarter manufacturing with IBM — leverage AI, hybrid cloud and automation to optimize production, improve quality, and build resilient, efficient operations. Transform your operations — use AI, automation, and process expertise to streamline workflows, improve efficiency, and drive lasting business performance. Maximize your assets’ performance with IBM Maximo — intelligent, AI-enabled asset management that reduces downtime and boosts efficiency. Book a demo today to see how smart maintenance and real-time insights can transform your operations. 1Digital Twin Market by Enterprise, Application (Predictive Maintenance, Business optimization), Industry (Aerospace, Automotive & Transportation, Healthcare, Infrastructure, Energy & Utilities) and Geography (external link to ibm.com). Global Forecast to 2027. Digital Twin Market. June 2022

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IBM Consulting Staff Editor Editor, Topics & Insights Digital transformation is a business strategy initiative that incorporates digital technology across all areas of an organization. It evaluates and modernizes an organization’s processes, products, operations and technology stack to enable continual, rapid, customer-driven innovation. Today customers expect to be able to conduct their business, do their work and live their lives by using the latest technology advances. They expect this ability from wherever they are, anytime they want, by using the device of their choice and with all the supporting information and personalized content they need close at hand. The ultimate goal of digital transformation is to meet these expectations. Every organization’s digital transformation implementation is different. It can begin with a single focused technology project, or as a comprehensive enterprise-wide initiative. It can range from integrating digital technology and digital solutions into existing processes and products, to reinventing processes and products or creating entirely new revenue streams by using still-emerging technologies. But experts agree that digital transformation is as much about business transformation and change management as it is about replacing analog processes or modernizing existing IT. While often led by a company’s chief information office (CIO), it requires the entire C-suite to align on new technologies and data-driven methodologies that can improve customer experience, empower employees and achieve business goals. But, most importantly, companies should create a digital transformation framework and monitor improvements through tracking key performance indicators (KPIs) to see if the work produces results. The earliest, headline-making examples of digital transformation—Uber, AirBnB, Netflix—used mobile and cloud computing technologies to reimagine transactions and, sometimes, disrupt entire industries. The COVID-19 pandemic drove transformative innovations to better support remote and hybrid work. Today, organizations are applying artificial intelligence (AI), automation and other technologies to streamline workflows, personalize customer experiences, improve decision-making, and respond more quickly and effectively to market disruptions and new opportunities. Digital transformation can help companies increase customer loyalty, attract talented employees, foster competitive advantage and build business value. McKinsey research found that between 2018-2022, digital leaders achieved about 65% greater annual total shareholder returns than digital “laggards.”1 Industry newsletter Stay up to date on the most important—and intriguing—industry trends on AI, automation, data and beyond with the Think newsletter. See the IBM Privacy Statement. Your subscription will be delivered in English. You will find an unsubscribe link in every newsletter. You can manage your subscriptions or unsubscribe here. Refer to our IBM Privacy Statement for more information. In digital transformation, domains are essentially targets or levers for transformation. Most digital transformation strategies target one or more of these domains: Business model transformation is a fundamental change in the way that an organization delivers products, services and value to its customers, investors or stakeholders. Examples include: Organizations pursue business model transformation for any number of reasons—for example, to meet changing customer expectations, boost flagging sales, or differentiate themselves in a highly competitive market. They might also see a chance to disrupt a market or industry in their favor with a new business model—or have a need to respond to a disruptive competitor. While business model transformation grabs the headlines, business process optimization is an increasingly common digital transformation driver. Process optimization can include: Process optimization can help organizations lower costs, reduce waste (time, effort and materials), make better use of human capital, and help all stakeholders make smarter decisions faster. Organizations are incorporating digital innovation into their products, and into the way their products are developed, produced and delivered. The most obvious examples involve the embedding of digital technology into everyday products that meet customer needs. Automobiles, for instance, are continually transformed in this way. Innovations range from the ability to view and operate a smartphone from a car dashboard, to sensors that prevent crashes and unintended lane changes, to vehicles that incorporate computer vision, geolocation, machine learning and robotic process automation (RPA) to operate with minimal or no human intervention. By implementing Internet of Things (IoT), operational technology and automation on the factory floor, manufacturers can speed production, reduce errors and defects and eliminate manual labor. By adopting agile or DevOps practices organizations can speed software development. Companies can also add value and competitive differentiation by offering technology alongside their existing services—witness the tracker apps offered by shipping companies and pizza vendors. Employee experience is a holistic approach to talent management that helps ensure that employees have the tools the need to succeed and thrive at work. Employee experience certainly impacts employee recruitment, morale, productivity and retention, but it can also have a