Transforming Global Supply Chains: The Role of AI, Computer Vision, and Digital Twin Technology
The global supply chain is moving through a major transformation phase, characterized by tariffs, rising trade restrictions, and evolving technological landscapes. As businesses adapt to these myriad changes, the adoption of advanced technologies can make the difference between success and stagnation within this dynamic environment.
According to Erez Agmoni, co-founder and general partner at Interwoven Ventures, a pioneering strategy for trade stakeholders to enhance operational efficiency and respond adeptly to disruptions is by harnessing the synergistic power of Artificial Intelligence (AI), computer vision, and digital twin technologies. This trio is revolutionizing how businesses manage and optimize their supply chains.
So, what exactly are these technologies? A digital twin is essentially a virtual representation of a physical entity—in this case, a supply chain. It acts as a live simulation that mirrors real-world processes, allowing organizations to analyze performance and predict outcomes based on various inputs and scenarios. On the other hand, AI-powered computer vision provides machines with the ability to interpret images and videos, effectively mimicking human visual judgment.
Agmoni highlights the potential of integrating these technologies: “The intersection between AI, digital twins, and computer vision is quite amazing… The more data you input, the better your scenarios become for resolving disruptions. Whether it’s a war, tariffs, or a pandemic, these technologies allow us to respond effectively.” This adaptability is crucial in today’s fast-paced world, where market conditions can shift rapidly.
Interwoven Ventures is centered in New York and focuses on backing early-stage companies that drive technological advancement in healthcare, manufacturing, logistics, and transportation sectors. Prior to this, Agmoni held the significant role of global head of innovation at Maersk, where he led initiatives to incorporate advanced technologies into the company’s extensive supply chain ecosystem.
Drawing from his experiences at Maersk, Agmoni emphasizes the importance of identifying specific problems before implementing solutions. “You have to ask yourself, ‘what is my problem?’ The introduction of a digital twin should never be just for show. It should serve to tackle genuine challenges.” This problem-first approach guides organizations in effectively measuring success and finding targeted solutions.
The digital twin market in the U.S. is currently booming, with projections indicating growth from $3 billion in 2023 to $36 billion by 2028, according to MarketsandMarkets. Meanwhile, the AI computer vision market also anticipates significant expansion, potentially soaring from $23.42 billion in 2025 to $63.48 billion by 2030.
One of Agmoni’s initial applications of AI computer vision at Maersk was to streamline the unloading process of containers in a cross-dock operation. Faced with varying reports on the time required to unload containers—ranging from six to eleven hours—Agmoni realized the lack of clarity was an issue. “They didn’t even know how long it actually took,” he noted. This was a classic example of a problem that could be addressed with smarter monitoring and operational efficiency.
Agmoni adds that streamlining cross-docking operations requires precise data on factors like how many containers need to be split for various destinations, the number of cartons in each, and the weight of each box. To tackle this complexity, Maersk deployed smart cameras throughout the facility, allowing the AI system to learn the operational behaviors over several months.
After eight months of data gathering, the results were astounding; the AI system achieved 82% accuracy in minute-by-minute predictions. This level of insight allowed supervisors to measure employee productivity and incentivize performance improvements, reshaping the entire unloading operation.
In addition to enhancing unloading procedures, Maersk also leveraged digital twin technology to optimize its drayage operations. Agmoni explained, “Each drayage operation involves navigating multiple ports, terminals, and warehouses. Historically, they had to operate across 13 different systems to coordinate everything, which limited their throughput to just 1.8 turns a day, a figure that was far from optimal.”
Agmoni’s efforts led to the development of a digital twin that provided complete visibility over the drayage operation. “This alone saved millions of dollars,” he stated. By consolidating all relevant information into a single system, the company was able to make more informed decisions about dispatching loads, ultimately maximizing operational capacity and efficiency.
One of the most valuable features of digital twin technology is its ability to simulate various scenarios. Agmoni elucidates, “You can throw new elements into the current real-life situation and let the system simulate it, offering insights that guide decision-making.” Whether tweaking pricing strategies or altering operational parameters, the capacity to visualize potential outcomes transforms risk management within the supply chain.