Collaborative AI agents are key to retail supply chains

In a recent meeting with a large retailer, my contact shared that each buyer on her team receives over 100 emails daily referencing data on a variety of topics, from out-of-stock issues and inaccurate pricing to recommendations for driving e-commerce. On the supplier side, the situation is similar: delivering Monday morning reporting to retailers, preparing for line reviews, monitoring out-of-stocks, and pushing new promotions. Emails and Excel are still the primary drivers of the $5 trillion retail industry, in the U.S. alone.

The opportunity for error in complex retail supply chains is immense. If demand forecasting and inventory management across thousands of store locations are inaccurate, the cost is tremendous. The combined cost of overstock and out-of-stocks are $1.77 trillion globally, just in 2023. These “if only” moments are coordination failures, and the root cause lies with siloed data and manual processes.

Tariff uncertainties, climate change, and geopolitical instability are driving additional waste and operational inefficiencies that strain an industry already operating on razor-thin margins. The disconnect between retailers and suppliers is unsustainable and presents the most challenging operational issue across highly complex retail supply chains.

COLLABORATIVE AI AGENTS

Improved collaboration between retailers, suppliers, and AI technology can overcome disconnects. Those gaps can be between product design, procurement, marketing and promotional planning, and product distribution. AI is often described as something a single company should leverage, but verticalized AI agents that specialize in retail can streamline manual tasks and facilitate collaboration across multiple companies so humans can spend time on what drives the business: being strategic.

Collaboration is at the core of a successful retail strategy. Agentic AI will change the way retailers and suppliers communicate and collaborate by surfacing alerts and making autonomous decisions that give retail the optimization boost it needs. It will not completely hand over management to agents, but it will enable humans to focus on higher level collaboration and informed decision making.

Currently, retailers, suppliers, and distributors each hold only a slice of the truth, thanks to complex workflows, fragmented data, and cross-company processes that lack connectivity, transparency, and context. AI agents can automate, negotiate, coordinate, and problem solve across organizational boundaries. They turn coordination into a competitive advantage. Companies that master agentic AI orchestration will (finally) gain complete visibility and optimization.

AI agents will become specialized “AI teammates” that coordinate across organizations to achieve shared goals and resolve problems independently and proactively. These autonomous agents can share insights (without exposing sensitive raw data), adapt to changing conditions in real time, and offer a path forward for retailers and their consumer packaged goods (CPG) partners to achieve immediate and long-term operational goals.

Notably, an agentic AI network requires more than technology itself. Many organizations focus on the latest agent-to-agent and multi-agent tools and frameworks, such as A2A, Microsoft AutoGen, or CrewAI. These tools support autonomous actions and support cooperation between AI agents, but they do not solve the more complex problem of building trust and standard AI operating procedures across companies.

Beyond the base technologies, these networks need a governance framework. Large enterprises are already adopting standards such as ISO 42001 and the NIST AI Risk Management Framework. These provide essential guidance, but they do not create the integral shared “smart contract,” a set of agreed-upon rules and goals that everyone trusts. Once this advanced framework is established, agents can take independent actions within predefined boundaries to work towards common goals shared by retailers and suppliers.

For example, price optimization is a critical joint business objective where AI agents can help. By tracking inventory levels, monitoring competitors’ pricing, and analyzing consumer behavior patterns, agents can recommend pricing adjustments when needed and offer ways to optimize promotional spend to help retailers and suppliers deliver value to their consumers while preserving profitability.

AI AGENTS IN ACTION

AI agents can address and solve coordination failures across many aspects of retail supply chains.

• Reducing out-of-stocks: Every empty shelf means lost sales, weakened brand loyalty, and an open door for competitors to capture the shopper’s choice—and purchase. Demand forecasting, which relies heavily on lagging data, often misses real-time shifts in demand, resulting in incorrect ordering. For example, phantom inventory (inventory noted as “in-store” but not actually on shelves due to misplacement), results in misaligned forecasts. AI agents can improve out-of-stock rates and deliver value directly to the bottom line for CPGs and their retail partners.
• Manage trade promotions: Trade promotions are one of the CPG’s largest P&L investments, but they quickly become discounts that drain profits. Poor measurement and inconsistent analysis lead to unprofitable promotions being repeated. CPGs often deploy a one-size-fits-all approach to promotion, offering discounts across categories rather than accounting for shopper and pack dynamics. PwC’s recent 2025 Future of Consumer Shopping Survey predicts that the most successful CPG companies will leverage AI to optimize pricing and promotion strategies in the coming years, unlocking significant incremental sales and margin uplift.
• E-commerce execution: Poor e-commerce execution wastes advertising spend and causes CPGs to cede the digital shelf share to the competition. Attribution and measurement are often muddied by limited cross-channel visibility. Messy product catalogs, missing attributes, or inconsistent product mapping can degrade (re)targeting campaigns. The Gartner 2025 CMO Spend Survey reports that marketing leaders are increasing their investment in GenAI to improve the efficiency of marketing tasks. By improving media spend effectiveness, AI can support brands in transforming wasted spend into profitable, scalable growth.

UNPRECEDENTED COLLABORATION

Collaborative AI agents designed for retail represent a significant structural shift in how the industry operates. The most challenging pain points and time-sensitive decisions that were “if only we knew” moments will be replaced by unprecedented cross-organizational collaboration, driven by informed and autonomous agents, allowing humans to focus on strategy.

Are Traasdahl is CEO and founder of Crisp.

source https://www.fastcompany.com/91464956/collaborative-ai-agents-are-key-to-retail-supply-chains