direct impact—positive or negative—on customer experience, business performance and brand reputation. Digital transformation efforts to improve employee experience can include: Customer experience, or CX, is the sum of customers’ perceptions resulting from all their interactions with a business or brand—online, in-store and in day-to-day life. In the end, all digital transformation journeys lead to the customer experience domain. Continually improving the customer experience is a competitive imperative for most organizations. In the digital age, continually improving the customer experience requires continual digital innovation. It’s not just that customers expect to be able to do business anytime, anywhere and on any device—today customers depend on it. They plan their mornings knowing their phones tell them exactly how long it takes to drive to work, and their evenings knowing they can meet the food delivery driver at their door. They ignore customer service call center hours, knowing they can get answers 24/7 from a chatbot. They stop saving receipts knowing that they can download their bank and credit card history at tax time (or anytime). Customers count on these and scores of other digital innovations, and they are ready to count on new ones. Successful digital transformation positions organizations to anticipate and deliver the next innovations and experiences customers will want. Miha Kralj joins Ann Funai to explore talent shifts, agentic AI and the future of innovation for enterprise tech teams. Virtually any digital technology can play a role in an organization’s digital transformation strategy, but these technologies are most closely associated with transformation initiatives. The original digital transformation enabler, cloud computing enables organizations to use the latest IT technologies, boost efficiency and scale with demand while managing costs. A hybrid cloud infrastructure, combining orchestrated public cloud and private cloud resources from multiple vendors, provides the application portability, vendor flexibility and IT agility needed for enduring digital transformation success. Customers’ dependence on mobile devices drove the earliest digital transformation initiatives, transformed existing business models (for example mobile tickets and wallets) and created entirely new ones (for example, Uber). Today customers insist on doing more business through mobile apps, whether simply ordering lunch or dinner from their favorite restaurant, or managing their banking and investments. The Internet of Things (IoT) is the universe of devices equipped with sensors that collect and transmit data over the internet. IoT devices are where digital technology meets physical reality. Applications like supply chain logistics and self-driving cars generate real-time data that AI and big data analytics applications turn into automation and decisions. AI and machine learning enable a computer or machine to mimic the capabilities of the human mind. AI learns from examples, recognizes objects, makes decisions and quickly processes large tasks. Generative AI applications can answer customer service inquiries, deliver content on demand, and perform other activities automatically and without human intervention, freeing employees for higher-value work. AI also enables personalization on demand and at scale across marketing, customer service, sales and other areas of a business. Organizations also use automation, and specifically robotic process automation (RPA), to perform repetitive tasks such as bookkeeping, sending invoices, or looking up or archiving records. Unlike AI, which can learn from data and perform tasks more accurately over time, RPA is limited to following processes that have been defined by a user or programmer. DevOps accelerates delivery of higher-quality software by combining and automating the work of software development and IT operations teams. DevSecOps continuously integrates and automates security throughout the DevOps lifecycle, from planning through feedback and back to planning again. DevOps and DevSecOps practices provide the agile development foundation organizations need to respond with speed to market changes and innovate software continuously. Digitization is the conversion of paper-based information into digital data. It’s also a cornerstone of foundational transformation initiatives in healthcare (electronic medical records or EMR), government (making public records more accessible and enabling citizens to make service requests online), and other industries. Blockchain is a distributed, permanent and immutable ledger or record of electronic transactions. Blockchain provides total transaction transparency to those who require it and is inaccessible to those who don’t. Organizations are using blockchain as a foundation for superresilient supply chains and cross-border financial services transformations. Digital transformation has created many ways organizations can partner with each other to serve customers. The rise of business ecosystems, driven by APIs and other advanced technologies and a growing interconnectedness between noncompetitive companies. Software providers can enable users to sign in with accounts from third parties. For example, an email provider can create a marketplace where users can connect their task management software or customer relationship management (CRM) provider. This new technology-led approach involves creating digital facsimiles of physical products or environments to test out ways to improve efficiency or effectiveness. For example, a manufacturer can make a digital twin of their shop floor to find ways to improve the location of machinery to increase output or reduce safety issues. Or a product manufacturer can create digital replicas of their products to identify ways to produce ones that are more ergonomic or easier to use. Digital twins help organizations improve their business in the future while not burdening existing operations with trial-and-error improvements. Experts and organizations credit digital transformation with everything from improved supply chain and resource management to significant gains in overall productivity, profitability and competitive advantage. Some of the most frequently cited benefits include: Successful digital transformation can improve an organization’s customer experience and customer