AI Supply Chain Strategies to Deliver Holiday Cheer
By Barry Bradley, Head of Supply Chain, Crisp
The holiday rush puts transportation networks to the test… keeping deliveries on schedule through winter weather and record order volumes requires precision and visibility that only AI can deliver.”
— Barry Bradley, Head of Supply Chain, Crisp
The holiday shopping season begins well before Black Friday and Cyber Monday, as households prepare for festive meals and cold-weather comforts. Once the big sales weekends hit, it’s full steam ahead, leaving little room for supply chain errors. Amid tariffs, disruptions, and fierce competition, stockouts can hit sales and loyalty hard. McKinsey reports that only 13% of consumers wait for out-of-stock items to return, while 70% quickly switch retailers or brands. That’s true any time of year, but especially during the holidays.
Keeping shelves full and shoppers happy requires solutions built for retail collaboration.
According to Deloitte, 60% of retail professionals say AI tools helped them improve forecasting and inventory management. AI’s strength lies in its ability to process and compute massive amounts of data. With clean, real-time supply chain data as the basis, AI-powered strategies help retailers deliver on holiday promises while staying responsive to real-time shopper behavior. The technology brings insights once hidden in data complexity to light.
1. Wrap your retail strategy around POS data
2. AI keeps deliveries on track
3. Stay in-season and ahead of the curve
Despite ongoing challenges, the remainder of 2025 presents an opportunity for supply chain teams to refine operations, meet demand with precision, and build a stronger foundation for the year ahead.
As the holidays approach and demand shifts by the hour, knowing what’s selling – and where – is essential. Point-of-sale (POS) data from in-store and e-commerce channels provides that visibility, helping supply chain teams inform and optimize forecasting, inventory allocation, and seasonal planning.
The challenge many CPGs and retailers face is getting that data clean and in real time. Before AI can automate insights, organizations must overcome disparate, inconsistent, and delayed data sources that block timely decisions.
To unlock the full potential of POS data, teams can streamline sales and inventory insights across sources, unifying performance into a single, harmonized view. A reliable automation and integration solution to clean and structure data for enterprise-wide access ensures success at scale.
The holiday rush puts transportation networks to the test. As demand surges, so do the risks: icy roads, delayed shipments, and distribution bottlenecks can all slow the flow of goods when timing matters most. Keeping deliveries on schedule through winter weather and record order volumes requires precision and visibility that only AI can deliver.
Traditional logistics systems often operate with blind spots between shipping and receiving, creating costly inefficiencies when reality deviates from plan. Whether it’s trucks missing delivery windows or understaffed receiving teams, disruptions ripple through the supply chain, impacting inventory, labor costs, and shopper satisfaction.
AI-powered tracking and signaling transform static logistics systems into adaptive networks. With a clean data foundation, AI can process EDI shipment and order data, real-time location details, inventory levels, and warehouse staffing signals, empowering teams to receive critical shipments precisely as they arrive.
Beyond on-time delivery, AI strengthens communication throughout the enterprise. Change orders that once got lost between sales, operations, and logistics can now be automatically captured and surfaced in real time.
The holiday season is as unpredictable as it is festive. From sudden surges in seasonal flavors to shifting preferences for comfort foods, understanding what’s trending – and what’s next – gives supply chain teams the agility to meet demand with precision.
As consumer habits evolve – from protein-forward snacks to smaller portions influenced by GLP-1 trends – AI helps pinpoint which products align with these shifts. Using detailed attributes like nutritional profiles, teams can track performance and adjust forecasts or inventory ahead of competitors.
For teams ready to take the next step in retail intelligence, AI Blueprints offer pre-built, data science–ready models that layer onto clean, harmonized retail data. These Blueprints surface actionable insights around On-Shelf Availability, Store Clustering, Assortment Optimization, and more, helping teams stay on top of phantom inventory and zero-sales instances during the busiest shopping weeks of the year.
What’s more, out-of-the-box solutions like an Anomaly Detection Blueprint can continuously monitor sales performance against baselines, flagging deviations before they become costly stockouts or overstock situations.
4. Speaking to insights
5. Ring in the AI Agents
As the holidays pick up, so does the flow of data. From order volumes to category trends, separating signal from noise can challenge even experienced planners. AI is making that easier through conversational analytics.
Large language model (LLM) analytics allow users to interact with data naturally. Instead of writing complex queries or sifting through spreadsheets, planners can ask, “Which distribution centers show the strongest surge in demand?” or “Where are inventory levels trending low before promotions?” and receive instant, accurate responses.
When powered by clean, structured retail data, tools like Snowflake Cortex and Databricks Genie can surface insights down to the SKU and store level, giving teams real-time intelligence at their fingertips.
Agentic AI introduces the next evolution of retail management. AI Agents can monitor live retail data streams, detect anomalies, and signal when it’s time to adjust plans or shipments. They can also deliver customized daily reports across departments, providing instant visibility into trends and exceptions before they escalate. Gartner projects that by 2027, half of business decisions will be augmented or automated by AI agents – and the groundwork for that future is being built right now.
Sign up for the waitlist of Crisp’s AI Agent Studio for Retail to take your AI strategy to the next level in 2026.
Steve Henderson is a specialist in email deliverability, compliance, and privacy with nearly 20 years’ international experience. He has contributed to industry guidance with M3AAWG and the UK’s Data & Marketing Association, and has advised leading global brands on best practice. As Head of Deliverability at SAP Emarsys, Steve leads a global team managing the delivery of over a billion emails each day, helping brands improve inbox placement and protect trust through practical, scalable strategies.