AI and the Supply Chain: A New Path to Business Performance

So much is being written about how AI will displace millions of jobs, reshape entire functions, and eventually automate large parts of how companies operate. But I’d rather look at the other side of the story, the positive side.

AI will absolutely change work, but it will also create new roles, elevate existing ones, and remove the inefficiencies that have slowed organizations down for decades. In the supply chain, AI isn’t replacing people; it’s removing waste, improving insight, strengthening decision-making, and giving teams the tools to run the business with stronger business acumen.

And nowhere is that impact clearer than in the core financial engines of the company.

The impact of AI on the supply chain isn’t theoretical; it’s real, it’s happening, and it will directly influence business performance. The clearest way to understand that value is to look at the two places that determine the health of any company: the income statement and the cash flow statement.

AI improves how products are sourced, manufactured, moved, and delivered. And every one of those decisions ultimately shows up as revenue, Cost of Goods Sold (COGS), operating expenses, or cash on hand. That’s why leaders need stronger business acumen to understand, interpret, and act on AI-driven insights.

That’s the story leaders should be focused on. Here’s how AI is transforming business performance where it matters most.

1) AI Drives Revenue by Making the Supply Chain Smarter

Revenue growth depends on a company’s ability to anticipate demand, meet customer expectations, and keep product flowing without disruption.

AI strengthens revenue by enabling:

• More accurate demand forecasting, incorporating hundreds of signals humans can’t track manually.
• Improved case fill rates, ensuring product is available where and when customers want it.
• Better promotions planning, tying marketing investments to operational realities.
• Proactive risk management, identifying supply disruptions before they hit the shelf.

Example:
A consumer goods company using AI to integrate point-of-sale data with supply data increased regional availability by 9%, resulting in millions in incremental sales.

2) AI Helps Manage COGS Through Smarter Production & Sourcing

COGS is one of the most difficult parts of the P&L to control. Fluctuating material costs, production inefficiencies, and unpredictable lead times create a constant challenge.

AI improves COGS performance through:

• Predictive sourcing models that analyze supplier risk, tariffs, commodity trends, and total landed cost.
• AI-assisted production scheduling that reduces changeovers, waste, and downtime.
• Energy and resource optimization, lowering variable manufacturing costs.
• Real-time quality insights to reduce scrap, rework, and returns.

Example:
A manufacturing network using AI scheduling reduced line downtime by 15%, improving throughput and lowering per-unit cost.

3) AI Reduces Operating Expenses Through Automation & Operational Efficiency

Operating expenses rise when supply chains run reactively. AI helps eliminate those inefficiencies.

AI lowers Opex by:

• Automating manual planning tasks that previously required hours of spreadsheet work.
• Optimizing transportation routes and loads, reducing freight costs.
• Detecting ordering, shipment, and invoicing anomalies before they become expensive.
• Reducing expediting, overtime, and emergency production runs.

Example:
A global retailer using AI logistics optimization cut expedited freight costs by 28% within the first year.

4) AI Strengthens Cash Flow Through Precision Inventory and Faster Conversion Cycles

While cash flow isn’t on the income statement, it is the fuel that powers growth, innovation, and resiliency.

AI drives cash improvement by:

• Optimizing safety stock dynamically at every node of the supply chain.
• Reducing excess and obsolete inventory, freeing trapped working capital.
• Improving forecast accuracy, enabling leaner, more balanced inventories.
• Accelerating the cash conversion cycle, reducing the time between investment and cash realization.

Example:
A distributor using AI for inventory optimization released $30M in working capital without sacrificing service performance.

Summary

AI is reshaping supply chain performance where it matters most—on the income statement and in the flow of cash. It’s improving revenue, reducing COGS, lowering operating expenses, and freeing up working capital. And as companies adopt these tools, AI won’t eliminate talent; it will create new roles in analytics, digital operations, and insight-driven decision-making.

This is exactly why business simulations are so valuable: they help leaders practice using AI-enabled insights to run a smarter, more profitable supply chain before applying those decisions in the real world.