relationships. Enabling customers to engage by using the device and channel of their choice (web portal, social media, in-app), providing 24/7 customer service through a chatbot, delivering personalized content in context during any transaction—these are just some of the ways organizations can better satisfy and retain customers by using digital technology. Digital transformation should enable organizations to innovate products and processes continually. Adoption of hybrid multicloud infrastructure provides access to the best digital tools and technologies as they emerge. Agile and DevOps practices enable developers to rapidly integrate these technologies into their applications and systems. The same flexibility and agility that enables rapid innovation also helps the organization respond faster to changes in customer demand, new market opportunities and competitive threats. In its earliest days, digital transformation enabled upstarts to disrupt entire industries; today it also helps organizations respond quickly and effectively to would-be disruptors. Digital tools can help organizations create more streamlined workflows, processes and infrastructure as a result of their transformations. Through automation and AI, organizations can cut down laborious menial tasks and free up their vital employees to spend more time with customers and other stakeholders. Digital transformation can improve employee engagement in any number of ways, from providing access to the latest tools and technologies to driving a culture of agile innovation in which employees are encouraged to experiment, take risk, ‘fail fast’ and learn continually. According to the latest Gallup Q12 meta-analysis, which evaluates the connection between employee engagement and business outcomes, companies with higher levels of engagement show significantly higher performance in everything from absenteeism to sales productivity and profitability.2 Digital transformation can uncover issues with legacy technology or existing cybersecurity measures that put an organization at risk. Adopting the latest security technologies can help an organization better detect and respond to threats, reduce successful attacks, and prevent or minimize any resulting damage. Infusion of the latest technologies into a company’s IT portfolio can help create new opportunities for revenue, including revenue streams from websites, mobile apps, upselling through chatbots and more. AI and sophisticated metrics can help identity new product and service opportunities based on customers’ website behaviors and buying patterns. And customers might simply be more inclined to purchase from companies that offer more options for doing digital business. Most people have read or heard how companies like Netflix and Uber have disrupted their business models and industries through digital transformation. But other organizations also have compelling stories about digital transformation initiatives that revolutionized their businesses. Here are just a few examples: Consumers have always known Audi for making beautiful, high-performance cars, but the company risked falling behind electric car upstarts as more people wanted to move away from gas-powered cars. The German automaker not only wanted to enter the electric market in a significant way but also wanted to embrace the digitization of its offerings through connected cars and autonomous driving. Audi has a clear understanding of what it needs to do to compete in a highly competitive marketplace driven by sustainability and convenience. Seeing the US’ only tennis major in person is an amazing experience, but not every tennis fan can make it to New York. The US Open wanted to ensure that the 15 million-plus fans could experience the tournament’s hundreds of matches through the US Open app and website. The US Open used generative AI models to turn more than 7 million tournament data points into digital content that gave fans more context about the matching being played. The UK’s system of public healthcare providers needed to balance providing more digital services to clients while maintaining a strong security posture. Its digital, data and technology delivery partner, NHS Digital, created a Cyber Security Operations Centre (CSOS) that is as a single point of coordination between NHS and external partners. It now monitors more than 1.2 million NHS devices for threats and blocks more than two billion malicious emails a year through targeted filtering. The independent German gas and oil company knew that AI would help it better harness data generated from across the organization. While several internal business and corporate units had begun using AI, it needed a centralized initiative to deploy it at scale. It started AI@Scale where projects incorporated scalability at the start. One such deployment automated data extraction from 2,000 PDF documents, freeing up employees to focus on more impactful work. The Korean manufacturing business conglomerate understood that even one successful cybersecurity attack might have devastating consequences. Its Doosan Digital Innovation (DDI) group consolidated multiple regional security operation centers (SOCs) to a unified, global SOC to streamline its security posture and deployed AI-based pattern matching. As a result, response times have decreased by about 85%. Activate these five mindshifts to cut through the uncertainty, spur business reinvention, and supercharge growth with agentic AI. Get past barriers and leap forward with courage and conviction in the generative AI era. 
 Explore how CEOs are using generative AI and application modernization to drive innovation and stay competitive. Learn how Industry 4.0 can transform your operations, overcome common challenges and drive business results with AI and industrial IoT. Find out how IBM uses AI to help the Recording Academy deliver improved digital fan experiences and better service to its members. A single solution to orchestrate AI agents, assistants and workflows across your business Manage your hybrid cloud environment to run workloads where and when you need them. Grow and transform your business by reimagining your strategy with AI for transformation. Whether you choose to customize pre-built apps and skills or build and deploy custom agentic services using an AI studio, the IBM watsonx platform has you covered.

