Integrating technologies that include blockchain, AI, and IoT is driving the transformation of supply chain management. Researchers, tech companies, and businesses are participating in driving the transformation, because of its potential to improve operational efficiencies and ESG. -Gerald Donald

There are integrated blockchain, artificial intelligence (AI), Internet of Things (IoT), and smart contracts projects either in development or partially initiated in supply chain management. But they are not completed projects because the technologies (especially AI and IoT) continue to evolve, and implementing the complex integrated technologies takes a large amount of resources, such as a high-level infrastructure supporting data collection and analysis. However, the insights from the work done to date showcase the potential uses of these technologies and adaptation to global supply chains. The technologies are driving a fully digitized and connected supply chain ecosystem that is self-orchestrated. The research and development projects go beyond tracking the movement of goods and lowering transaction costs. They improve transparency, reduce fraud, ensure compliance with regulations, and improve security, and may lead to supply chain management that is chiefly tech-driven. They can also help companies drive environmental sustainability and diverse supplier inclusion throughout the supply chain, increasing accountability.

Tracking Tuna Fish to Demonstrate the Power of Integrated Technologies

Projects can take many forms. Researchers empirically studied Thailand’s tuna fish supply chain to identify how AI and blockchain technology (BCT) could be leveraged to improve end-to-end operations and material and data-handling processes. What the researchers learned presents a vision of the future of supply chains across industries. They mapped the business processes and material, data, and information flows that could benefit from the application of AI and BCT, reflecting the trend in global businesses to rely on interactive decision-making based on the use of real-time data flowing from multiple sources for things such as risk minimization and avoiding product recalls. In this project, the integration of AI is especially valuable in the food industry, as consumers and governments demand verifiable transparency and traceability evidence concerning product safety and quality.

The tuna fishing sector was chosen because many fishers fail to comply with regulations and illegally catch and sell fish due to a lack of transparency. The Thai fish industry needs technology-enabled traceability and analytics, because fish exports are a significant economic contributor at $6.3 billion. A few years ago, the EU temporarily stopped Thai fish imports because of the “magnitude of illegal, unreported, and unregulated fishing activities.” Implementing an end-to-end supply chain system to track and trace seafood enabled by BCT and AI would modernize the sector and improve export opportunities. The approach to enabling the technologies was to first capture the fish supply network ecosystem features, identify the role of AI and BCT implementations in data and information that fits operational objectives, and devise a method for measuring the supply chain impact. The unified framework implementation required sensory infrastructure for BCT, like radio-frequency identification, complemented by AI to enable tamperproof automated data collection and analysis.

The implementation of combined BCT and BCT revealed that fish supply chains would support improved sustainability performance by reducing data gaps. It would also enable data inoperability by integrating data inconsistencies. The integrated framework would also produce more realistic market and operations scenarios to inform decision-making and enhance competitiveness. The researchers believe implementing integrated AI and BCT could apply to many industries, including pharmaceutical, automotive, agriculture, and aerospace.

Need for Transparency

The need for transparency drives the combination of blockchain, AI, and IoT. PwC discusses hyperconnected networks, which are built with an infrastructure of networks, AI, blockchain, and IoT to process information combined with other technologies such as 5G, cloud, and mesh networking. An example of the possibilities for supply chains are retailers able to confirm that products can move safely and quickly from the manufacturing plant to the warehouse to the retail stores. Another example is the hyperconnected network enabling machine-to-machine interactions on a massive scale. The networks can monitor performance, optimize operations, and order parts before the equipment breaks down.

The Maverix AI and machine learning analytical module is being developed for supply chain data analysis. The module will utilize machine learning algorithms to identify trends and patterns, predict future supply chain performance, and identify areas for improvement. The module predicts potential supply chain disruptions by monitoring real-time supply chain data from IoT devices. Gray Matter will augment a customer’s supply chain data with open-source data like air pressure and weather. The initial use cases are inventory management and predictive maintenance, but the module will expand the use cases over time. Maverix also uses Smart Contracts.

Challenges to Overcome but Visions of the Future Are Here While the research project involving the Thai fish industry was not an implementation, it carefully identified the major challenges any supply chain manager would have to address, like the need for adequate data storage capacity and scalability, security weaknesses, legal issues, data privacy, and agreement of the participants. There is also a need for financial resources, legal and regulatory compliance, organizational readiness, standardization, and professional knowledge of BCT and AI. As if that is not enough, organizations must also consider product governance, scalability, interoperability, and latency. The flow of data and information As for the potential return on investment (ROI) of the technology-integrated supply chain systems, it is impressive. Blockchain technology has the potential to save businesses billions of dollars in transaction fees, reduce fraud, and increase efficiency. Looking forward, the future of integrated technology looks promising. Many experts predict that we will see more integrated technologies solutions in supply chains in the coming years, especially in the areas of finance, healthcare, and supply chain management. These solutions will continue to improve transparency, security, and efficiency and will likely significantly impact various industries.

Visionaries are already looking ahead to moving from AI to the metaverse as the future of the global supply chain. Cindy He is an Industry and Innovation Analyst at ANZ Bank and researches emerging technologies and trends disrupting the financial services and banking industries. She describes the first step as achieving the ability to monitor operations in real-time. This gives enterprises “on-demand access to rich data” in the end-to-end supply chain, including all supplier tiers, manufacturing and warehouse operations, logistics partners and routes, shipments, containers, and critical documents. It also provides ESG transparency and the ability to anticipate disruptions and assess macroeconomic events like extreme weather, trade sanctions, and military conflicts. Integrating blockchain, AI, and the IoT can make it possible for supply chains to utilize technologies to plan, respond, and make decisions in response to real-time events. There are fintechs that are already simulating an end-to-end supply chain in an AI-power metaverse by creating a digital twin for access and collaboration.

The Unfolding of the Future of Supply Chain Management

The full utilization of powerful technologies in supply chain management has a long way to go. Companies and researchers are working on innovative solutions, so there is no doubt that AI, IoT, and blockchain will have expanding roles in supply chain management. The transformation has already started, and the more data scientists and tech developers explore the possibilities, the more efficient the supply chain will become.