Agentic AI as a tool for more resilient supply chains in procurement in New Zealand
An analysis on The Conversation describes how agentic AI could speed up the detection of supply chain problems from weeks to hours. Procurement in New Zealand remains largely manual, while abroad companies are already piloting or deploying agents.
A commentary on The Conversation, written by an author who contributed to the BCG 2026 Tech Procurement Study, describes the potential of agentic AI to improve supply chain resilience in procurement in New Zealand. According to DHL Export Barometer data, 87% of New Zealand exporters faced higher transport costs over the past year, and only 7% avoided supply chain disruptions. The author argues that procurement — the process of selecting suppliers, terms, and alternatives — is a key element of resilience in a small, trade-dependent economy, but it remains largely manual and under-resourced.
According to the BCG study, which surveyed more than 200 procurement professionals, most foreign businesses are already piloting or deploying agentic AI in procurement — agents for finding and vetting suppliers, evaluating bids, analyzing contracts, and tracking risks. The author states that while the manual cycle of identifying a problem and finding a new supplier takes weeks, a risk-monitoring agent can continuously track shipping data, news, and supplier registries and shorten detection to hours; a supplier-sourcing agent can compile and vet alternatives within days.
According to the author, the study found that performance results were similar regardless of whether companies developed agentic AI in-house, co-developed it with a partner, or purchased it as a managed service. At the same time, however, a difference emerged in internal expertise: 46% of companies developing solutions in-house rate their capacity as fully sufficient, compared with 7% for co-development and 6% for externally purchased solutions, with in-house organizations operating the most autonomous agents. Respondents cited fragmented data, outdated software, and governance as the main barriers, and 71% of them mentioned trust in autonomous decision-making as an obstacle, along with security, regulatory uncertainty, and accountability.
Why it matters
For companies dependent on long and vulnerable supply routes, faster problem detection and faster identification of alternative suppliers mean smaller economic losses during disruptions. According to the author, agentic AI also enables even smaller procurement teams (e.g., three-person teams) to handle work that previously required far more people, which is relevant for companies without the resources of large multinational corporations.
Two audiences, two different impacts
What this means
For individuals
For procurement and purchasing professionals, the text implies a need to build knowledge about how AI agents work, the data they process, and their decision-making processes, even when a company buys the technology as a ready-made service.
For a business
Companies dependent on imports or exports may consider deploying agentic AI in procurement for supply chain risk monitoring and faster identification of alternative suppliers, but according to the study they must also address internal barriers such as fragmented data, outdated systems, and insufficient trust in autonomous decision-making.
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Event sources
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