Business Magazine

Why We Will Be Seeing a Radical Reinvention of Supply Chains

Posted on the 24 January 2025 by Phil's Stock World @philstockworld
  • Artificial intelligence (AI) and generative AI can transform logistics byoptimizing supply chains with real-time pricing, predictive planning and enhanced safety while boosting sustainability.
  • Quantum computing will accelerate innovation using advanced algorithms and faster computation to revolutionize logistics efficiency, traceability and crisis management.
  • Robotics and humanoids will take over repetitive tasks, reduce costs and drive safety, requiring new social contracts and reshaping the workforce.

Global supply chains are on a growth trajectory due to increased consumption and population. With this change comes a need to enhance production and improve planning, execution, collaboration and performance efficiency.

Customer expectations for speed and efficiency are driving momentum, while the need to improve performance on sustainability is receiving increasing focus.

The multimodal logistics industry is excessively fragmented and has historically carried significant process and information technology debt compared to other leading industries, such as financial services and automotive.

However, with new advancements in artificial intelligence (AI), generative AI (GenAI) and other technologies, there is an opportunity to leapfrog and scale efficiency gains while reducing one's carbon footprint.

As AI and artificial general intelligence (AGI) capabilities become more affordable and accessible, new pragmatic opportunities to optimize pathways for the movement of goods, improving sustainability and cost-efficiency, are arising.

Over the last few years, with the affordability and access of high-performing graphics processing units (GPUs), AI and AGI are increasingly becoming widespread and pervasive in edge computing (where data is stored and processed closer to the user than remote data centres) through mobile devices.

The predictability and convenience offered by AI have been well received. While the impact on security and society is still being assessed and regulations are catching up, productivity improvements are evident in daily life.

AI is getting embedded in the fabric of enterprise estates and end-user devices. It impacts approximately 20% of enterprises' transactions, according to a 2024 ThreatLabz report.

Advanced use cases such as early detection of demand signals for autonomous order generations, enhancing safety by detecting faults and anomalies in vessels and railcars, and preventing potential losses or damages are some new capabilities leveraging AI.

The computational speed enables the development of digital twins for networks and supply-demand scenarios, facilitating better planning, utilization and resilience. Fusion algorithms improve accuracy by reducing the mean absolute percentage error, providing higher demand-supply matching precision and minimizing waste.

AI significantly enhances predictability in the transfer of goods by improving the accuracy of arrival times and reducing delays. AI-based pricing algorithms offer smart, real-time pricing, effectively lowering movement costs and minimizing areas of cost leakage.

GenAI's slow but sure takeover

GenAI's advancements are happening rapidly. Despite warnings, there is no stopping GenAI as the system matures to handle complex linguistic capabilities and create contextual responses, which is a phenomenal boost to productivity levels.

GenAI agents are gradually increasing their presence in enterprises, projected to grow from 5% to 25% of transactions in the next three years with faster adoption, according to Infosys research. They demonstrate capabilities to think, analyze, empathize, reason, behave, talk and engage like humans under pragmatic supervision.

GenAI improves customer experiences through contextual and proactive communication about shipments and their status. Automating document generation, leveraging GenAI and blockchain integration, streamlines cross-border transactions, minimizing disruptions and ensuring seamless movement of goods.

Union contract management and business rule implementation - mechanisms that are specific to the logistics industry - have been simplified, enabling rapid rule enactments and self-service queries for employees, reducing manual intervention. Current advancements in GenAI are enhancing interactions with employees, customers, suppliers and logistics providers, driving speed and efficiency.

GenAI also plays a significant role in image analytics. Recent advancements in image recognition and video content generation enhance defect detection quality through consistent learning and faster correlations. Image processing capabilities are advancing drone adoption for stock inspections, asset inspections and damage or warranty management.

" The morphing of information technology to industrial robotics will be rapid in the next decade and enterprises must be prepared to avoid an existential crisis. "

The dawn of quantum computing

With GPU adoption, the speed of AI execution has dramatically improved. GPU and chip makers are racing to innovate faster and better. Quantum computing will enhance this, amplifying the computational power of AI and GenAI and increasing speed and agility in logistics.

It will improve the management of ledger-based transactions (blockchain) and enhance traceability for manufacturers and retailers. It will also support inventory control and authenticity verification.

Shor's algorithm can handle large numbers and enhance transaction security, enabling secure handling of shipments and manufacturing of sensitive products. Grover's algorithm can enhance the creation of digital twin capabilities to simulate crises and generate opportunities, improving organizational response and mitigation strategies.

This technological evolution will revolutionize the management of multimodal logistics and supply chains, driving technological adoption. The only point of challenge will be the cost of compute until it reaches a point of scale.

The evolution of robotics

Robots were projected to displace 85 million jobs by 2025, which we can expect to increase. Humanoids will initially be viable where safety concerns exist and they will consistently react and interact to execute decisions.

They will become an option for lower-level jobs, reducing costs, improving customer experience and continuously learning and improving. This will also necessitate new forms of social contracts regarding human and humanoid management.

Robotics will be enhanced to handle monotonous jobs, such as packaging, sorting and put-away. The adoption of dark warehouses, unmanned loading or unloading and assembly points is expected to increase, improving safety in hazardous environments by leveraging robotics.

Managing transformation

The morphing of information technology to industrial robotics will be rapid in the next decade and enterprises must be prepared to avoid an existential crisis.

Improving collaboration, communication and planning across multimodal transportation will be a global focus area that will unlock potential and enhance supply chain efficiency. Geopolitical developments must address labour shortages and promote availability and localization by harnessing quantum computing capabilities and humanoid technologies.

This poses a conundrum as more machines will increase the energy consumption per capita. However, the efficiency advantage they provide will outweigh their environmental impact.


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