IBM Consulting Staff Editor Editor, Topics & Insights Digital transformation is a business strategy initiative that incorporates digital technology across all areas of an organization. It evaluates and modernizes an organization’s processes, products, operations and technology stack to enable continual, rapid, customer-driven innovation. Today customers expect to be able to conduct their business, do their work and live their lives by using the latest technology advances. They expect this ability from wherever they are, anytime they want, by using the device of their choice and with all the supporting information and personalized content they need close at hand. The ultimate goal of digital transformation is to meet these expectations. Every organization’s digital transformation implementation is different. It can begin with a single focused technology project, or as a comprehensive enterprise-wide initiative. It can range from integrating digital technology and digital solutions into existing processes and products, to reinventing processes and products or creating entirely new revenue streams by using still-emerging technologies. But experts agree that digital transformation is as much about business transformation and change management as it is about replacing analog processes or modernizing existing IT. While often led by a company’s chief information office (CIO), it requires the entire C-suite to align on new technologies and data-driven methodologies that can improve customer experience, empower employees and achieve business goals. But, most importantly, companies should create a digital transformation framework and monitor improvements through tracking key performance indicators (KPIs) to see if the work produces results. The earliest, headline-making examples of digital transformation—Uber, AirBnB, Netflix—used mobile and cloud computing technologies to reimagine transactions and, sometimes, disrupt entire industries. The COVID-19 pandemic drove transformative innovations to better support remote and hybrid work. Today, organizations are applying artificial intelligence (AI), automation and other technologies to streamline workflows, personalize customer experiences, improve decision-making, and respond more quickly and effectively to market disruptions and new opportunities. Digital transformation can help companies increase customer loyalty, attract talented employees, foster competitive advantage and build business value. McKinsey research found that between 2018-2022, digital leaders achieved about 65% greater annual total shareholder returns than digital “laggards.”1 Industry newsletter Stay up to date on the most important—and intriguing—industry trends on AI, automation, data and beyond with the Think newsletter. See the IBM Privacy Statement. Your subscription will be delivered in English. You will find an unsubscribe link in every newsletter. You can manage your subscriptions or unsubscribe here. Refer to our IBM Privacy Statement for more information. In digital transformation, domains are essentially targets or levers for transformation. Most digital transformation strategies target one or more of these domains: Business model transformation is a fundamental change in the way that an organization delivers products, services and value to its customers, investors or stakeholders. Examples include: Organizations pursue business model transformation for any number of reasons—for example, to meet changing customer expectations, boost flagging sales, or differentiate themselves in a highly competitive market. They might also see a chance to disrupt a market or industry in their favor with a new business model—or have a need to respond to a disruptive competitor. While business model transformation grabs the headlines, business process optimization is an increasingly common digital transformation driver. Process optimization can include: Process optimization can help organizations lower costs, reduce waste (time, effort and materials), make better use of human capital, and help all stakeholders make smarter decisions faster. Organizations are incorporating digital innovation into their products, and into the way their products are developed, produced and delivered. The most obvious examples involve the embedding of digital technology into everyday products that meet customer needs. Automobiles, for instance, are continually transformed in this way. Innovations range from the ability to view and operate a smartphone from a car dashboard, to sensors that prevent crashes and unintended lane changes, to vehicles that incorporate computer vision, geolocation, machine learning and robotic process automation (RPA) to operate with minimal or no human intervention. By implementing Internet of Things (IoT), operational technology and automation on the factory floor, manufacturers can speed production, reduce errors and defects and eliminate manual labor. By adopting agile or DevOps practices organizations can speed software development. Companies can also add value and competitive differentiation by offering technology alongside their existing services—witness the tracker apps offered by shipping companies and pizza vendors. Employee experience is a holistic approach to talent management that helps ensure that employees have the tools the need to succeed and thrive at work. Employee experience certainly impacts employee recruitment, morale, productivity and retention, but it can also have a direct impact—positive or negative—on customer experience, business performance and brand reputation. Digital transformation efforts to improve employee experience can include: Customer experience, or CX, is the sum of customers’ perceptions resulting from all their interactions with a business or brand—online, in-store and in day-to-day life. In the end, all digital transformation journeys lead to the customer experience domain. Continually improving the customer experience is a competitive imperative for most organizations. In the digital age, continually improving the customer experience requires continual digital innovation. It’s not just that customers expect to be able to do business anytime, anywhere and on any device—today customers depend on it. They plan their mornings knowing their phones tell them exactly how long it takes to drive to work, and their evenings knowing they can meet the food delivery driver at their door. They ignore customer service call center hours, knowing they can get answers 24/7 from a chatbot. They stop saving receipts knowing that they can download their bank and credit card history at tax time (or anytime). Customers count on these and scores of other digital innovations, and they are ready to count on new ones. Successful digital transformation positions organizations to anticipate and deliver the next innovations and experiences customers will want. Miha Kralj joins Ann Funai to explore talent shifts, agentic AI and the future of innovation for enterprise tech teams. Virtually any digital technology can play a role in an organization’s digital transformation strategy, but these technologies are most closely associated with transformation initiatives. The original digital transformation enabler, cloud computing enables organizations to use the latest IT technologies, boost efficiency and scale with demand while managing costs. A hybrid cloud infrastructure, combining orchestrated public cloud and private cloud resources from multiple vendors, provides the application portability, vendor flexibility and IT agility needed for enduring digital transformation success. Customers’ dependence on mobile devices drove the earliest digital transformation initiatives, transformed existing business models (for example mobile tickets and wallets) and created entirely new ones (for example, Uber). Today customers insist on doing more business through mobile apps, whether simply ordering lunch or dinner from their favorite restaurant, or managing their banking and investments. The Internet of Things (IoT) is the universe of devices equipped with sensors that collect and transmit data over the internet. IoT devices are where digital technology meets physical reality. Applications like supply chain logistics and self-driving cars generate real-time data that AI and big data analytics applications turn into automation and decisions. AI and machine learning enable a computer or machine to mimic the capabilities of the human mind. AI learns from examples, recognizes objects, makes decisions and quickly processes large tasks. Generative AI applications can answer customer service inquiries, deliver content on demand, and perform other activities automatically and without human intervention, freeing employees for higher-value work. AI also enables personalization on demand and at scale across marketing, customer service, sales and other areas of a business. Organizations also use automation, and specifically robotic process automation (RPA), to perform repetitive tasks such as bookkeeping, sending invoices, or looking up or archiving records. Unlike AI, which can