AI

How agentic ecosystems are redefining the consumer experience

While there's more hype and excitement around customer-facing AI chatbots or flashy generative AI tools, consumer loyalty comes from providing a consistent, accurate shopping experience.

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April 14, 2026 by Meriel Neighbour — Chair of Ambassadors at MACH Alliance; Director of Technology Delivery and Transformation at River Island, MACH Alliance

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Agentic AI, or the ability to have an assortment of AI agents collaborating and working within a retailer's operation, is primed to forever change how retailers operate. But it will also shift the consumer experience, even if shoppers can't "see" the changes.

Apparel, wellness brands, mass retailers, and many sectors utilize AI customer service agents that interact with shoppers, and retailers are partnering with open-source AI tools for shopping, but it's the operational side of a retailer's business and technology stack where agentic will deeply seed change.

When it comes to interacting with these agentic-ready retailers, consumers can expect a more efficient and consistent omnichannel experience, provided retailers support agentic with the right approach to technology.

Composability and agentic AI go together

First, the success of an agentic AI-ready retail business relies on how a retailer manages data, and the ability to layer an open, composable, and connected IT infrastructure beneath the AI solutions.

It's paramount that a retailer ensures that its data is in a consumable state, meaning the information can be sought by AI agents to execute a decision back to a supply chain team, for example, driven by composable technology. Here, the architecture drives the agents, whether it's a back-end process or a voice assistant helping a shopper make a purchase decision.

The composable technology lends itself to interoperability so that agents can perform across the company. The two go hand in hand.

In fact, the 2026 Enterprise Technology Report, a study from the MACH Alliance, found 99% of the enterprise companies that have fully implemented a composable architecture are already achieving at least one measurable outcome from implementing AI.

The study also points out:

75% of retail/commerce/e-commerce leaders in the survey have widely or fully adopted composable and MACH principles, compared to 67% in manufacturing and 62% in financial services.
69% of retail leaders said their companies are using advanced AI in their tech stacks, not simply relying on free tools like ChatGPT or on a vendor that has AI.

These statistics highlight a correlation between composable frameworks and AI success, leading retailers to deliver more consistent, improved customer experiences through advanced operational workflows.

How composable technology supports AI agents

The agentic AI ecosystem is defined as AI agents or software entities that perceive, decide, and act autonomously across a retailer's systems, channels, and departments — envision a fully connected army of AI agents, not simply one chatbot or basic automation AI tool.

For example, these embedded agents, working together, are empowered to autonomously update pricing and promotions online in real time, forecast inventory based on weather patterns or changes in shopper behaviors, and automatically reorder and purchase products for shoppers.

Of course, upstream of this is a world where AI agents do interact with consumers, too. A consumer shopping online can engage an agent to bring forward product information including sustainability and traceability history of an item or even virtually put a shopper inside the very dress they're browsing.

Yet, composable technologies can transform business operations first. Composable architecture does so by leveraging modular, interoperable, and flexible components to support many collaborative agents, as opposed to locking into one vendor or way of working. A composable strategy, with microservices and API-first agents orchestrating across a company's tech lifecycle, enables retailers to shift toward managing outcomes, not just managing siloed AI or tech systems.

Agentic powers a consistent consumer experience

While the consumer may not be able to visually observe AI agents working together to power more efficient inventory forecasts or assortment plans, they'll feel these partnerships in the consistency of the shopping experience.

For example, agentic AI embedded into an operations process can help retailers autonomously predict demand shifts, rebalance inventory across distribution centers and stores, and select optimal fulfillment paths in real time. This is an art that retailer teams constantly aspire to meet — right product, right place, right time, at the right price.

Consider a hypothetical fashion retailer, FSHION, which is preparing for an unseasonably warm autumn. Traditional systems might leave winter coats sitting in warehouses while lighter jackets sell out in stores. But an agentic system can analyze weather forecasts, social media trends, and early sales patterns to detect the shift.

Before FSHION customers even notice stock issues, AI agents autonomously reroute seasonal inventory, moving heavier items to northern regions while redistributing lightweight layers to stores experiencing unexpected demand.

The result: shoppers find what they want, when they want it, without ever knowing a potential stockout was avoided.

Similarly, AI agents can optimize pricing and localized promotions to improve sell-through while maintaining brand integrity. Imagine a scenario in which agents detect that a particular style of denim is selling exceptionally well in urban markets but underperforming in suburban locations.

Rather than applying blanket markdowns that erode margin, the agents can orchestrate targeted promotions — pairing the slow-moving denim with complementary items that are popular in those suburban FSHION stores.

Retail will rely on composable and agentic working together

Retailers are exploring and investing in agentic AI capabilities, but success comes with a composable architecture set up in the back end.

While there's more hype and excitement around customer-facing AI chatbots or flashy generative AI tools, consumer loyalty comes from providing a consistent, accurate shopping experience.

Agentic AI is about building a sophisticated, interconnected ecosystem of agents that work in concert to anticipate needs, optimize decisions, and execute flawlessly across every touchpoint. And it all starts with the open, composable, and connected foundation that makes that collaboration possible.

About Meriel Neighbour

Meriel is currently leading a digital transformation at River Island and is the chair of ambassadors at MACH Alliance, a not-for-profit organization working to help retailers and enterprise businesses prepare for agentic AI through composable technology.

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