[AI]How Shopify is bringing agentic AI to enterprise commerce

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is enhancing core enterprise commerce workflows with agentic AI, automating operations while expanding sales channels.

The adoption of generative AI in commerce has largely centred on customer support chatbots and basic content generation.

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’s Winter ‘26 Edition, titled Renaissance, pushes this technology toward agentic commerce where AI systems actively manage workflows, configure infrastructure, and distribute products into third-party ecosystems.

Modernising commerce with the agentic AI storefront

The most distinct architectural adjustment is the introduction of ‘Agentic Storefronts’. Traditionally, merchants drive traffic to a proprietary domain to secure a conversion.

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’s new model allows products to surface directly within AI-driven conversations on platforms such as ChatGPT, Perplexity, and

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Copilot.

For CDOs, this fragmentation of the customer journey requires a change in channel strategy. Rather than complex integrations for each external platform, products configured in the admin become discoverable by these agents immediately. The transaction occurs within the conversation, with attribution data flowing back to the central admin. This capability addresses the risk of brand invisibility as search behaviour migrates toward LLMs.

“AI is now essential to modern commerce,” says Deann Evans, Managing Director, EMEA at

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. 

Evans points to internal data suggesting 93 percent of *** merchants are investing in AI tools to aid discovery, aligning with the 66 percent of consumers who expect to use AI for at least one part of their holiday shopping.

Operational intelligence and ‘Sidekick’ updates

While distributed commerce addresses revenue generation, the updates to ‘Sidekick’ (

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’s AI assistant) target operational expenditures and efficiency. The tool has evolved from a reactive AI chatbot into a proactive agentic system capable of executing complex administrative tasks for commerce.

Sidekick Pulse now surfaces personalised tasks based on real-time data, such as suggesting product bundles when specific cart behaviours are detected or flagging compliance gaps like missing return policies.

For technical teams, the reduction in low-level ticket volume is a primary benefit. Sidekick can now generate admin applications from natural language prompts, allowing non-technical staff to build custom tools without developer intervention. Furthermore, it creates ‘Working Flow’ automations from descriptions to bypass the need for deep knowledge of

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’s specific logic syntax.

To support standardisation across large teams, prompts can now be saved and shared as “skills,” ensuring that verified and safe prompt structures are reused rather than ad-hoc queries.

A persistent difficulty for enterprise retail is testing changes without disrupting live revenue streams.

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has introduced ‘SimGym’ (currently in research preview) and ‘Rollouts’ to address this.

SimGym utilises AI shopper agents with human-like profiles to simulate traffic and purchasing behaviour. This allows merchants to model how storefront changes affect conversion rates using synthetic data derived from billions of annual purchases, rather than waiting for live A/B test results.

Complementing this, Rollouts provides native experimentation capabilities within the admin, allowing for controlled scheduled changes and data-informed decision-making regarding buyer behaviour. For the C-suite, this reduces the risk profile of platform updates and marketing experiments.

Infrastructure and developer velocity

Beyond agentic AI, the update addresses physical commerce infrastructure and developer tooling. The new ‘POS Hub’ offers a wired connectivity solution for retail hardware, designed to improve resilience in high-volume brick-and-mortar environments. It acts as a dedicated operational unit, integrating card readers and scanners via a stable connection, which is vital for maintaining throughput during peak trading periods.

On the software side, the AI-native developer platform aims to accelerate build times. AI agents can now scaffold apps, execute GraphQL operations, and generate validated code. This is supported by the

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Catalog, which enables agents to search across hundreds of millions of products to build richer applications.

Vanessa Lee, VP of Leading Product at

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, commented: “We chose the Renaissance theme for this Edition because it symbolises progress, momentum, courage, and new beginnings … Many of these features weren’t possible a year ago and they redefine how we achieve our mission of making commerce better for everyone.”

For enterprise leaders, the barrier to creating custom internal tools has lowered. The storefront is also no longer a static destination; it is a distributed set of data points accessible by third-party AI agents. Preparing product data for the agentic AI future of commerce is now a requisite for maintaining competitive visibility.

See also:

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