learn from data and perform tasks more accurately over time, RPA is limited to following processes that have been defined by a user or programmer. DevOps accelerates delivery of higher-quality software by combining and automating the work of software development and IT operations teams. DevSecOps continuously integrates and automates security throughout the DevOps lifecycle, from planning through feedback and back to planning again. DevOps and DevSecOps practices provide the agile development foundation organizations need to respond with speed to market changes and innovate software continuously. Digitization is the conversion of paper-based information into digital data. It’s also a cornerstone of foundational transformation initiatives in healthcare (electronic medical records or EMR), government (making public records more accessible and enabling citizens to make service requests online), and other industries. Blockchain is a distributed, permanent and immutable ledger or record of electronic transactions. Blockchain provides total transaction transparency to those who require it and is inaccessible to those who don’t. Organizations are using blockchain as a foundation for superresilient supply chains and cross-border financial services transformations. Digital transformation has created many ways organizations can partner with each other to serve customers. The rise of business ecosystems, driven by APIs and other advanced technologies and a growing interconnectedness between noncompetitive companies. Software providers can enable users to sign in with accounts from third parties. For example, an email provider can create a marketplace where users can connect their task management software or customer relationship management (CRM) provider. This new technology-led approach involves creating digital facsimiles of physical products or environments to test out ways to improve efficiency or effectiveness. For example, a manufacturer can make a digital twin of their shop floor to find ways to improve the location of machinery to increase output or reduce safety issues. Or a product manufacturer can create digital replicas of their products to identify ways to produce ones that are more ergonomic or easier to use. Digital twins help organizations improve their business in the future while not burdening existing operations with trial-and-error improvements. Experts and organizations credit digital transformation with everything from improved supply chain and resource management to significant gains in overall productivity, profitability and competitive advantage. Some of the most frequently cited benefits include: Successful digital transformation can improve an organization’s customer experience and customer relationships. Enabling customers to engage by using the device and channel of their choice (web portal, social media, in-app), providing 24/7 customer service through a chatbot, delivering personalized content in context during any transaction—these are just some of the ways organizations can better satisfy and retain customers by using digital technology. Digital transformation should enable organizations to innovate products and processes continually. Adoption of hybrid multicloud infrastructure provides access to the best digital tools and technologies as they emerge. Agile and DevOps practices enable developers to rapidly integrate these technologies into their applications and systems. The same flexibility and agility that enables rapid innovation also helps the organization respond faster to changes in customer demand, new market opportunities and competitive threats. In its earliest days, digital transformation enabled upstarts to disrupt entire industries; today it also helps organizations respond quickly and effectively to would-be disruptors. Digital tools can help organizations create more streamlined workflows, processes and infrastructure as a result of their transformations. Through automation and AI, organizations can cut down laborious menial tasks and free up their vital employees to spend more time with customers and other stakeholders. Digital transformation can improve employee engagement in any number of ways, from providing access to the latest tools and technologies to driving a culture of agile innovation in which employees are encouraged to experiment, take risk, ‘fail fast’ and learn continually. According to the latest Gallup Q12 meta-analysis, which evaluates the connection between employee engagement and business outcomes, companies with higher levels of engagement show significantly higher performance in everything from absenteeism to sales productivity and profitability.2 Digital transformation can uncover issues with legacy technology or existing cybersecurity measures that put an organization at risk. Adopting the latest security technologies can help an organization better detect and respond to threats, reduce successful attacks, and prevent or minimize any resulting damage. Infusion of the latest technologies into a company’s IT portfolio can help create new opportunities for revenue, including revenue streams from websites, mobile apps, upselling through chatbots and more. AI and sophisticated metrics can help identity new product and service opportunities based on customers’ website behaviors and buying patterns. And customers might simply be more inclined to purchase from companies that offer more options for doing digital business. Most people have read or heard how companies like Netflix and Uber have disrupted their business models and industries through digital transformation. But other organizations also have compelling stories about digital transformation initiatives that revolutionized their businesses. Here are just a few examples: Consumers have always known Audi for making beautiful, high-performance cars, but the company risked falling behind electric car upstarts as more people wanted to move away from gas-powered cars. The German automaker not only wanted to enter the electric market in a significant way but also wanted to embrace the digitization of its offerings through connected cars and autonomous driving. Audi has a clear understanding of what it needs to do to compete in a highly competitive marketplace driven by sustainability and convenience. Seeing the US’ only tennis major in person is an amazing experience, but not every tennis fan can make it to New York. The US Open wanted to ensure that the 15 million-plus fans could experience the tournament’s hundreds of matches through the US Open app and website. The US Open used generative AI models to turn more than 7 million tournament data points into digital content that gave fans more context about the matching being played. The UK’s system of public healthcare providers needed to balance providing more digital services to clients while maintaining a strong security posture. Its digital, data and technology delivery partner, NHS Digital, created a Cyber Security Operations Centre (CSOS) that is as a single point of coordination between NHS and external partners. It now monitors more than 1.2 million NHS devices for threats and blocks more than two billion malicious emails a year through targeted filtering. The independent German gas and oil company knew that AI would help it better harness data generated from across the organization. While several internal business and corporate units had begun using AI, it needed a centralized initiative to deploy it at scale. It started AI@Scale where projects incorporated scalability at the start. One such deployment automated data extraction from 2,000 PDF documents, freeing up employees to focus on more impactful work. The Korean manufacturing business conglomerate understood that even one successful cybersecurity attack might have devastating consequences. Its Doosan Digital Innovation (DDI) group consolidated multiple regional security operation centers (SOCs) to a unified, global SOC to streamline its security posture and deployed AI-based pattern matching. As a result, response times have decreased by about 85%. Activate these five mindshifts to cut through the uncertainty, spur business reinvention, and supercharge growth with agentic AI. Get past barriers and leap forward with courage and conviction in the generative AI era. 
 Explore how CEOs are using generative AI and application modernization to drive innovation and stay competitive. Learn how Industry 4.0 can transform your operations, overcome common challenges and drive business results with AI and industrial IoT. Find out how IBM uses AI to help the Recording Academy deliver improved digital fan experiences and better service to its members. A single solution to orchestrate AI agents, assistants and workflows across your business Manage your hybrid cloud environment to run workloads where and when you need them. Grow and transform your business by reimagining your strategy with AI for transformation. Whether you choose to customize pre-built apps and skills or build and deploy custom agentic services using an AI studio, the IBM watsonx platform has you covered.

