The AI Investment Gap
Supply chain is one of the first places companies point new AI investment. It is chaotic, data heavy, and expensive to get wrong, which makes it an obvious target and a hard one to get right.
Forrester's Landscape names the obstacle directly: "orchestrating internal and external stakeholders with their own processes and views of data remains a challenge" and that it takes "time and courage to build trust to share data about demand signals and capacity in tiered supply chains" (The Supply Chain Platforms Landscape, Q2 2026). That is not a modeling problem. It is a context problem.
Supply chain data is split across suppliers, carriers, ERPs, and spreadsheets that were never built to share a common view. Feed an AI system a partial picture of that network and it will not fail loudly. It will make a confident, well-reasoned, wrong call: an allocation that ignores a carrier delay, a reorder that misses a compliance change, a forecast built on a demand signal that was already out of date. In a supply chain, the cost of a wrong inference is not a bad recommendation. It is a stockout, a chargeback, or a shipment that lands at the wrong dock at the wrong time.
Disruption Is Raising the Stakes
Oil price swings and ongoing trade volatility keep changing the cost and availability of supply with little warning, and every shift moves through every tier of the network. Closing the gap between AI's promise and its return takes three things working together:
Resilience, so the network can absorb a shock without every company scrambling on its own.
Visibility, so disruption is visible as it happens, not weeks later in a report.
Performance data that closes the loop, so what happened this cycle actually changes what gets ordered, allocated, or rerouted next time.
Forrester's Landscape reinforces why this matters now: "supply chain variety, volume, and variability demand more integrated, swift, and sophisticated decision-making" (The Supply Chain Platforms Landscape, Q2 2026). Complexity and disruption are the operating conditions that were previously viewed as the side effect.
Customers report the same shift already underway. According to our customer research, 88% now operate proactively, up from a majority who described their operations as reactive before.
What Forrester's Landscape Shows
The Supply Chain Platforms Landscape, Q2 2026 gives technology executives an independent view of 40 vendors. Each is listed against the capabilities that matter most across five core use cases: fulfill, orchestrate, order, plan, and source. Real-time connectivity and visibility are named as primary functionality across the majority of those use cases, and performance and risk data sharing are named as primary for planning specifically, an independent, vendor-neutral look at exactly the gap described above.
Where SPS Fits
The SPS Commerce network carries three layers of context most companies can't assemble on their own: a customer's own supply chain activity, often more complete on the network than in their own ERP; patterns across the broader network that reveal what normal and what risk actually look like; and nearly three decades of what causes a disruption or compliance failure in practice, not just in policy.
That context is already built into products in market today, not on a roadmap. MAX, an agentic AI layer built into the network, is grounded in how trading relationships behave and built so a person reviews and approves before anything changes, directly answering the decision-automation and agentic AI shift Forrester names in the Landscape. Visibility Management connects every system in the purchase order lifecycle into one view and ranks exceptions by revenue at risk before a miss reaches the shelf, the same real-time connectivity and visibility Forrester identifies as primary functionality across the Landscape's core use cases.
Customers report the results directly. According to the SPS Commerce Customer Impact Study (June 2026), 83% say the data they exchange through the network improves their AI-readiness, and 82% of suppliers say SPS gives them better visibility into retailer requirements. On the financial side, suppliers report high improvement in fill rate (83%), the kind of performance data that changes what happens next cycle rather than just getting logged.
“As a small, high-growth brand, we're leaning heavily into AI to expedite efficiency and insight. We've gone deep with MAX and have already saved countless hours and hundreds of thousands of dollars.”
- Allen Thompson, Chief Operating Officer, RIP-IT
Context You Can Trust
AI works best with the full picture of your supply chain network behind it. See what SPS and Forrester have to say about closing the context gap, backed by independent research on 40 vendors across five core use cases. Read the full report here.
About SPS Commerce
SPS Commerce (NASDAQ: SPSC) is the leading intelligent supply chain network, connecting trading partners around the globe to optimize supply chain operations with all retail partners. Our AI-powered network connects 300,000+ trading relationships worldwide and moves more than 750 million transactions and over $650 billion in gross merchandise value each year. SPS is trusted by seven of the top 10 largest retailers and over two-thirds of today's fastest growing brands. With nearly 3,000 employees and offices worldwide, SPS Commerce is headquartered in Minneapolis, Minnesota.