Digital twins are used across manufacturing, construction, healthcare, energy, transport, software, education, marketing and customer experience. They can be built using sensors, cloud platforms, data models, AI tools, simulation software, avatars, voice technology and connected systems.
This guide explains what a digital twin is, how it works, the main types, how it differs from AI, and how businesses can use digital twins in practical ways.
TLDR: What Is a Digital Twin?
A digital twin is a virtual representation of a real object, system, process or person. It uses data to mirror, monitor, simulate or recreate something from the real world in a digital environment.
In simple terms, a digital twin is a digital version of something real.
For example, a manufacturer may create a digital twin of a machine to monitor performance, predict faults and test changes before applying them in real life. A business may create a human digital twin using an AI avatar, voice clone and multilingual video workflow to communicate at scale without filming every message manually.
A digital twin usually includes:
- A real-world subject
- Data from or about that subject
- A digital model
- A connection between the real and digital version
- Software that displays, analyses or generates outputs
- A way to use the insights in the real world
Some digital twins update in real time. Others are updated manually, periodically or when new content is needed.
Digital Twin Explained Simply
The easiest way to understand a digital twin is to imagine a living digital version of something real.
A wind turbine, for example, may have sensors that collect data on temperature, vibration, wind conditions and energy output. That data is sent to a digital model of the turbine. Engineers can then see how the turbine is performing, spot unusual behaviour and test how it may react in different conditions.
A human digital twin works differently but follows the same basic idea. Instead of sensor data from a machine, it may use video recordings, voice samples, facial movement, appearance, speech patterns and approved scripts. These inputs can create a digital version of a person for videos, training, presentations, marketing or multilingual communication.
Nertia’s Digital Twin service focuses on high-fidelity human digital twins, combining visual avatars, voice modelling and multilingual video production.
How Does a Digital Twin Work?
A digital twin works by connecting real-world information to a digital representation. The exact process depends on what is being represented, but most digital twins follow the same core stages.
1. Define What the Digital Twin Represents
The first step is to decide what the digital twin will represent.
This could be:
- A machine
- A product
- A building
- A vehicle
- A production line
- A supply chain
- A customer journey
- A business process
- A person
The business also needs to define the purpose of the twin. For example, the goal may be to reduce downtime, improve energy use, test a workflow, create training material or produce videos without repeated filming.
2. Collect the Right Data
The digital twin needs relevant information from or about the real-world subject.
For physical digital twins, this may include:
- Sensor readings
- Equipment data
- Temperature
- Vibration
- Energy use
- Location
- Maintenance records
- Environmental conditions
For process digital twins, the data may come from:
- CRM systems
- Workflow tools
- Analytics platforms
- Operational reports
- Customer interactions
- Transaction history
For human digital twins, inputs may include:
- Video footage
- Voice recordings
- Photographs
- Facial expressions
- Speech patterns
- Mannerisms
- Approved scripts
- Brand messaging
The quality of the digital twin depends heavily on the quality of the data. More data is not always better. The data needs to be accurate, relevant and suitable for the intended use.
3. Build the Digital Model
The collected information is used to create a digital representation.
Depending on the project, this model may be:
- A 3D model
- A dashboard
- A simulation
- A process map
- A data model
- An AI avatar
- A voice model
- A combination of several technologies
A digital twin of a machine may focus on performance and component behaviour. A digital twin of a person may focus on appearance, voice, delivery style and language.
4. Connect the Model to Data
The digital model is then connected to relevant data sources.
This connection may happen:
- In real time
- At regular intervals
- When new information is available
- Through manual updates
- During a specific content or simulation workflow
Not every digital twin needs live data. A factory twin may need continuous updates from sensors. A human digital twin used for video production may only need updates when new scripts, recordings or language versions are created.
5. Analyse, Simulate or Generate Outputs
Once the digital twin is built, it can be used to produce useful outputs.
These may include:
- Monitoring performance
- Detecting unusual activity
- Predicting maintenance needs
- Testing different scenarios
- Comparing possible outcomes
- Identifying inefficiencies
- Producing video content
- Creating translated versions of a message
- Supporting customer communication
Artificial intelligence may be used to recognise patterns, make predictions, generate speech, create video or process language.
6. Apply the Insight
A digital twin becomes valuable when its outputs lead to a useful action.