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passiveadjective (GRAMMAR)

• ‘Catrin told me’ is an activesentence, and ‘I was told by Catrin’ is passive.
• In a passive sentence, the subject is the person or thing affected by the action of the verb.
• ‘Was made’ is a passive form of the verb ‘make’.
• Some verbs do not have a passive form.

• accusative
• active voice
• aorist
• art
• bent
• conditional
• conjugation
• ditransitive
• imperative
• imperfect
• modal
• modality
• non-finite
• non-progressive
• passivization
• passivize
• tense
• unconjugated
• wast
• wilt

passiveadjective (BEHAVIOUR)

• adynamic
• anywhere
• breather
• breathing space
• bum aroundphrasal verb
• dormant
• idle
• laze
• laze around
• leave someone beidiom
• lie aroundphrasal verb
• moribund
• navel
• recharge
• siesta
• sit on somethingphrasal verb
• sit on your arseidiom
• sit on your handsidiom
• sit roundphrasal verb
• slob

passiveadjective (INCOME)

• assessable
• bank
• base pay
• basic
• basic income
• coin
• feather your own nestidiom
• gross
• killing
• laugh
• non-wage
• nonearning
• not get out of bed for somethingidiom
• on commission
• operating
• salaried
• scrape a livingidiom
• starting salary
• stipend
• stoppage

Related word

Compare

Grammar

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• accusative
• active voice
• aorist
• art
• bent
• conditional
• conjugation
• ditransitive
• imperative
• imperfect
• modal
• modality
• non-finite
• non-progressive
• passivization
• passivize
• tense
• unconjugated
• wast
• wilt

Grammar

passive | American Dictionary

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passiveadjective (BEHAVIOR)

passiveadjective (GRAMMAR)

Note:

• In English, passive verbs or sentences are formed with a form of the verb “to be” and a past participle.

passively

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passivity

passive | Business English

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passively

Translations of passive

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adjective

1. not reacting visibly to something that might be expected to produce manifestations of an emotion or feeling. Antonyms:active
2. not participating readily or actively; inactive. a passive member of a committee. Antonyms:active
3. not involving visible reaction or active participation. to play a passive role. Antonyms:active
4. inert or quiescent.
5. influenced, acted upon, or affected by some external force, cause, or agency; being the object of action rather than causing action (active ).
6. receiving or characterized by the reception of impressions or influences from external sources.
7. produced or caused by an external agency.
8. receiving, enduring, or submitting without resistance. a passive hypnotic subject. Synonyms:docile , submissive Antonyms:recalcitrant , resistant
9. Grammar. noting a voice in the inflection of the verb in some languages which is used to indicate that the subject undergoes the action of the verb. Latin portātur, “he, she, or it is carried,” is in the passive voice. noting or pertaining to a construction similar to this in meaning, as English He is carried (active ).
10. noting a voice in the inflection of the verb in some languages which is used to indicate that the subject undergoes the action of the verb. Latin portātur, “he, she, or it is carried,” is in the passive voice.
11. noting or pertaining to a construction similar to this in meaning, as English He is carried (active ).
12. Chemistry. inactive, especially under conditions in which chemical activity is to be expected.
13. Metallurgy. (of a metal) treated so as to impart impassivity.
14. Medicine/Medical. of or relating to certain unhealthy but dormant conditions; inactive, as opposed to active or spontaneous.
15. Telecommunications. designed to relay signals without electronic devices. a passive communications satellite.
16. (of a solar heating system) accumulating and distributing solar heat without the aid of machinery.

not reacting visibly to something that might be expected to produce manifestations of an emotion or feeling.

not participating readily or actively; inactive.

a passive member of a committee.

a passive member of a committee.

not involving visible reaction or active participation.

to play a passive role.

to play a passive role.

inert or quiescent.

influenced, acted upon, or affected by some external force, cause, or agency; being the object of action rather than causing action (active ).

receiving or characterized by the reception of impressions or influences from external sources.

produced or caused by an external agency.

receiving, enduring, or submitting without resistance.

a passive hypnotic subject.

a passive hypnotic subject.

Grammar.

1. noting a voice in the inflection of the verb in some languages which is used to indicate that the subject undergoes the action of the verb. Latin portātur, “he, she, or it is carried,” is in the passive voice.
2. noting or pertaining to a construction similar to this in meaning, as English He is carried (active ).
3. Chemistry. inactive, especially under conditions in which chemical activity is to be expected.

noting a voice in the inflection of the verb in some languages which is used to indicate that the subject undergoes the action of the verb. Latin portātur, “he, she, or it is carried,” is in the passive voice.

noting or pertaining to a construction similar to this in meaning, as English He is carried (active ).

Chemistry. inactive, especially under conditions in which chemical activity is to be expected.

Metallurgy. (of a metal) treated so as to impart impassivity.

Medicine/Medical. of or relating to certain unhealthy but dormant conditions; inactive, as opposed to active or spontaneous.

Telecommunications. designed to relay signals without electronic devices.

a passive communications satellite.

a passive communications satellite.

(of a solar heating system) accumulating and distributing solar heat without the aid of machinery.

noun

1. the passive voice.
2. a passive form or construction.

the passive voice.

a passive form or construction.

adjective

1. not active or not participating perceptibly in an activity, organization, etc
2. unresisting and receptive to external forces; submissive
3. not working or operating
4. affected or acted upon by an external object or force
5. grammar denoting a voice of verbs in sentences in which the grammatical subject is not the logical subject but rather the recipient of the action described by the verb, as was broken in the sentence The glass was broken by a boy Compare active
6. chem (of a substance, esp a metal) apparently chemically unreactive, usually as a result of the formation of a thin protective layer that prevents further reaction
7. electronicstelecomm containing no source of power and therefore capable only of attenuating a signal a passive network not capable of amplifying a signal or controlling a function a passive communications satellite
8. containing no source of power and therefore capable only of attenuating a signal a passive network
9. not capable of amplifying a signal or controlling a function a passive communications satellite
10. finance (of a bond, share, debt, etc) yielding no interest

not active or not participating perceptibly in an activity, organization, etc

unresisting and receptive to external forces; submissive

not working or operating

affected or acted upon by an external object or force

grammar denoting a voice of verbs in sentences in which the grammatical subject is not the logical subject but rather the recipient of the action described by the verb, as was broken in the sentence The glass was broken by a boy Compare active

chem (of a substance, esp a metal) apparently chemically unreactive, usually as a result of the formation of a thin protective layer that prevents further reaction

electronicstelecomm

1. containing no source of power and therefore capable only of attenuating a signal a passive network
2. not capable of amplifying a signal or controlling a function a passive communications satellite
3. finance (of a bond, share, debt, etc) yielding no interest

containing no source of power and therefore capable only of attenuating a signal

a passive network

a passive network

not capable of amplifying a signal or controlling a function

a passive communications satellite

a passive communications satellite

finance (of a bond, share, debt, etc) yielding no interest

noun

1. grammar the passive voice a passive verb
2. the passive voice
3. a passive verb

grammar

1. the passive voice
2. a passive verb

the passive voice

a passive verb

Other Word Forms

• passively adverb
• passivity noun
• quasi-passive adjective
• semipassive adjective
• semipassiveness noun
• unpassive adjective

