High potential for AI in supply chain management

Growing adoption of AI is attributable to demand for better transparency and visibility in supply chain data and processes.

According to a new Transparency Market Research report, there is a lucrative opportunity for artificial intelligence (AI) in supply chain management (SCM) through to 2026.
Solution providers integrate AI technology in SCM to improve productivity and workflow. The term ‘artificial intelligence’ refers to the design of computer systems that can imitate human behavioral patterns by understanding the phenomenon of human intelligence.
AI can be divided into sub-fields: artificial neural networks (ANNs), machine learning, expert systems, fuzzy logic, and agent-based systems.
Maintenance is made easy due to automated processing, as regular repairs and upkeep are required for maintaining equipment. Artificial intelligence gathers information through sensors, which is combined with maintenance data. The best time to repair equipment in an organization is analyzed by the system, which is called predictive maintenance.
Inventory can be improved by reducing redundancy with the help of smart storage processing and deploying advanced technology. Furthermore, AI can track and maintain database of suppliers and shipping.

Growing adoption of AI is also attributable to factors such as demand for better transparency and visibility in supply chain data and processes.

Rising adoption of Big Data is another factor driving the use of AI for improving consumer services and satisfaction.
Moreover, increasing demand for accuracy and safety in warehouses will drive growth of AI in coming years.
However, a lack of awareness about developments in AI technology can be a restraining factor for market growth.

Market segmentation

The market can be segmented based on technology, which is divided into natural language processing (NLP), machine learning (ML), computer vision, and context-aware computing.
The computer vision segment is expected to expand at a high pace during the forecast period from 2018 to 2026, due to increasing adoption of computer vision for semi-autonomous or autonomous applications in several industries across the world such as automotive and manufacturing.
In terms of end-user industry, the market can be segmented into retail, consumer-packaged goods, health care, automotive, aerospace, manufacturing, and food & beverages.
The consumer-packaged goods segment is expected to expand at a rapid pace during the forecast period.
Geographically, the market can be divided into North America, Europe, Middle East & Africa and Asia Pacific.
Asia Pacific is expected to expand at a significant rate during the forecast period. Increasing adoption of deep learning and NLP technologies for use in automotive, retail, and manufacturing applications is driving the market in the region.

Key players

Key players are United Parcel (which uses AI to develop the most efficient route for its fleet); Rolls-Royce Motor Cars (which uses AI to safely transport its cargo); Blue Marble Logistics (which uses robots to deliver drugs, groceries, and packages with the help of AI); Lineage Logistics (which uses an AI algorithm that can forecast the time when orders arrive and leave a warehouse); and Infinera (which uses machine learning to analyze production times and logistics and predict delivery dates in a better manner).
SCM plays a vital role in the current age of high supply needs, which lead to increase in the degree of competition and demand uncertainty.
The SCM centers indicate an organization’s ability to integrate and organize processes of gathering materials; transforming them into finished goods; and delivering them to customers.
By identifying the growing significance of information with the success of SCM, experts have invested in technology for better management of information and making better business decisions.

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