For example:
- A maintenance team repairs a machine before it fails
- A building manager reduces energy use
- A logistics team changes a delivery route
- A business improves a slow customer journey
- A founder creates multilingual videos using a human digital twin
- A website uses an AI chatbot to answer visitor questions
The purpose is not just to create a digital copy. The purpose is to improve visibility, decision-making, communication or performance.
Digital Twin Process at a Glance
| Stage | What Happens | Example |
|---|---|---|
| Define | Choose the real-world subject and goal | Monitor a machine |
| Collect | Gather useful data | Temperature and vibration data |
| Model | Create the digital representation | A virtual machine model |
| Connect | Link data sources to the model | Live sensor updates |
| Analyse | Find patterns or simulate outcomes | Detect unusual vibration |
| Act | Apply the insight | Schedule maintenance |
Digital Twin vs Digital Model
A digital model is a digital representation of something. A digital twin is usually more dynamic because it has a meaningful connection to real-world data.
| Feature | Digital Model | Digital Twin |
|---|---|---|
| Represents something real | Yes | Yes |
| Uses real-world data | Sometimes | Usually |
| Updates when conditions change | Not always | Often |
| Supports monitoring | Limited | Common |
| Supports simulation | Sometimes | Common |
| Can support prediction | Limited | Possible with analytics or AI |
A 3D model of a building is not automatically a digital twin. It becomes closer to a digital twin when it connects to information such as occupancy, temperature, energy use, maintenance status or user behaviour.
Digital Twin vs Simulation
A simulation tests how something may behave under certain conditions. A digital twin may include simulation, but it is usually connected to a specific real-world subject.
| Digital Twin | Simulation |
|---|---|
| Represents a real object, process, system or person | May represent a general scenario |
| Can use live or historical data | Often uses assumed data |
| May update over time | Usually runs for a specific test |
| Can support monitoring | Mainly supports testing |
| Can include several simulations | Usually one part of a wider model |
For example, a simulation may test how a generic engine performs in high heat. A digital twin may use data from one specific engine to test how that exact engine is likely to perform.
Digital Twin vs AI
A digital twin is not the same as artificial intelligence.
The digital twin is the representation. AI is one of the technologies that may help the twin analyse information, predict outcomes, generate content or interact with users.
A digital twin does not always need AI. A simple digital twin may display live performance data. A more advanced digital twin may use machine learning to forecast problems.
For a human digital twin, AI may help with:
- AI avatar generation
- Voice cloning
- Text-to-speech
- Lip synchronisation
- Translation
- Video dubbing
- Script generation
- Interactive responses
Platforms such as HeyGen, Synthesia, ElevenLabs and DeepL show how avatar, voice and translation technologies can support modern digital communication workflows.
Types of Digital Twins
Digital twins can be grouped by what they represent.
Component Digital Twin
A component twin represents one individual part, such as a motor, battery, pump, turbine blade or vehicle component. It helps teams understand how that specific part performs.
Asset Digital Twin
An asset twin represents a complete physical asset, such as a vehicle, machine, wind turbine, building system or medical device. It can show how different components work together.
System Digital Twin
A system twin represents a group of connected assets or environments. Examples include factories, warehouses, energy networks, transport systems and buildings.
Process Digital Twin
A process twin represents a workflow or sequence of activities. It may be used to analyse sales processes, customer onboarding, logistics, manufacturing workflows or support operations.
Customer Digital Twin
A customer digital twin represents patterns in customer behaviour, preferences, journeys or interactions. Businesses must use this type responsibly, with clear privacy and data practices.
Human Digital Twin
A human digital twin is a digital representation of a person. In business communication, this may include an AI avatar, voice clone, facial movement, multilingual dubbing and approved messaging.
This type of digital twin can help founders, trainers, educators, sales teams and brands produce consistent content without recording every video manually.
What Technology Powers Digital Twins?
Digital twins are usually built from several connected technologies.
Sensors and IoT Devices
Sensors collect information from physical objects and environments. This may include movement, temperature, speed, vibration, pressure, humidity, sound or energy use.
Cloud Platforms
Cloud services provide storage, processing power and access across teams. Platforms such as Microsoft Azure Digital Twins and AWS IoT TwinMaker are designed to help create digital representations of physical environments and systems.
3D Modelling and Simulation
3D models and simulation tools help teams visualise objects, buildings, factories and environments. NVIDIA Omniverse is one example of a platform used for industrial digital twins and robotics simulation.