Etymology

Origin of passive

First recorded in 1350–1400; Middle English, from Latin passīvus literally, “submissive,” equivalent to pass(us) (past participle of patī “to experience, undergo, submit”) + -īvus adjective suffix; -ive

Example Sentences

Examples are provided to illustrate real-world usage of words in context. Any opinions expressed do not reflect the views of Dictionary.com.

Unlike traditional passive ETFs, which track a market index like the S&P 500, these funds are curated by a manager who chooses a collection of securities and is aiming to outperform the broader market. From The Wall Street Journal

Unlike traditional passive ETFs, which track a market index like the S&P 500, these funds are curated by a manager who chooses a collection of securities and is aiming to outperform the broader market.

From The Wall Street Journal

Maternal vaccination during the third trimester of pregnancy and passive immunization of newborns using long-acting antibodies are being rolled out in many countries. From Science Daily

Maternal vaccination during the third trimester of pregnancy and passive immunization of newborns using long-acting antibodies are being rolled out in many countries.

From Science Daily

It’s a high-net-worth strategy because it creates passive losses in taxable portfolios, which are used to offset capital gains for tax purposes. From Barron’s

It’s a high-net-worth strategy because it creates passive losses in taxable portfolios, which are used to offset capital gains for tax purposes.

From Barron’s

The debate centers on whether Strategy is an operating company or a passive asset holder. From Barron’s

The debate centers on whether Strategy is an operating company or a passive asset holder.

From Barron’s

Scientists have long debated whether water in these confined regions simply behaves as a passive bystander or affects how molecules interact. From Science Daily

Scientists have long debated whether water in these confined regions simply behaves as a passive bystander or affects how molecules interact.

From Science Daily

Related Words

• apathetic
• indifferent
• laid-back
• nonviolent
• quiet
• static
• unflappable
• uninvolved

Definitions and idiom definitions from Dictionary.com Unabridged, based on the Random House Unabridged Dictionary, © Random House, Inc. 2023

Idioms from The American Heritage® Idioms Dictionary copyright © 2002, 2001, 1995 by Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company.

inactive, idle, inert, passive, supine mean not engaged in work or activity. inactive applies to anyone or anything not in action or in operation or at work. on inactive status as an astronaut inactive accounts idle applies to persons that are not busy or occupied or to their powers or their implements. workers were idle in the fields inert as applied to things implies powerlessness to move or to affect other things; as applied to persons it suggests an inherent or habitual indisposition to activity. inert ingredients in drugs an inert citizenry passive implies immobility or lack of normally expected response to an external force or influence and often suggests deliberate submissiveness or self-control. passive resistance supine applies only to persons and commonly implies abjectness or indolence. a supine willingness to play the fool inactive, idle, inert, passive, supine mean not engaged in work or activity. inactive applies to anyone or anything not in action or in operation or at work. idle applies to persons that are not busy or occupied or to their powers or their implements. inert as applied to things implies powerlessness to move or to affect other things; as applied to persons it suggests an inherent or habitual indisposition to activity. passive implies immobility or lack of normally expected response to an external force or influence and often suggests deliberate submissiveness or self-control. supine applies only to persons and commonly implies abjectness or indolence. Adjective and Noun Middle English, from Latin passivus, from passus, past participle of pati 14th century, in the meaning defined at sense 1a(1) 15th century, in the meaning defined at sense 1 “Passive.” Merriam-Webster.com Dictionary, Merriam-Webster, https://www.merriam-webster.com/dictionary/passive. Accessed 13 Dec. 2025. Note: Under the Internal Revenue Code, there are two sources of passive income: rental activity and a business in which the taxpayer does not materially participate. Nglish: Translation of passive for Spanish Speakers Subscribe to America’s largest dictionary and get thousands more definitions and advanced search—ad free! See Definitions and Examples » Get Word of the Day daily email!

1. accepting what happens or what people do without trying to change anything or oppose them He played a passive role in the relationship.a passive observer of eventsShe wore a passive expression on her face as if she didn’t care what happened. Extra Examples Watching TV is a completely passive activity.We are passive recipients of information from the world around us. Oxford Collocations Dictionaryverbs beseembecome…adverb extremelyfairlyvery…See full entry Join us Join our community to access the latest language learning and assessment tips from Oxford University Press!
2. He played a passive role in the relationship.
3. a passive observer of events
4. She wore a passive expression on her face as if she didn’t care what happened.
5. Watching TV is a completely passive activity.
6. We are passive recipients of information from the world around us.
7. be
8. seem
9. become
10. …
11. extremely
12. fairly
13. very
14. …
15. (grammar)connected with the form of a verb used when the subject is affected by the action of the verb, for example He was bitten by a dog.compareactiveTopics Languageb1

• He played a passive role in the relationship.
• a passive observer of events
• She wore a passive expression on her face as if she didn’t care what happened.

• Watching TV is a completely passive activity.
• We are passive recipients of information from the world around us.

