A synergy between tech tools and innovative solutions is essential for optimizing their efficiency and generating value for the business. Take generative AI and digital twins as an example: both technologies offer a range of massive benefits to the business on their own. Both have countless use cases in different industries when implemented properly, everybody knows that by now.
But what if you put the two together? Imagine the possibilities!
Let’s see how merging digital twins and generative AI can benefit organizations by enabling real-time insights and improving decision-making.
What is an AI Twin, and How Does It Work?
An AI twin is a digital copy of a physical object created to replicate certain processes and responsibilities usually performed by the object it copies. Think of the digital twin as a simulation taken a step further; it not only duplicates specific environments, people, or objects but can also perform some tasks and react to the changes in the environment.
There is more than one method for creating a digital twin, as it can require different types of data-gathering methods. A digital twin relies on inputs from devices such as Internet of Things sensors, wearable technology, and 3D modeling tools, as well as software capable of collecting, analyzing, and storing data.
Generative artificial intelligence is a subfield of AI technology that can generate images, texts, videos, presentations, and other complex content formats from scratch. It is commonly used to create promotional and educational materials. What if it could also generate test scenarios for digital twins to help you predict most if not all, use cases for your product? What if it could do more than that?
Advantages of Merging Generative AI with Digital Twins
Artificial intelligence affects numerous industries, including life sciences, education, engineering, and others. However, many still have yet to learn about the benefits of merging AI with digital twin technology—some of which we describe here:
Better scenario planning
GenAI’s vast capabilities enable digital twins to simulate a wider range of variables, conditions, and outcomes, allowing for many “what-if” scenarios to be explored. This way, users can research more options and come up with better solutions instead of relying on a couple of possibilities that represent just a fraction of potential situations.
Improved personalization
AI-powered digital twins offer more insights into users’ behavior, making it easier for companies and organizations to personalize their content, products, and services. For example, a virtual representation of a patient can give healthcare providers a better understanding of the individual’s needs and issues, allowing them to personalize treatment and approach the patient’s problem in a way the traditional model could never offer.
Saving resources
The GenAI’s capability to create multiple real-world scenarios allows digital twins to provide users with more sophisticated predictions, which leads to better savings of energy, money, materials, and many other resources. Here is how this goes: let’s imagine a healthcare organization created a digital representation of a medical facility’s power grids. Generative AI models merged with those virtual replicas can simulate peak loads and predict both short and long-term demand spikes. As a result, a hospital can save its energy and prevent system crashes avoiding spending on fixing the power systems.
More opportunities for innovation and creativity
Once you combine digital models with artificial intelligence, you can expect some unusual, unanticipated results from such a merge. Generative AI has the capability to come up with various ideas and predict multiple outcomes, while digital twins hold the power to create hyperrealistic representations of their physical counterparts. As a result, the combination of both offers an unlimited number of solutions to different problems, sometimes leading to new ideas and fresher perspectives.
Data-backed decision making
Digital twins augmented by generative AI can provide companies with unique insights into their products, services, and users. GenAI alone is a unique technology used by many already. 43% of CEOs state that they use generative AI to make informed strategic decisions, and 50% are currently making GenAI a part of their products and services.
How to Personalize Content Journeys with Video Avatars
An AI avatar is one example of how AI-powered twins can be integrated into a company’s workflows and operations, both internal and external. Here is a quick instruction on how you can easily create personalized content journeys with video avatars:
Step 1: Collect all the necessary data
What do you want to be a part of your video? Think about all the information you would like to include, as well as details about your target audience and its preferences. It’s crucial to ensure you know what your audience would like to see in the video, as its success depends mostly on whether anyone will actually view and share it.
Step 2: Write a script tailored to your audience
With your AI avatar, you can craft personalized messages and outstanding videos that help you promote your business and create unique content journeys. To make your video more useful and engaging, prepare a script beforehand and double-check all the information you include in it.
Step 3: Choose your avatar
With the eWizard content experience platform, you can customize your AI avatar and choose its appearance, voice, and other features. Depending on the software you use to create your avatar, you can personalize it to create a video tailored to your clients’ needs.
Step 4: Integrate dynamic content
Use dynamic elements to give your videos a personal touch. For example, you can add a personalized greeting, recommendations based on customer data, and even offers a viewer might be interested in. eWizard allows its users to quickly personalize any type of content and create customized AI avatars, making content more valuable and memorable.
Step 5: Monitor
Track viewer engagement metrics to assess the performance of your videos. Based on this data, you can find different approaches to creating video content and AI avatars, along with other ideas for implementing AI-powered digital twins into your journey.
GenAI and Digital Twins Use Cases
Digital twins provide limitless opportunities for creating different simulations of real-world situations. By merging GenAI and digital twin technology, it becomes possible to fully test all sorts of products and services prior to their launch. Let’s take a look at some cases where the combination of the two important technologies proves especially valuable.