Industrial Digital Twin Software
Industrial platforms, such as Siemens Digital Twin, are used to model, simulate and optimise products, processes and systems before making changes in the real world.
AI and Machine Learning
AI can help digital twins recognise patterns, predict problems, generate content, translate language and provide recommendations.
APIs and Integrations
APIs allow digital twins to connect with websites, dashboards, CRM systems, analytics tools, maintenance platforms, support systems and mobile applications.
Avatar, Voice and Translation Tools
Human digital twins use visual and voice technologies to represent a person. These may include AI avatar generation, voice cloning, lip-syncing, text-to-speech and multilingual dubbing.
Example: How a Machine Digital Twin Works
Imagine a company wants to reduce unexpected breakdowns in a production machine.
The process could work like this:
- Sensors collect temperature, vibration and output data.
- The data is sent to a digital model of the machine.
- The system compares current readings with normal operating patterns.
- Analytics detect unusual behaviour.
- The digital twin predicts a possible fault.
- The maintenance team reviews the warning.
- The machine is inspected before a full breakdown happens.
The digital twin does not repair the machine itself. It gives the team better information so they can act earlier.
Example: How a Human Digital Twin Works
Imagine a founder regularly records product explainers, training videos and company updates.
A human digital twin workflow may involve:
- Recording the founder on camera
- Capturing facial expressions and presentation style
- Recording their voice
- Creating a visual avatar
- Creating an approved voice model
- Writing a script
- Generating a video using the avatar and voice
- Reviewing the final output
- Translating or dubbing the video into other languages
This allows the founder to produce more content without being present for every recording session.
For this to be done responsibly, the person being represented should give informed consent. The business should also define who can use the digital twin, what it can be used for and how approvals are managed.
Digital Twin vs AI Avatar
An AI avatar is a visual representation of a person or character. A human digital twin is usually broader.
| AI Avatar | Human Digital Twin |
|---|---|
| Primarily visual | Combines appearance, voice and behaviour |
| May use a generic voice | Can use an approved voice model |
| Often used for video | Can support training, sales and communication |
| May be fictional | Usually based on a real person |
| Can be standalone | May connect to scripts, knowledge and workflows |
Not every AI avatar is a digital twin. The term is more appropriate when the digital version is meaningfully connected to a real person and represents several parts of their identity or communication style.
For a deeper comparison, read AI Avatars vs Chatbots: What’s the Difference?
Digital Twin vs Chatbot
A digital twin represents something real. A chatbot is a conversational interface designed to answer questions and guide users.
| Digital Twin | AI Chatbot |
|---|---|
| Represents an object, process, system or person | Manages conversations |
| May be visual, operational or data-based | Usually text or voice based |
| Can support simulation and monitoring | Supports communication |
| Does not always interact with users | Built for interaction |
| May include a chatbot | Can operate without a digital twin |
The two can work together. For example, a chatbot could answer website visitor questions, while a human digital twin presents key information through video or voice.
Nertia’s AI Chatbot Maker helps businesses create website chatbots that answer questions, guide visitors and support customer journeys.
Benefits of Digital Twins
Digital twins can help businesses improve how they monitor, plan, communicate and scale.
Key benefits include:
- Better visibility across systems, assets or content workflows
- Safer testing before applying changes in the real world
- Earlier problem detection
- More informed decisions
- Reduced downtime
- Improved efficiency
- More consistent communication
- Scalable content production
- Stronger multilingual reach
- Better customer education
For human digital twins, the main benefit is repeatable communication. A person can deliver approved messages across videos, training materials, sales content and languages without recording from scratch every time.
Challenges and Risks of Digital Twins
Digital twins can be powerful, but they need to be planned carefully.
Common challenges include:
- Poor data quality
- High technical complexity
- Integration requirements
- Cybersecurity risks
- Privacy concerns
- Inaccurate assumptions
- Ongoing maintenance
- Cost control
- Consent and identity protection
Human digital twins need extra care because they involve a person’s likeness, voice and identity. Businesses should have clear permission, approval workflows and usage rules before creating or publishing content.
How Much Does a Digital Twin Cost?
There is no single standard price for a digital twin.
