The Latin America, Middle East and Africa Cognitive Supply Chain Market would witness market growth of 16.7% CAGR during the forecast period (2023-2030).
Cognitive supply chain systems can predict supply chain disruptions and help companies proactively address issues such as disruptions in the supply chain due to natural disasters, transportation delays, or unexpected demand spikes. AI-driven systems can help companies maintain optimal inventory levels, reducing excess stock and minimizing shortages, thus improving overall supply chain efficiency. Advanced algorithms can improve demand forecasting accuracy, assisting companies to align production and inventory with customer demand. AI-powered supply chain visibility enables businesses to trace shipments, monitor stock levels, and identify potential bottlenecks in real time. Some of these solutions utilize blockchain technology to improve supply chain transparency and traceability, particularly in industries where origin and authenticity are crucial, such as the food and pharmaceutical industries.
These systems can analyse historical data, market trends, and external factors to improve demand forecasting accuracy. This helps organizations better anticipate product demand, optimize inventory levels, and reduce stockouts or overstock situations. These solutions use real-time data and predictive analytics to optimize inventory levels. They can automatically reorder stock, reduce carrying costs, and minimize supply chain disruptions. In manufacturing and logistics, cognitive supply chain systems can predict equipment failures and maintenance needs based on sensor data and historical performance. This reduces unplanned downtime and maintenance costs. These applications of these technologies are helping businesses improve efficiency, enhance customer satisfaction, and adapt to the ever-changing dynamics of the global supply chain. They are particularly valuable in industries with complex and extensive supply chain networks, such as manufacturing, retail, logistics, and healthcare.
Saudi Arabia’s Vision 2030 plan includes initiatives to diversify the economy from oil dependency. As a result, there is a growing focus on developing the logistics and transport sectors to support non-oil industries, such as manufacturing, retail, and tourism. The increasing transport and logistics industry in Saudi Arabia has contributed significantly to the country’s supply chain management and technology demand growth. Saudi Arabia’s strategic geographic location and ambitious economic diversification and development plans have spurred a substantial increase in the transport and logistics sector. As a result, the abovementioned factors expand the market’s growth in this region.
The Brazil market dominated the LAMEA Cognitive Supply Chain Market, By Country in 2022, and would continue to be a dominant market till 2030; thereby, achieving a market value of $398.8 million by 2030. The Argentina market is showcasing a CAGR of 17.4% during (2023 - 2030). Additionally, The UAE market would register a CAGR of 16.4% during (2023 - 2030).
Based on Deployment Type, the market is segmented into On-premise, and Cloud. Based on Technology, the market is segmented into Internet of Things (IoT), Machine Learning, and Others. Based on Enterprise Size, the market is segmented into Large Enterprises, Small & Medium-sized Enterprises. Based on Vertical, the market is segmented into Manufacturing, Food & Beverage, Logistics & Transportation, Retail & E-commerce, Healthcare, and Others. Based on countries, the market is segmented into Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include SAP SE, Oracle Corporation, Accenture PLC, IBM Corporation, Intel Corporation, NVIDIA Corporation, Honeywell International, Inc., C.H. Robinson Worldwide, Inc., Amazon.com, Inc. and Panasonic Holdings Corporation
Scope of the Study
Market Segments covered in the Report:
By Deployment Type

  • On-premise
  • Cloud


By Technology

  • Internet of Things (IoT)
  • Machine Learning
  • Others


By Enterprise Size

  • Large Enterprises
  • Small & Medium-sized Enterprises


By Vertical

  • Manufacturing
  • Food & Beverage
  • Logistics & Transportation
  • Retail & E-commerce
  • Healthcare
  • Others


By Country

  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA


Companies Profiled

  • SAP SE
  • Oracle Corporation
  • Accenture PLC
  • IBM Corporation
  • Intel Corporation
  • NVIDIA Corporation
  • Honeywell International, Inc.
  • C.H. Robinson Worldwide, Inc.
  • Amazon.com, Inc.
  • Panasonic Holdings Corporation


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