AI Investments Are Set to Spike: What Operations Leaders Need to Execute in 2026
February 26, 2026 - New research from ShipStation, in partnership with Retail Economics, surveyed 8,000+ consumers and 400 retailers. The headline: 90% of global retailers plan to increase AI investments in the next 12-24 months to optimize shipping and delivery.
North American businesses are moving fastest. 61% are actively growing AI usage and testing new applications, and 28% say AI is already embedded and scaled across several functions (vs. Europe at 50% and 17%).
Why the urgency: Expectation vs. capability gap
Consumer expectations in North America are ahead of current operations. 59% of consumers expect two-day delivery, but only 40% of retailers offer it as standard. That gap is your roadmap.
Price sensitivity matters. The optimal price shoppers will pay for premium delivery is $5-$9, yet just 42% of U.S. retailers price within that range.
Where AI moves the needle over the next 24 months
- Delivery execution (44%): Faster SLAs, tighter ETA accuracy, and proactive exception comms.
- Predictive fulfillment (39%): Smarter demand forecasting, inventory placement, and carrier selection.
- Reverse logistics (26%): Lower return costs, better dispositioning, and faster refunds.
"With so many businesses scaling their AI use, it's clear that AI is no longer a futuristic concept-it's a necessity for shippers looking to compete effectively and meet evolving consumer demands," said Kelly Vincent, Chief Product Officer at Auctane, ShipStation's parent company.
Biggest hurdles ops teams will face
- Adopting AI and emerging tech (33%)
- Fulfillment costs (29%)
- Managing inventory across channels (26%)
Size matters, too. Smaller retailers (under $125m) struggle with AI development costs (53%) and integrating agents with legacy systems (35%). Larger retailers ($625m+) cite skills shortages (47%) and customer resistance/lack of trust (53%).
What this means for Operations: A practical playbook
- Close the two-day gap: Segment SKUs by velocity and margin, push top movers to regional nodes, expand ship-from-store, and diversify carriers. Tighten SLAs where you win; offer paid upgrades where you don't.
- Price premium shipping in the sweet spot: Test $5-$9 with A/B price ladders by zone and basket size. Add guardrails: target contribution margin per order and refund thresholds tied to ETA accuracy.
- Run focused AI pilots: Start with ETA prediction, exception triage/automated outreach, dynamic carrier selection, and dock/slot scheduling. Timebox to 8-12 weeks with clear success metrics.
- Fix data plumbing early: Unify orders, inventory, carrier events, and returns. Standardize event codes, address hygiene, and geocoding. You'll need clean telemetry for any meaningful AI lift.
- Integrate where it counts: Prioritize WMS/TMS/OMS connectors and real-time event streams. Push/pull via APIs so AI recommendations can auto-execute, not just report.
- Attack returns cost: Automate RMA creation, smart routing to refurbish/resell/liquidate, and "label in box" or QR flows. Shorten refund cycle time to lift repeat purchase.
- Measure like a hawk: On-time %, ETA accuracy, exceptions per 100 orders, contacts per order, 2-day coverage %, cost per order, return cycle time, and delivery NPS.
- De-risk AI adoption: Add human-in-the-loop for high-impact decisions, log feature importance for explainability, and craft customer comms to build trust.
Resource allocation by company size
- Smaller orgs: Favor SaaS over custom builds to reduce capex and integration burden. Start with carrier optimization and ETA accuracy-fast ROI, minimal change management.
- Larger orgs: Invest in MLOps, data engineering, and change management. Stand up an AI Center of Excellence with shared feature stores and governance.
90-day rollout blueprint
- Weeks 0-2: Baseline KPIs, map data sources, and identify top three failure modes (late handoffs, bad addresses, carrier mix).
- Weeks 2-4: Launch premium shipping price tests ($5-$9) and select two AI pilots (ETA + exception comms).
- Weeks 4-8: Integrate APIs, instrument events, and push AI recommendations to production for a controlled cohort.
- Weeks 8-12: Scale to 30-50% of order volume. Review KPI deltas, adjust SLAs and carrier mix, and lock a returns automation pilot.
Further learning and tools
For hands-on strategies and templates, explore AI for Operations and the AI Learning Path for Supply Chain Managers.
Access the report
For more on the Ecommerce Delivery Benchmark Report 2026, visit ShipStation or request a full copy at media@auctane.com.
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