The commerce industry stands at an inflection point. Within the next 18 months, every major retail media platform, marketplace, and adtech partner will deploy specialized AI agents designed to automate critical functions across their ecosystems. Amazon is already testing agents for campaign optimization and catalog management. Walmart, Instacart, and Criteo are following suit. The question facing brands and agencies isn't whether this transformation will happen; it's how to prepare for an environment where dozens of autonomous agents operate simultaneously across your commerce infrastructure. The instinctive response might be to build competing agents that can match these platform capabilities. But this impulse misses the fundamental shift occurring in our industry. The real strategic opportunity lies not in replicating what platforms are building, but in creating the orchestration layer that manages them all. The Agent Proliferation Reality To understand why orchestration matters, we need to map the emerging agent ecosystem. Retailers and marketplaces are developing specialized agents across three critical domains. First, retail media agents are handling campaign planning, creative optimization, bid management, and budget pacing. These aren't simple automation scripts, they're sophisticated systems that understand platform-specific auction dynamics, consumer behavior patterns within each ecosystem, and the nuanced relationships between ad formats, placement strategies, and conversion outcomes. An Amazon DSP agent operates fundamentally differently from a Walmart Connect agent, because the underlying systems, data structures, and optimization levers are fundamentally different. Second, catalog and merchandising agents are managing product content, enforcing compliance requirements, optimizing product detail pages, and coordinating promotional strategies. These agents need deep integration with each platform's content management systems, understanding everything from image specifications to A+ content requirements to category-specific attribute hierarchies. Third, operational agents are streamlining dispute resolution, processing order exceptions, managing inventory synchronization, and handling seller performance metrics. These are the unglamorous but essential functions that consume disproportionate time from commerce teams today. Meanwhile, adtech partners are building their own agent capabilities that span the full marketing funnel. Planning agents can analyze historical performance data, recommend audience segments, suggest optimal channel mixes, and propose format strategies based on creative performance patterns. Management agents handle cross-platform campaign execution, dynamic budget reallocation, and real-time optimization based on performance signals. Analytics agents are moving beyond basic reporting to deliver sophisticated measurement including marketing mix modeling, path-to-purchase analysis, and incrementality testing. This isn't speculative. These capabilities are being deployed now, with varying degrees of sophistication and automation. The infrastructure is being built. The APIs are being documented. The agent economy in commerce is arriving faster than most organizations realize. The Complexity Trap When confronted with this proliferation, many brands and agencies are considering building their own competing agents. The logic seems sound: if we develop proprietary agents that can match platform capabilities, we maintain control and avoid dependence on vendor solutions. This approach is strategically flawed for several reasons. First, it dramatically underestimates the development investment required. Building an agent that can truly compete with Amazon's retail media optimization capabilities means replicating years of machine learning development, platform-specific data collection, and algorithm refinement. It means maintaining that agent as Amazon continuously evolves its advertising infrastructure. Now multiply that effort across Walmart, Instacart, Target, Kroger, and every other retail media network in your channel mix. The resource requirements become prohibitive quickly. Second, it misses where the actual strategic value lies. Platform-specific agents are ultimately commoditizing. Amazon's DSP agent and your hypothetical Amazon DSP agent are both optimizing within the same constrained system with access to largely the same signals. The differentiation potential is limited. Meanwhile, the orchestration challenge—how to coordinate strategy across all these platforms simultaneously—is where genuine competitive advantage emerges. Third, building competing agents puts you in direct competition with your platform partners. These platforms have asymmetric advantages: complete data access, ability to modify underlying systems to enhance agent performance, and massive scale to train and refine their models. Competing directly in this arena is a losing proposition. The more profound issue is that building point solution agents doesn't solve the actual problem brands face. The coming challenge isn't executing effectively within a single platform—it's maintaining strategic coherence across dozens of platforms simultaneously, each with its own autonomous agent making thousands of tactical decisions daily. The Orchestration Imperative The alternative approach is to build upward in the stack rather than outward. Instead of replicating platform agents, develop the orchestration ecosystem that manages them. This model starts with unified brief development. Brand teams should be able to input comprehensive strategic direction in a single location: creative requirements including brand guidelines, messaging frameworks, and asset specifications; budget parameters with total allocation, efficiency targets, and investment constraints; business objectives spanning awareness goals, consideration metrics, and conversion targets; channel preferences reflecting strategic priorities and known performance patterns. This unified brief becomes the input for orchestration agents that operate at a higher level of abstraction. These meta-agents handle several critical functions that platform-specific agents cannot. Creative message development involves translating brand strategy into platform-optimized creative briefs. An orchestration agent understands that the same product launch