Every holiday season, the retail industry faces the same paradox: consumer demand surges, yet billions are lost to empty shelves, slow replenishment, and disconnected planning. Traditional supply chain models built on reactive forecasting and siloed visibility are reaching their limits.

A quiet revolution is underway. Agentic AI is transforming inventory management from a slow, reactive process into a real-time, autonomous system that senses, responds, and acts at the speed of consumer demand. At the forefront of this shift is Majaz Mohammed, Head of CPG at Tredence, who is helping global retailers move toward truly self-orchestrating supply chains.

AI & the Holiday Supply Chain

According to McKinsey, nearly 30% of U.S. annual retail sales occur during the Thanksgiving and Christmas season. Yet billions are lost each year due to poor inventory execution.

Majaz: “AI fundamentally changes the equation. Agentic systems monitor real-time signals such as social chatter, weather, and competitor moves, and can act within 90 minutes. Instead of broad forecasts, AI models micro-segment and adjust daily, spotting trends before stockouts occur.”

AI not only improves planning but continuously repositions inventory to priority regions, preventing lost sales and excess stock.

Balancing Automation and Human Judgment

Majaz: “AI handles the volume; humans handle strategy. AI monitors thousands of SKUs, triggers replenishments, and reallocates stock. Humans step in for context — viral trends, supplier disruptions, or margin risks. Think of AI as radar and humans as pilots.”

Trust in Agentic AI Decisions

Trust is built on transparency, guardrails, and performance history. Teams must understand what data drove AI decisions, define margin and inventory thresholds, and validate results through continuous measurement. Starting with low-risk categories builds confidence.

Digital Twins and Generative AI

Digital twins simulate the supply chain, allowing teams to test disruptions, promotions, and logistics scenarios safely. Generative AI then analyzes massive datasets to recommend optimized inventory, pricing, and allocation strategies in minutes.

Combined, these technologies create predictive, self-optimizing networks that respond autonomously to market changes.

Resilience Over Prevention

Modern leaders focus on adaptability rather than prevention. AI-driven supply chains diversify sourcing, dynamically adjust safety stock, and rebalance inventory in real time when disruptions occur.

Advice for CTOs and Supply Chain Leaders

• Start with data infrastructure, not flashy AI projects.
• Unify data across ERP, WMS, and POS systems using APIs.
• Prove ROI in a pilot within 90 days.
• Invest in data quality before advanced modeling.

The Self-Healing Supply Chain

A self-healing supply chain anticipates and corrects disruptions automatically. If a shipment is delayed, the system reroutes inventory, simulates downstream impact, and notifies stakeholders within minutes.

By 2026, leading supply chains will operate semi-autonomously, with AI handling most operational decisions and humans focusing on strategy and governance.

The Evolving Role of Humans

Majaz: “Humans will shift from operators to orchestrators. AI manages execution, but people define objectives, manage exceptions, and ensure accountability.”

One Phrase for 2025

Majaz: “Execute in real time or become irrelevant.”

Closing Thoughts

Agentic AI is no longer experimental. It is becoming the backbone of holiday readiness, revenue protection, and operational resilience. Retailers no longer need bigger warehouses—they need smarter supply chains.

The future belongs to orchestrators, not operators. Companies that invest in intelligent supply chains today will define tomorrow’s winners.