Automated Negotiation for Future Supply Chains
Figure 5-4: Vision of an AI agent for demand-fluctuation response in global logistics. The agent coordinates across six stakeholder roles— supplier, buyer, warehouse, factory, freight forwarder, logistics provider— and consumes a separate supply-chain risk feed. The negotiation-and-coordination primitive is shared with Pattern 1( deliverydate adjustment) and Pattern 4( ERP-embedded SOM); the extension here is to the multi-stakeholder logistics layer. EARLY-STAGE EXPLORATION— not yet a product of NEC.
5 MACHINE CUSTOMERS AND THE RE-SHAPING OF B2B COMMERCE
The four patterns above describe automated negotiation as it is deployed today. Sections 6 and 7 turn from current practice to its forward-looking implications.
Gartner publicly launched the concept of machine customers at its 2022 CSO & Sales Leader Conference [ 35 ], defining them as non-human economic actors that can autonomously negotiate and purchase goods and services in exchange for payment. Don Scheibenreif, Distinguished VP Analyst at Gartner, has consistently argued that machine customers are not a futuristic curiosity but a near-term re-shaping of how revenue is generated. Gartner ' s most recent forecast— featured in its Top Predictions for IT Organizations and Users in 2026 and Beyond— states that by 2028, 90 % of B2B buying will be AI-agent intermediated, pushing over $ 15 trillion of B2B spend through AI-agent exchanges. The earlier, often-quoted projection that by 2030 machine customers will be responsible for 20 % of revenue for many enterprises [ 35 ] is the predecessor to this one.
Three implications of the machine-customer view matter for supply chain leaders:
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