• be
• seem
• become
• …

• extremely
• fairly
• very
• …

Join us

Join our community to access the latest language learning and assessment tips from Oxford University Press!

• See Also: Passion WeekpassionalpassionarypassionatepassionflowerpassionfruitPassionistpassionlessPassiontidepassivatepassivepassive euthanasiapassive immunitypassive nounpassive reasonpassive resistancepassive restraintpassive smokingpassive transferpassive-aggressivepassive-aggressive personality Recent searches: View All
• See Also:
• Passion WeekpassionalpassionarypassionatepassionflowerpassionfruitPassionistpassionlessPassiontidepassivatepassivepassive euthanasiapassive immunitypassive nounpassive reasonpassive resistancepassive restraintpassive smokingpassive transferpassive-aggressivepassive-aggressive personality
• Passion Week
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• passive noun
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• See Also:

• Passion WeekpassionalpassionarypassionatepassionflowerpassionfruitPassionistpassionlessPassiontidepassivatepassivepassive euthanasiapassive immunitypassive nounpassive reasonpassive resistancepassive restraintpassive smokingpassive transferpassive-aggressivepassive-aggressive personality
• Passion Week
• passional
• passionary
• passionate
• passionflower
• passionfruit
• Passionist
• passionless
• Passiontide
• passivate
• passive
• passive euthanasia
• passive immunity
• passive noun
• passive reason
• passive resistance
• passive restraint
• passive smoking
• passive transfer
• passive-aggressive
• passive-aggressive personality

• Passion Week
• passional
• passionary
• passionate
• passionflower
• passionfruit
• Passionist
• passionless
• Passiontide
• passivate
• passive
• passive euthanasia
• passive immunity
• passive noun
• passive reason
• passive resistance
• passive restraint
• passive smoking
• passive transfer
• passive-aggressive
• passive-aggressive personality

• Recent searches:

• View All

1. not reacting to something expected to produce signs of feeling:He was passive enough to accept the boss’s abuse in front of everyone in the office.
2. not acting or participating much; inactive:a passive member of a committee.
3. Grammar(opposed to active) of, relating to, or being a voice, verb form, or construction that expresses an action that is done to rather than by the subject:In a passive sentence, the subject undergoes the action of the verb but does not perform it. In the passive sentence The letter was written last week, the subject letter does not perform the action, but receives the action of writing.

1. Grammar[uncountable] the passive voice.
2. Grammar[countable] a passive verb form or construction.

1. not reacting visibly to something that might be expected to produce manifestations of an emotion or feeling.
2. not participating readily or actively; inactive:a passive member of a committee.
3. not involving visible reaction or active participation:to play a passive role.
4. inert or quiescent.
5. influenced, acted upon, or affected by some external force, cause, or agency; being the object of action rather than causing action (opposed to active).
6. receiving or characterized by the reception of impressions or influences from external sources.
7. produced or caused by an external agency.
8. receiving, enduring, or submitting without resistance:a passive hypnotic subject.
9. Grammar noting a voice in the inflection of the verb in some languages which is used to indicate that the subject undergoes the action of the verb. Latin portātur, “he, she, or it is carried,” is in the passive voice.noting or pertaining to a construction similar to this in meaning, as English He is carried (opposed to active).
10. noting a voice in the inflection of the verb in some languages which is used to indicate that the subject undergoes the action of the verb. Latin portātur, “he, she, or it is carried,” is in the passive voice.
11. noting or pertaining to a construction similar to this in meaning, as English He is carried (opposed to active).
12. Chemistryinactive, esp. under conditions in which chemical activity is to be expected.
13. Metallurgy(of a metal) treated so as to impart impassivity.
14. Medicineof or pertaining to certain unhealthy but dormant conditions; inactive, as opposed to active or spontaneous.
15. Telecommunicationsdesigned to relay signals without electronic devices:a passive communications satellite.
16. Energy(of a solar heating system) accumulating and distributing solar heat without the aid of machinery.

• noting a voice in the inflection of the verb in some languages which is used to indicate that the subject undergoes the action of the verb. Latin portātur, “he, she, or it is carried,” is in the passive voice.
• noting or pertaining to a construction similar to this in meaning, as English He is carried (opposed to active).
• Chemistryinactive, esp. under conditions in which chemical activity is to be expected.

1. Grammarthe passive voice.
2. Grammara passive form or construction.

• Latin passīvus literally, submissive, equivalent. to pass(us) (past participle of patī to experience, undergo, submit) + -īvus -ive
• Middle English 1350–1400

1. not active or not participating perceptibly in an activity, organization, etc
2. unresisting and receptive to external forces; submissive
3. affected or acted upon by an external object or force
4. denoting a voice of verbs in sentences in which the grammatical subject is not the logical subject but rather the recipient of the action described by the verb, as was broken in the sentence The glass was broken by a boy Compareactive
5. (of a substance, esp a metal) apparently chemically unreactive, usually as a result of the formation of a thin protective layer that prevents further reaction
6. containing no source of power and therefore capable only of attenuating a signal: a passive network not capable of amplifying a signal or controlling a function: a passive communications satellite
7. containing no source of power and therefore capable only of attenuating a signal: a passive network
8. not capable of amplifying a signal or controlling a function: a passive communications satellite
9. (of a bond, share, debt, etc) yielding no interest

• containing no source of power and therefore capable only of attenuating a signal: a passive network
• not capable of amplifying a signal or controlling a function: a passive communications satellite
• (of a bond, share, debt, etc) yielding no interest

1. the passive voice a passive verb
2. the passive voice
3. a passive verb

• the passive voice
• a passive verb

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