The shift from conversational chatbots that only answer questions to “AI agents” that autonomously reason and use tools when given a purpose is rapidly progressing in the enterprise field by the second half of 2026. While the use of AI so far has been limited to “assistants that assist humans with their homework,” the latest autonomous agents are beginning to take on the role of directly driving business processes themselves.
On the front lines: A dramatic change in the supply chain that automatically links everything from order receipt to procurement
One area where notable changes are being seen is in supply chain management. Some major manufacturing companies have put into practical use a system in which multiple AI agents communicate with each other to optimize material procurement. For example, a monitoring agent'' that detects a delay in the delivery of parts due to bad weather can delegate the task to a negotiation agent’’ that automatically selects an alternative supplier and creates a draft order in minutes that takes into account the balance between procurement costs and delivery dates. Humans only need to press the final approval button, and decision-making lead time has been shortened from several days to several tens of minutes.
System design evolving from a single tool to “multi-agent collaboration”
The biggest technological turning point is the shift from a configuration in which everything is left to a single large-scale language model (LLM) to a multi-agent architecture in which small and medium-sized models with specialized roles work together. By having an ``orchestrator’’ who brings together specialized agents such as those in charge of research, data analysis, code generation, and quality verification, overseeing the entire process, it has become possible to complete long, complex workflows while greatly reducing the risk of hallucinations (plausible lies). The in-house API and protocols for linking with existing SaaS have been standardized, and the foundation for securely accessing business databases via plug-ins has been created, which is also supporting its widespread use.
The boundaries of governance and decision-making authority facing the second half of 2026
On the other hand, the governance design associated with agents operating internal systems autonomously is an urgent issue. The creation of operational rules such as to what extent an agent is allowed to execute independently'' and how to define responsibility in the event of a failure or incorrect order placement’’ are the focus of discussion in many information systems departments. In the future, the development of a policy management engine that controls the degree of freedom of autonomous execution in stages according to the criticality of the business, and ensuring traceability that allows the agent’s thought process to be audited, will likely become differentiating factors that will determine a company’s competitiveness.