What's next for Digital Twins?

Digital Twins are not a new concept in the industrial setting or in the world of supply chain specifically. They have been evolving for many years, but now AI is supercharging them, turning Digital Twins into more than just representations of assets or processes.

What started as static interpretations has evolved into dynamic tools that are critical for business efficiency and a true source of competitive advantage. Their impact is, and will continue to be, amplified by technologies such as IoT, autonomous robotics, machine learning, computer vision, and of course, AI - including agentic AI.

Together, these advancements transform Digital Twins from simple 3D mappings into dynamic systems that enable greater accuracy, proactive decision-making, operational efficiency, and more sustainable practices in warehouses.

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The evolution of the Digital Twin

A Digital Twin is, simply put, a virtual model of a virtual representation of a real-world process, system or physical object'. The concept in itself is older, but it was officially introduced in manufacturing in 2002, while the term was coined only later, in 2010. 

The history of warehouse designing, planning and mapping goes from CAD (Computer-Aided Design) tools, to BIM (Building Information Modeling) - both static and without any live features integrated, to adding data layers on top of BIMs, by using sensors and WMS, and finally to dynamic Digital Twins. 

As more data-collecting, sensing and intelligent technologies have started to enter the warehouse, Digital Twins have started to evolve to become an operational system, a LIVE replica of the warehouse. 

In 2017, the concept of an IoT-based warehouse testbed was introduced (PhyNetLab). In 2019, Digital Twins have then been named a “key strategic trend”. Then, in 2020, DHL announced its first Digital Twin of a warehouse in the Asia-Pacific region. In 2023, Maersk was “rolling out a digital twin simulation product that predicts what will happen operationally in the near term.”

As Digital Twins started showing benefits, the adoption and development of these solutions has accelerated.

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AI changes the game for everyone

The global Digital Twin market is projected to reach USD 155.84 billion by 2030. North America currently leads adoption, accounting for roughly 32% of the market in 2024, but the gap is narrowing, as access to technology and data gets increasingly democratised for players of any size or from any part of the world.

A major driver of this trend are robotics, AI and agentic AI. With these advancements, Digital Twins are no longer passive replicas of a warehouse; they have become active operation engines, powered by real-time data analysis, predictive scenario modeling, and automated decision-making. 

Real-time information from autonomous data-gathering robots and camera systems keeps twins in sync with reality. Once limited to static digital mappings, modern warehouse twins can now “see” what’s happening on the floor, anticipate issues, optimise processes, and continuously learn and improve - becoming the backbone of the adaptive warehouse.

Warehouse managers have access to more operational data than ever before, faster and with greater accuracy, but the true leap forward comes when AI ties all the inputs together. 

Modern Digital Twins act as centralised, single sources of truth - not just 3D representations, but intelligent platforms that can flag inventory discrepancies, detect risks, send alerts, and analyse storage patterns and space utilisation. 

The AI-twin becomes a central point of truth and decision making, driving improvements across the board.

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The case for AI-powered Digital Twins

By using automated, continuous scanning, warehouses can maintain a better stock accuracy. For example, DB Schenker, a global logistics company, improved their accuracy substantially by 6% after implementing real-time scanning robots and Digital Twin technology. Warehouses that are able to see in real time what’s happening with their stock better track the status of their goods and make more informed decisions, knowing the system reflects reality.

The new intelligent type of twin shows data, but also monitors for problems. By leveraging AI, computer vision and robotics, it’s easier now to detect anomalies, such as misplaced stock, fall risks, over-stocking or damaged goods. There’s less room for surprises - the twin catches errors faster, can alert the staff and prevents downstream mistakes. This also has the benefit of saving time for employees, leading to up to 41% reduction in manual investigations.

Mapping the space and knowing how it is used in real time allows the twin to highlight underutilised areas to make room for more storage without the need to expand footprint. An AI-twin can analyse slotting patterns helping managers understand how to place inventory to minimise travel distance, for example. 

Furthermore, understanding how resources are consumed supports managers in reducing the warehouse’s environmental impact -  “digital twins can help to reduce the greenhouse gas emissions and carbon footprint of an existing building by up to 50 per cent, alongside cost savings of up to 35 per cent.” (source).

Finally, when warehouse managers have access to consolidated, refined, real-time data, they can make better decisions faster and respond more effectively to potential disruptions. A Digital Twin can forecast how demand is likely to evolve and highlight the best strategies to remain agile in a volatile e-commerce market. This means decisions are no longer made in blind, based on assumptions, or using outdated information. 

When agentic AI is introduced, some of these decisions can even be automated, further streamlining operations. For example, if the system detects that a major sales event is approaching, it can automatically trigger restocking of high-demand products to ensure supply keeps pace with anticipated demand.

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Real-life case study

AI-powered Digital Twins are already deployed in multiple big players’ warehouses. In 2025, Vente-unique.com, a top-tier online furniture and home décor retailer, implemented DexoryView. 

“Errors and delays can result in reduced customer experience, which can impact profitability. We needed a solution that provided real-time data without disrupting operations.”

- Cyrille Mazal, Supply Chain & Customer Service Director, Vente-unique.com

By using autonomous robotics and a Digital Twin interface, operations became more agile. The robots started capturing high-resolution data without interfering with daily activities. The AI-powered Digital Twin generated live updates on the inventory, stock locations and item movements. The system was integrated smoothly in the existing workflows and in just 3 days of the initial test, accuracy was improved from 92% to 98%, and the site has now reached 99.9% inventory accuracy.

“Thanks to Dexory’s autonomous robots, we have not only achieved exceptional inventory accuracy but also optimised our ability to perform full inventories several times per week.”

- Cyrille Mazal, Vente-unique.com

‍Read the full case study here.

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The road ahead for AI-twins

Digital Twins have evolved from simple planning tools into advanced management solutions. Paired with AI, robotics, and real-time data, they now deliver a live, dynamic replica of the warehouse - one that can be continuously analysed, optimised, and improved.

The benefits are already clear: higher inventory accuracy, smarter use of space and resources, and greater operational resilience. Advances in agentic AI and robotics are paving the way for truly “adaptive” warehouses, where Digital Twins not only flag issues but also generate insights and trigger responses in real time.

In this new model, the intelligent AI-driven twin becomes a central pillar of warehouse management. The boundary between the physical and digital all but disappears, creating real-time feedback loops, proactive decision-making, and a more competitive operation. For managers yet to invest in Digital Twin technology, there’s no better time to start than now.

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Ready to gain more visibility than ever, with autonomous robots and AI-powered digital twins? Learn more here.