Patient monitoring
Artificial intelligence plays a significant role in the healthcare and pharmaceutical industries. For instance, healthcare providers can use AI twins to create virtual models of their patients, continuously updated with real-time data. By reflecting the well-being of a patient in a simulation, AI twins offer unique insights into the individual’s health, such as any changes, even the smallest ones, improvements, distress, signs of other conditions, etc.
It’s possible to create such digital twins with the help of wearables, sensors, and other instruments that allow for quick data collection at long distances. This way, patients can stay at home and continue with their routine while still providing their healthcare provider with all the necessary information.
In this case, generative AI can be used for multiple purposes, such as personalization of the treatment plan based on the info given by the patient, predictions of potential issues before they manifest into serious conditions and diseases, and simulations of disease’s or condition’s progression and how it might affect the patient.
Product design
Once you decide to introduce a new product, it’s crucial to test it thoroughly before the official release. With digital twins, you can create a virtual model of the product or service you’re working on and see if it is ready for the market or needs a little bit more polishing.
In this scenario, generative artificial intelligence can recommend ways to improve your product, advise what you could change to make it more appealing, and analyze how well your target audience would react to a new offering.
Let’s say a health technology company is working on a new wearable device for tracking patients’ vitals. Digital twin technology can assess the device’s durability and comfort and test its design on different user groups. GenAI can propose new models and changes to the choice of materials, shape, and design, reducing the need for physical prototypes and helping create a better version of the product.
Content creation and personalization
AI and digital twins can serve as powerful tools for creating interesting and valuable content that’s tailored to specific audiences. Suppose you decided to launch a marketing campaign for a new pharma product across different channels. Your digital twin can act as a buyer persona that represents your real customers who might be interested in your content. The main task of this persona is to use behavioral data, such as purchase history, browsing and shopping habits, customer reviews, product views, and other information to create a profile of a potential customer. In this scenario, AI can complement digital twins by analyzing the unique insights they provide or by directly generating content for your future campaign to match the expectations of the buyer.
The Future of AI Twin and Possible Challenges
AI twins are still in the early stages of development, which is why there is still a lot left to explore and learn about artificial intelligence and digital twin combinations. Here are some potential challenges that could arise:
Poor quality data
Regardless of what you decide to replicate in the virtual world, how close it is to its physical version will heavily depend on the quality of the data provided. Moreover, GenAI’s predictive capabilities also rely on data quality, as it is impossible to make an accurate prediction without adequate data.
Well-organized networks
Digital twin technology is most beneficial when there are multiple twins that are all a part of a network. Interconnected digital twins can offer more insights into different scenarios and processes, as well as better reflect the state of systems, objects, and individuals they represent as a virtual model. However, for a network to be correctly organized and managed, it’s crucial to have a strong framework for connectivity and security, which might not be accessible to everyone working with digital twins.
Talent shortage
Only 28% of IT experts in the public sector consider themselves skilled in generative AI enough to use it as part of their job. As the demand for artificial intelligence grows, so does the need for experts in it. However, the talent supply cannot keep pace with the market needs, at least at the moment, causing significant skills shortages in many industries. Because of that, many companies simply cannot find enough experts to create AI-powered digital twins.
Safety concerns
Creating digital twins entails utilizing various data, which can sometimes be very sensitive and belong to individuals who need to consent prior to third parties accessing their personal information. For companies to effectively use AI twins, it’s important to ensure that their customers know how their data will be used and are comfortable with it. Many might be hesitant to share their data because of the fear of data leaks and potential misuse of their information, which is why companies planning to create digital twins must take care of safety issues first.
Siloed processes
It’s not enough to just create a digital model of something and make it a part of one process. Digital twin capabilities have the potential to affect multiple processes, so it does not make sense for a business to make AI-driven twins a part of just one workflow, task, or project. Doing so can lead to silos, miscommunication, limited predictive power, and even reduced agility and missed insights. Instead of taking a siloed approach to use AI twins, maximize their benefits by creating an integrated network with centralized monitoring and shared data protocols, helping employees across various teams learn more about this tool, its advantages, and how they can use it to improve decision-making and problem-solving.
Lack of knowledge
Before any kind of software technology or system is added to the roaster of your company’s tools, consider this question: why do you need it? AI twin is just one of the many buzzwords whose true value often goes unrecognized. Some don’t even realize that a digital twin is an umbrella term that encompasses all sorts of approaches to creating digital replicas and virtual representations. Because of this lack of expertise, many businesses fail to understand why they need AI twins and what they can do with them to make their business operations more efficient. Understanding exactly why your company needs any kind of tech is the first step towards success.
Summing Up
Many businesses already run simulations powered by AI and ML algorithms that assist them in making complicated decisions and improving their products. The powerful combination of AI and digital twins made it possible to see and analyze how objects interact with each other, predict potential outcomes of various scenarios, and reveal how some products and services are perceived by their users.
If you are ready to leverage the potential of AI-driven twins, message us now. Our team of experts will answer all your questions about AI, content creation, digital twins, and many more!
