AI-powered supply chains require work redesign, not just process automation

As supply chains face mounting pressure from disruption, geopolitical volatility, inflation, and changing customer expectations, companies are increasingly turning to artificial intelligence to improve decision-making and operational performance. But according to Blue Yonder’s Shri Hariharan, senior vice president-global solutions, the real opportunity is not simply applying AI to existing processes—it is fundamentally redesigning how supply chain work gets done.

“The problem isn’t technology,” said Hariharan, who has spent more than two decades at Blue Yonder in customer-facing and advisory roles. “The opportunity is how do you convert that technology and harness it by redefining work?”

Shifting demands

Hariharan said the role of supply chains inside organizations has shifted dramatically over the past several years, beginning with the COVID-19 pandemic and continuing through ongoing geopolitical and economic disruptions.

“The good news is that supply chains got a boardroom presence permanently,” he said.

But that visibility has also created new pressure on supply chain leaders to connect operational decisions to broader business outcomes, particularly as CFOs and boards increasingly scrutinize investments in AI and digital transformation.

Hariharan told Supply Chain Management Review in a meeting at the recent Gartner/Xpo Supply Chain Symposium that the issue is convincing the rest of the organization that a supply chain problem is impactful to the rest of the team, and then finding technological solutions to these problems.

Operational, financial disconnect

According to Hariharan, one of the biggest historical problems with supply chain technology deployments has been the disconnect between operational improvements and financial language understood by executive leadership.

Supply chain may know what it wants, but the the ROI doesn’t meet requirements expected by leadership. Hariharan argued that AI-driven supply chain transformation increasingly requires organizations to evaluate decisions not only through operational metrics, but also through their impact on revenue, margin, inventory, cash flow, and cost-to-serve.

“What does that total composite view look like to deliver business value?” he said. That includes helping companies understand the ripple effects of operational decisions across the enterprise.

As an example, Hariharan described how CFO-driven inventory reduction initiatives can unintentionally create downstream cost increases if organizations fail to evaluate the broader network implications.

“If I can improve customer fulfillment, can I do it by improving predictions so I make my forecast better and I can sense my demand better?” he said. “Can I reduce my expedited transfers? Can I reduce unplanned transfers?”

Scenario planning

To support those decisions, Blue Yonder is increasingly focusing on scenario-based planning and multi-variable optimization models that can evaluate hundreds of potential supply chain scenarios simultaneously.

Historically, Hariharan said, supply chain systems were not architected to evaluate complex trade-offs across multiple objectives at enterprise scale.

Cloud-native architecture and AI-enabled scenario modeling help companies analyze combinations of pricing, manufacturing, inventory, transportation, and distribution decisions while balancing operational and financial objectives.

“No human’s going to be able to run 300 scenarios in two days,” Hariharan said. “But what if technology could come to bear?”

But Hariharan said technology alone is not enough. One of the biggest challenges remains translating operational supply chain decisions into business language understood by executive leadership teams.

So how do supply chain organizations take what they are doing and convey that to the people who “don’t speak supply chain?”

Speaking CFO

Hariharan said Blue Yonder has increasingly focused on creating what he described as a “translation layer” that converts operational supply chain levers into enterprise business metrics.

“We’re converting very operational levers to what the business wants, which is what? Revenue, margin, cost to serve, cash to serve,” he said.

That focus on business outcomes is also reshaping how customers approach AI adoption itself. According to Hariharan, the market has shifted significantly over the past year from companies simply demanding AI capabilities to organizations asking where AI actually creates operational value.

“We’re kind of slowing down to go fast because everything looks like a nail right now,” he said.

Hariharan said many companies are beginning to recognize that accelerating broken or inefficient processes with AI does not necessarily improve business performance. “This can’t just be automation,” he said. “This has to be a recalibration of work because you can’t just speed up bad processes.”

One area receiving growing attention is what Hariharan described as autonomous sales and operations execution, or S&OE, where AI agents continuously evaluate operational conditions, monitor changes in demand and supply, and automatically generate updated trade-off analyses for planners and operators.

“What if you understood all the context factors of my business and you’re sensing for them and giving me automatic adjustment of my demand profile in the short term against real orders and inventory in the network?” he said.

Blue Yonder itself has also adjusted its internal strategy in response to those evolving customer demands. Hariharan said the company recently created a dedicated Supply Chain Advisory organization focused less on selling software and more on helping companies identify operational transformation opportunities.

“We saw the way the market was going, which is going from buying SaaS solutions to consuming SaaS solutions to driving business outcomes,” he said.

That includes embedding both product and domain experts directly with customers to evaluate how work is currently performed and where AI-enabled redesign opportunities exist.

“We don’t want to be a solution looking for a problem,” Hariharan said. “Everything looks like a nail and we got the hammer.”

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