The cost depends on:
- What is being represented
- The amount of data required
- Whether live data is needed
- The complexity of the model
- The quality of the visual output
- The number of integrations
- AI or prediction requirements
- Security and compliance needs
- Ongoing maintenance
- Content volume
An industrial digital twin connected to thousands of sensors may require significant infrastructure and specialist development.
A human digital twin for video, voice and multilingual content is often more defined because it follows a clearer production workflow.
The best starting point is to define the use case first. A focused digital twin is usually more valuable than an overcomplicated system with no clear purpose.
Where Are Digital Twins Used?
Digital twins are used across many sectors, including:
- Manufacturing
- Energy
- Transport
- Construction
- Property
- Healthcare
- Retail
- Logistics
- Education
- Software
- Media
- Professional services
Their purpose changes depending on the industry. Some are used to monitor assets. Others are used to simulate processes, improve customer journeys or produce scalable communication.
For more practical examples, read Digital Twins for Business: Use Cases and Real-World Applications
How Digital Twins Can Be Used on Websites
A digital twin can become part of a wider digital customer experience.
A website could include:
- A video avatar introducing the business
- A digital spokesperson explaining services
- Multilingual video content
- Product demonstrations
- Training videos
- Interactive guides
- An AI chatbot for common questions
- Personalised onboarding content
The technology should support the user journey. It should not be added just because it looks impressive.
A digital twin works best when it helps visitors understand, trust or take action. If your website is unclear, slow or difficult to navigate, the digital twin will not fix the experience on its own.
Nertia’s website design and development service helps businesses create clear, conversion-focused websites that can support video, content, chatbots and AI tools. You can also run a free SEO, AEO and GEO website scan to review your current website structure.
The Future of Digital Twin Technology
Digital twins are becoming more accessible as AI, cloud platforms, connected devices and no-code tools improve.
In the future, digital twins are likely to become:
- Easier to create
- More accurate
- More interactive
- More connected to business systems
- Better at prediction
- More useful for content and communication
- More realistic for human avatars
- More controlled through consent and identity systems
However, better technology does not remove the need for clear goals. The most useful digital twins are not built for novelty. They are built to solve a specific problem.
Create a Digital Twin Built Around Your Goals
A digital twin can help your business monitor systems, test ideas, create content, translate messages or communicate more consistently.
For human digital twins, quality, control and consent matter. Your digital presence should reflect how you look, sound and communicate while giving you clear oversight of where and how it is used.
Nertia creates bespoke digital twins using high-fidelity visual avatars, authentic voice modelling and multilingual video production.
Whether you need a digital spokesperson, scalable content workflow or guidance on how a human digital twin could support your business, explore Nertia’s Digital Twin service.
Frequently Asked Questions About Digital Twins
What is a digital twin in simple terms?
A digital twin is a digital version of something real. It may represent a machine, building, process, system or person and use data to monitor, simulate, predict or generate outputs.
How does a digital twin work?
A digital twin works by collecting data from or about a real-world subject, creating a digital model, connecting that model to relevant information and using software to analyse, simulate or generate useful outputs.
Is a digital twin the same as AI?
No. A digital twin is the digital representation. AI is a technology that may help the digital twin analyse data, make predictions, generate content or respond to users.
What is an example of a digital twin?
A factory may use a digital twin of a machine to monitor temperature and vibration so maintenance teams can detect faults earlier. A business may use a human digital twin to create videos, training content or multilingual presentations.
What is a human digital twin?
A human digital twin is a digital representation of a person. In business communication, it may combine an AI avatar, voice model, facial movement and approved scripts to create video or voice content.
Do digital twins always use real-time data?
No. Some digital twins use live data, but others use historical data, manually updated data or recorded content. The update frequency depends on the purpose of the twin.
What is the difference between a digital twin and an AI avatar?
An AI avatar is mainly a visual representation. A human digital twin is broader because it may include appearance, voice, mannerisms, language, approved knowledge and content workflows.
What are digital twins used for?
Digital twins are used for monitoring, simulation, predictive maintenance, workflow improvement, training, customer experience, website communication and scalable content production.
Are digital twins expensive?
Costs vary widely. A large industrial digital twin may require sensors, integrations and specialist infrastructure. A human digital twin for video and voice content may follow a more focused production process.
How can my business start with digital twins?
Start with a clear use case. Decide what you want the digital twin to improve, what data or content is needed and how the output will be used. For human digital twins, you can begin by speaking with Nertia about your goals, content needs and language requirements.