Artificial intelligence

NEC Launches AI Agent Platform for Supply Chain Management

NEC has unveiled the NEC SCM AI Agent solution for managing supply chain tasks through an orchestrating agent that relies on seven sub-agents, while keeping final decisions in the hands of employees. The annual price starts at 18 million yen, and the company aims to sell the solution to 100 companies within five years.

2026-09-18
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NEC Launches AI Agent Platform for Supply Chain Management

NEC announced the launch of the NEC SCM AI Agent solution for supply chain management, a system based on an orchestrating artificial intelligence agent that distributes tasks among seven specialized sub-agents. The company presented the solution at CEATEC JAPAN 2026, held from September 8 to 11, 2026, alongside the start of its availability to customers.

The solution targets companies facing complexity in supply chain management as a result of differences in business processes among sectors such as manufacturing, distribution, and retail. NEC believes that relying on a single standardized system does not always accommodate these differences, while some organizations still collect data manually in Excel spreadsheets or coordinate procedures through phone calls and email.

How Does the Solution Work?

The orchestrating agent, which NEC calls Orchestrator AI, analyzes a task and divides it among sub-agents dedicated to different areas. Examples cited in the presentation include demand forecasting, production planning, and inventory management, along with other tasks related to supply chain workflows.

In one scenario, the artificial intelligence agent detects the possibility of a shortage of a component and then reports the result to the orchestrating agent. Tasks such as adjusting the production plan or changing the order quantity are then distributed to specialized agents, instead of requiring the employee to follow every step separately.

NEC says the system does not replace all existing systems at once. If a customer uses an existing supply chain management system and another system for production management, the two can be connected through application programming interfaces (APIs) to use the agents within the existing environment.

Humans Remain the Final Decision-Makers

The sub-agents present their results to employees, including risks or proposed actions. The system may generate several options, such as changing the production plan or increasing the inventory quantity, before a human reviews them and confirms the final decision. This mechanism shows that the role of artificial intelligence in the solution focuses on collecting and analyzing data and coordinating actions, rather than completely eliminating human oversight.

NEC also noted that moving AI functions into a single system is not a requirement. The company currently provides functions for seven sub-agents and is working to expand them in line with each customer’s needs. As for the security and governance controls associated with using artificial intelligence in existing systems, the company says it will provide them through the AI Platform Service.

What Changes in Practice?

NEC presents the solution as a coordination layer above multiple processes and systems, rather than as a new system that completely replaces the existing infrastructure. This may reduce the scale of change required during implementation, but it makes the solution’s value dependent on data quality, systems integration, and the definition of permissions among the agents.

The annual price starts at 18 million yen, with the price varying according to the volume of data used. NEC aims to deploy the solution at 100 companies within five years, focusing on large, small, and medium-sized companies.

certi.news reading: The fundamental change here is the shift of artificial intelligence in supply chain management from the standalone use of a language model to a multi-agent architecture that distributes tasks and coordinates them. However, the source does not specify measured operational results, such as the extent of cost reductions or improvements in forecasting accuracy, nor does it provide deeper details about data security or the mechanism for evaluating the agents’ decisions. Therefore, the solution’s practical viability will depend on the integration of each customer’s systems and its ability to review the proposals before implementing them.

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MONOist Japan
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