Digital twins are changing industries like manufacturing, healthcare, and aerospace by providing solutions that enhance operations, boost efficiency, and enable predictive capabilities across various sectors. According to GlobalData, the global digital twins market is projected to grow at a compound annual growth rate (CAGR) of 35.6%, increasing from USD 5 billion in 2019 to USD 154 billion by 2030.
This market growth will be fueled by the availability of low-cost sensors in Internet of Things (IoT) devices, decreasing expenses for high-performance computing (HPC), and improved cloud accessibility. Additionally, advancements in data analytics and artificial intelligence (AI) will contribute to this expansion.
Aisha U-K Umaru, a Strategic Intelligence Analyst at GlobalData, noted, “Large companies such as Amazon have tapped into their reach and reputation to partner with firms such as Matterport and Anthropic to enhance their digital twin offerings, and smaller companies such as Aerogility are providing services to specific industries such as aerospace and defense.”
Digital twins have been around conceptually for decades, with early examples used during NASA’s Apollo 13 mission to the moon in 1970. Although they are not yet widespread, their adoption is growing across various sectors.
Umaru added that digital twins are utilized in multiple industries, including oil and gas, energy, sports, and government. They serve diverse functions, from improving factory efficiency to enhancing the viewing experience for sports fans. The integration of AI into digital twins is becoming more common, providing users with greater context.
This has led to the development of hybrid technology, known as semantic twins, which allows users to ask large language models (LLMs) questions about a digital twin and its components. In response, the LLM can utilize its knowledge of the twin, its objectives, and its broader understanding of systems and the world.
For instance, a semantic twin of a city might be asked, “How can I update this twin to align with other cities that have similar populations and transportation systems managing traffic congestion more effectively?” Semantic twins also benefit from generative AI (GenAI) features, such as advanced predictive analytics and information retention.
Umaru concluded, “AI is pervading almost every industry, and it can offer more depth to digital twins. Semantic twins can allow users to draw deeper meaning from their digital twins, using LLMs for support.”