AI won’t fix a broken supply chain foundation

The push for supply chain artificial intelligence investments is not facing a lot of pushback from the finance office, but it is facing scrutiny on the return being generated.

“The COO is getting money from the CFO using the word AI,” Al Mendoza, U.S. & Americas supply chain leader for EY, told Supply Chain Management Review in an interview at the Gartner Supply Chain/Xpo Symposium last month. “Now the CFO is coming back and saying, ‘Where’s my return on investment?’”

AI investment is similar to any other investment where the finance leaders expect to see a return on investment. That could be cost savings, streamlined operations, or transformational change. But, while companies are investing aggressively, they are still falling short on documenting the transformational gains they initially expected.

“What we’re finding is … 96% are still finding value,” Mendoza said. “It’s just not the transformational value they thought there was going to be.”

Investment is high, but clarity is not

Despite continued macroeconomic and geopolitical uncertainty, supply chain remains a top priority in the C-suite. Mendoza pointed to strong investment trends, noting that a significant share of companies are committing more than $10 million to artificial intelligence initiatives. At the same time, he described a market still searching for direction.

“I think there’s an overall lack of clarity exactly where the market is going,” he said. “It’s very clear that it’s going to be more digitized and more AI, but how that translates into value is still evolving.”

That uncertainty is leading many organizations into what Mendoza described as a fragmented approach—pursuing isolated use cases rather than cohesive transformation.

Technology alone is not the differentiator

For companies chasing competitive advantage, Mendoza said the technology isn’t often the answer.

“The moat isn’t that I have the best technology because that can be replaced in five minutes,” he said. Instead, the differentiators are less flashy and more difficult to build.

“It’s really, do I have the culture? Do I have the management systems? Do I have the data? Do I have the standardization?” he said, emphasizing that these foundational elements are what allow companies to sustain performance and continuously improve.

This is where many organizations fall short. While nearly all are investing in new tools, fewer are investing with the same intensity in the operating model required to make those tools effective.

The rise of the “value blueprint”

To address that gap, Mendoza described a shift in how EY is working with clients—moving from isolated use cases toward what he called a “value blueprint” approach.

“It’s really hard for companies to backdoor into transformation,” he said. “If you have a lot of very interesting use cases, you’re going to get stuck in very interesting use case land.”

The alternative is to step back and rethink processes end-to-end. Mendoza described it as “opening up the aperture.” That means reimagining workflows such as forecast-to-fulfillment or order-to-cash from a zero-based perspective, aligning supply chain, finance, and technology into a unified strategy.

“Here’s my big vision,” he said. “How do all my use cases enable me to be moving toward that?”

AI success starts with the problem

Even with the momentum behind AI, Mendoza reinforced a principle that continues to surface across the industry: the most successful companies are those that start with the problem, not the technology.

Referencing a well-known Einstein quote, he added: “I spend 95% of my time thinking of the problem and 5% solving it.”

That mindset is critical in avoiding what he described as underachieving AI programs that deliver incremental improvements but fail to move the business in a meaningful way.

“If your solve is very nuanced, very small, it’s not going to bring that transformational value that you need,” he said.

Workforce reinvention

One of the impacts of AI adoption is its impact on the workforce. Mendoza pushed back on the idea that automation is primarily about replacement, instead framing it as a shift in skill requirements. “What we’re going to create are users that need to have breadth of their skillset and real expertise,” he said.

That shift requires companies to rethink how they train and develop employees, particularly as labor shortages persist across supply chain functions. Leading organizations, he noted, are investing in upskilling rather than relying solely on external hiring. They are also capturing institutional knowledge and tracking where human intervention occurs so they can use that data to digitize and automate decision-making over time.

The foundation problem

If there is a central point to AI investment, it is that the most important work in a transformation is the least visible work, and that makes it harder to justify to the CFO.

“It’s so much cooler to design the house than to pay for the foundation,” Mendoza said.

That foundation includes standardized processes, clean data, and management systems that empower employees to execute consistently. It is also where many transformation efforts stall, particularly when faced with short-term financial pressures.

“There will be something with higher ROI that you can pick from,” Mendoza acknowledged. “But sustainable ROI is a different way to look at it.”

Supply chain’s opportunity

The current environment is marked by disruption, cost pressure, and shifting demand, but it has elevated supply chain’s importance within organizations. Mendoza noted that the vast majority of CEOs now see supply chain as materially impacting financial performance. Yet despite that visibility, supply chain leaders still face a challenge: translating operational impact into strategic influence.

“We have gotten invited to the boardroom,” he said. “We’ve got to add value when we’re there.”

That means moving beyond cost discussions and demonstrating how supply chain contributes to growth, customer experience, and speed to market.

“We need to bring in how we are part of the organic growth mindset that the C-suite really has,” he said.

The bottom line

AI may be driving urgency and unlocking budgets, but it is not, by itself, delivering transformation. The companies pulling ahead are those willing to do the harder work: aligning strategy, investing in people, and building the operational foundation that allows technology to scale.

Or, as Mendoza put it, the real challenge isn’t accessing AI, it’s building something that can return measurable value.

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