Retail has changed — permanently.
In recent years, retailers have emphasized omnichannel transformation, turning stores into fulfillment nodes with fluid inventory. At the same time, consumer expectations have heightened to a point where same-day is standard, scheduled delivery is assumed and white-glove delivery is increasingly required. Cost-pressure is high, and margins are thin.
In this challenging environment, many enterprise retailers are still managing last mile delivery through fragmented courier networks, manual exception handling, disconnected systems and reactive decision-making.
It’s an unsustainable model that demands action.
In a recent conversation with Andrew Silver on The Freight Pod, Bill Catania, Founder and CEO of OneRail, breaks down what modern retail leaders must understand about the future of AI-driven last mile orchestration, including why the transformation cycle is still in its early innings.
Enterprise retailers navigating growth, complexity and margin pressure can use these insights to embrace the modern retail landscape and build a competitive advantage.
Takeaway #1: AI Is Existential Infrastructure
For many retailers, last-mile technology is still framed as a feature conversation: better visibility, better reporting, more automation. But AI-driven last mile orchestration is much more than just a feature at the enterprise level — it becomes infrastructure.
That’s because manual dispatch can’t scale across thousands of stores:
- As order volume increases, exception volume increases.
- As service levels multiply, the carrier mix expands.
- As product complexity expands, variability increases.
Too many delivery programs still rely on labor-heavy coordination, where headcount grows alongside orders. That model quickly breaks under scale.
Catania described OneRail’s early system candidly: a digital dispatcher environment where human operators selected couriers from a screen. There was no embedded intelligence, no predictive scoring, no optimization logic. The system replaced spreadsheets and phone calls, but the cracks became obvious as the network expanded.
OneRail’s ability to scale over time would have been impossible without AI.
“We’d have to have like, I don’t know, 3,700 employees to digitally dispatch all the orders that we have and we couldn’t be in business,” Catania said. “So it’s life and death, data science and AI for us.”
For enterprise retailers, the implication is this: If your last mile model scales linearly with labor, it’s structurally flawed. Scale required real-time execution decisions across thousands of delivery variables without adding thousands of employees to manage them.
Takeaway #2: Retailers Need Ownership
Accountability is one of the most persistent problems in last mile delivery.
In traditional brokerage models, risk is distributed and often deflected — the carrier blames the shipper, and the shipper blames the carrier. When damage occurs, when a delivery is missed, when a claim surfaces, the response becomes procedural and the retailer absorbs the operational disruption and customer dissatisfaction.
At enterprise scale, that model creates friction in stores, in customer service, in finance and ultimately in brand perception.
Catania was direct about how OneRail approaches this differently.
“We take the full risk,” he said. “We take the full risk and I know that sounds crazy, but we take the full risk and we do that when it’s under our authority.”
When a company assumes full responsibility for execution under its authority, incentives shift. True ownership leads to greater investment in data science, deeper analysis of exception patterns and close monitoring of carrier performance. Over time, the risk is engineered out of the system rather than passed along.
Takeaway #3: Last Mile Orchestration Requires Operational Muscle
Buying better software isn’t always the solution. Software promises better visibility, fancier dashboards and more integrations. But visibility doesn’t move freight, dashboards don’t manage carriers and APIs can’t resolve service failures in Detroit while preserving margin in Dallas.
Catania addressed this reality head-on:
“There’s not many software companies that wanna roll their sleeves up and manage transportation.”
Managing transportation at last mile scale is operationally heavy. It requires:
- Continuous courier recruitment to fill geographic gaps
- Insurance verification and compliance tracking across a fragmented carrier base
- Active SLA performance management and QA oversight
- Identifying degradation patterns at the market level before they turn into customer complaints
That work requires disciplined execution supported by technology, and it’s why true orchestration requires two layers working in sync:
- A technology layer that makes real-time decisions
- An operational layer that actively manages the network
Today’s retailers need an integrated system where intelligence and execution reinforce each other.
Takeaway #4: The Enterprise Mindset That Unlocks Innovation
In enterprise retail, it’s easy to say “no” to things like:
- Refrigerated and frozen distribution.
- White-glove furniture delivery.
- Industrial supply and oversized freight.
- Auto parts moving store-to-store.
- Multiple SLAs layered across thousands of fulfillment nodes.
But “no” also shuts down innovation. Catania framed OneRail’s approach differently: “We never say no. It’s, ‘yes if.’”
The “yes if” mindset reframes the conversation around conditions and structure. While it’s never easy, it’s beneficial to say “yes” if:
- The risk aligns with the reward.
- The data supports the feasibility.
- The SLA can be engineered to protect performance.
- The economics are sound.
For enterprise retailers, complexity is unavoidable. The question is whether your partners respond to it defensively or constructively.
Takeaway #5: Last Mile Is Still in the Early Innings
Many retailers believe they’re well into digital transformation. It could be that stores have been enabled for omnichannel, inventory is more visible, order management systems are modernized and transportation management platforms are in place.
But Catania warns that there’s much more work to be done.
“I know we’re in the early innings of last mile transformation,” he said. “It feels like there’s about a seven year, eight year investment cycle ahead of us.”
That perspective is important for enterprise leaders making capital allocation decisions right now. While retailers have made progress upstream (in planning, inventory visibility and omnichannel enablement), the downstream execution layer is still evolving.
The next phase will focus on connecting systems earlier in the order flow so that cost, service level and capacity decisions are optimized before the delivery is ever dispatched.
Retailers who invest early in scalable, AI-driven last mile orchestration will define the next phase of retail transformation.
The Shift Retail Leaders Must Make
What Catania made clear on The Freight Pod is that the structure behind last mile orchestration determines whether growth produces leverage or exposes operational weakness.
For enterprise leaders, the implications are practical and immediate:
- Is our last mile model structurally scalable?
- Who ultimately owns delivery risk across our network?
- Are cost and service decisions being optimized in real time?
- Are our last-mile decisions connected upstream to order and inventory systems?
The retailers that answer these questions with clarity — and invest accordingly — will build a durable operational advantage. Those that continue to view the last mile as a tactical carrier strategy will find that complexity, cost pressure and customer expectations outpace their model.
Schedule a demo to discover how OneRail’s AI-native platform brings true last mile orchestration to your retail delivery operations.
