Published on the 08/10/2026 | Written by Heather Wright

Risk mitigation, not efficiency, the killer app…

“Anyone who is dependent on supply chains and the logistical risk [involved], needs to deploy agentic AI in order to reduce that risk. It’s as simple as that.”

It’s a bold statement, but according to Ilan Oshri, director of the Centre for Digital Enterprise at the University of Auckland Business School, local organisations are overlooking what could become agentic AI’s most valuable business application.

“Agentic AI in the supply chain should actually be positioned as a risk mitigation capability – that is where we’re going to see the biggest return.

While much of the discussion around agentic AI has focused on productivity gains, procurement automation and operational efficiency, Oshri argues businesses need to flip their thinking. For New Zealand and Australian organisations operating in an increasingly volatile global environment, the bigger opportunity may be using AI agents to continuously monitor, assess and respond to supply chain risk before disruptions reach the bottom line.

“Most companies think ‘let’s pilot agentic AI where we don’t have high risk. We’re saying you’ve got it wrong when it comes to procurement. You need to try it out,” he told iStart.

Oshri’s research into how agentic AI could transform procurement as part of global research for Boston Consulting Group, found organisations should start agentic AI deployments in areas with high transaction volumes and rich data environments, rather than low-risk experimental projects.

“Our findings are actually the opposite,” he says. “Where there are a high degree of transactions is where companies are actually supposed to start, simply because of the dependency on data in order to make agentic AI beneficial for the company.” That high data guides agentic AI to learn ‘really quickly’ reducing the level of errors significantly.

For local businesses however, Oshri believes the strongest use case is not procurement automation. Instead, he argues agentic AI should be viewed as a risk management capability.

“In the case of New Zealand, agentic AI in the supply chain should actually be positioned as a risk mitigation capability – that is where we’re going to see the biggest return, at least at this point in time.”

His argument reflects the realities of the smaller, geographically remote economies, heavily dependent on global trade, shipping routes and international suppliers.

From freight disruptions and geopolitical tensions to supplier issues and logistics bottlenecks, local organisations face risks that can emerge with little warning and quickly impact operations.

Using exporters as an example, he notes their need to get product to other countries. Freight costs are built into pricing, but what happens if emerging threats affect logistics, shipping costs or supply availability. Likewise, plenty of product is shipped to A/NZ to form part of products made here, and could benefit from similar agentic offerings.

“These kinds of agents basically do the scanning all the time and raise flags whenever they think a risk is going up.

Today, much of that monitoring is still performed manually or outsourced to specialist providers. Agentic AI could provide organisations with a constantly operating early-warning system capable of identifying risks – and taking action – before they become expensive disruptions.

“This is where possibly the highest benefit will be for companies.”

In the current environment, Oshri believes that capability is becoming increasingly important.

“Unfortunately, geopolitically, we are in the big surprises era at the moment,” he says.

While onboarding suppliers, managing contracts and automating routine procurement tasks all have value, he argues those applications are all ‘vanilla’ and relatively straightforward.

“You need to do that. But the big buck is the big surprises.”

Procurement should lead

The research also challenges traditional approaches to technology ownership. Historically, digital and IT teams have led major tech implementations across support functions. Agentic AI in procurement is different.

“We’re saying loud and clear that procurement needs to be the owner of the implementation of agentic AI,” Oshri says.

The reason, he argues, is simple: procurement teams understand the data they hold and the supplier relationships, business processes, contracts and operational risks in ways technology teams do not.

“Data scientists will make assumptions about the algorithm in terms of the ability to develop it and they will make assumptions about what data is needed in order to train it. That’s not the right approach to come up with an efficient AI-based solution.

“For this kind of technology, the approach should be completely different than what we have seen in ERP and what we have seen in RPA… It’s about do you understand what you have so the algorithm can actually behave according to the business process.

“It’s only procurement people who can answer that.”

An uncomfortable conversation about autonomy

Perhaps Oshri’s most controversial argument is that organisations also need to start thinking beyond human-supervised AI.

Current deployments typically are largely ‘human in command’, with some ‘human in the loop’. In either case people retain oversight of decisions and outcomes. Oshri believes many businesses are avoiding a more difficult discussion about autonomy.

“When we hear autonomous, I think many of us feel uncomfortable,” he says. “One reason for that is that we’re thinking if it is autonomous, that people just lost their jobs and it doesn’t sound right.”

He argues the transition towards greater autonomy is inevitable.

“As difficult as it is to think about, I think this is probably the future. We are moving towards that.”

Oshri says organisations should be honestly assessing which processes genuinely require human involvement and which could eventually be trusted to autonomous agents.

His view is that businesses often default to human-centred models because of concerns about the consequences, not necessarily because the technology is incapable.

“In many of the cases, we could have gone autonomous and we would have been actually providing outcomes that would not fall below the standards that we have built for human in the loop or human on the loop,” he says. “We are tilting towards the human-centred approach simply because we are struggling to cope with the consequences.”

It’s an argument likely to provoke debate among business leaders concerned about accountability, governance and workforce impacts. But Oshri believes the conversation is one organisations can no longer avoid.

For local businesses, the Oshri’s broader message is clear. The real value of agentic AI may not be found in making procurement processes a little faster or a little cheaper. Instead, it may lie in helping organisations anticipate disruption, manage uncertainty and build resilience in an era of increasingly unpredictable global supply chains.

And for companies exposed to those risks, Oshri’s advice is unequivocal: Deploy it.