message needs to manifest differently across Amazon DSP video, Walmart Connect sponsored products, and Instacart display advertising. It can generate platform-specific creative guidance while maintaining brand consistency. Partner and channel selection means analyzing which platforms and formats align with specific campaign objectives. Rather than executing the same strategy everywhere, orchestration agents can evaluate where investment should concentrate based on audience overlap, historical performance, incremental reach opportunities, and strategic priorities. Budget allocation across platforms requires understanding inter-platform dynamics that individual platform agents cannot see. An orchestration agent knows when Amazon performance is cannibalizing Walmart sales, when Instacart awareness drives Amazon conversion, and how to rebalance investment accordingly. Coordination of platform agent execution involves setting appropriate objectives and constraints for each platform-specific agent, monitoring their collective performance, and adjusting strategy when agents are optimizing locally but delivering suboptimal global outcomes. Once strategy is set and parameters established, orchestration agents delegate execution to platform-specific agents. Amazon's agent handles bid management within Amazon DSP. Walmart's agent optimizes product page content within Walmart Connect. Instacart's agent manages promotional timing within Instacart advertising. Each platform agent operates autonomously within its domain, but under strategic direction from the orchestration layer. This architecture delivers several advantages. It concentrates investment where differentiation is possible; in strategic coordination rather than tactical execution. It creates platform-agnostic strategic planning that isn't locked into any single vendor's ecosystem. It enables genuine full-funnel optimization by coordinating across platforms rather than optimizing within silos. It builds durable capabilities that persist regardless of how individual platform agents evolve. Building the Orchestration Ecosystem Implementing this vision requires three foundational elements. First, standardized interfaces for agent communication. We need common protocols for how orchestration agents transmit objectives to platform agents, how platform agents report performance back to orchestration layers, and how agents signal constraints, conflicts, or required approvals. The industry should coalesce around open standards rather than proprietary integration approaches. Second, unified data infrastructure that consolidates performance signals across platforms. Orchestration agents need comprehensive visibility into cross-platform performance to make informed allocation decisions. This requires data warehousing capabilities that can ingest platform-specific metrics and normalize them for comparative analysis. Third, governance frameworks that define decision rights, approval requirements, and intervention protocols. Even in an agent-driven environment, humans need clear mechanisms to provide strategic direction, approve significant budget shifts, and intervene when agent behavior deviates from brand standards or business priorities. The technology providers best positioned to deliver this orchestration layer are those with existing cross-platform data aggregation capabilities, strong relationships across multiple retail media networks and adtech partners, and sophisticated marketing strategy expertise. Agencies, in particular, have natural advantages here; they already operate as strategic coordinators across platform relationships, they maintain cross-client visibility that enables better pattern recognition, and their value proposition naturally aligns with orchestration rather than point solution delivery. The Path Forward This transformation won't happen overnight, but the building blocks are emerging rapidly. Organizations should begin preparing now through several concrete actions. Audit your current agent landscape. Catalog which platforms are deploying agent capabilities, what functions they're automating, and what interfaces they're exposing for external coordination. This mapping exercise reveals both opportunities and gaps in your orchestration requirements. Invest in data infrastructure before agent infrastructure. The prerequisite for effective orchestration is comprehensive cross-platform visibility. Prioritize building unified data warehouses that can consolidate performance signals across your entire commerce ecosystem. Develop standardized brief frameworks that can serve as inputs for orchestration agents. Moving from platform-specific campaign planning to unified strategic briefs requires rethinking how your teams articulate objectives, requirements, and constraints. Cultivate agent literacy across your organization. The shift to agent-mediated commerce requires new mental models about control, optimization, and strategic leverage. Teams need to understand the distinction between strategic direction and tactical execution, and where human judgment remains essential versus where agent autonomy should be embraced. Engage in industry collaboration around standards and protocols. The orchestration vision only works if agents can communicate across organizational boundaries. Participate in industry forums working to establish common interfaces, data standards, and governance frameworks. The explosion of specialized AI agents across the commerce ecosystem is inevitable. The strategic question is whether your organization will attempt to compete with platform-specific capabilities or build the orchestration layer that delivers genuine competitive advantage. The answer will determine whether you're overwhelmed by agent proliferation or empowered by it. The future of commerce isn't about building better agents than Amazon or Walmart. It's about building the systems that make all those agents work together toward unified strategic objectives. That's where the next generation of competitive advantage in commerce will be won.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

This story contains AI-generated text. The author has used AI either for research, to generate outlines, or write the text itself. 

The Case for Orchestrating AI Agents Across Retail Platforms

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