Shopify’s AI push meets checkout trust gap

Agentic AI is revolutionizing customer experience by autonomously managing product discovery, comparison, and personalized recommendations through natural language interactions, effectively moving beyond traditional chatbots. Shopify’s VP of Data, Nell Thomas, highlights that discovery is the first and most profound phase reshaped by AI, with Shopify expanding its commerce platform to lead this autonomous retail frontier. This transformation enables shoppers to engage with AI agents that not only understand their needs but also act on them, creating a seamless and proactive shopping journey.

The evolution from reactive chatbots to fully autonomous agentic AI agents marks a pivotal shift in retail customer service, where AI systems like Omnichat’s CS and Sales Agents execute multi-step tasks such as processing returns and proactively suggesting products within chat windows. Jerry Weng of Omnichat emphasizes that the true value lies in converting conversations into dynamic CRM and real-time social commerce engines, enabling scalable, personalized service that acts as a digital workforce integrated deeply into retail operations.

Agentic AI enhances personalized shopping by synthesizing vast customer data to offer tailored recommendations and automate routine purchases, freeing consumers to focus on categories they care about. Tools like OmniClaw, as explained by CEO Alan Chan, overcome generic AI limitations by providing business-specific insights that empower marketing managers to craft timely, relevant campaigns. Additionally, AI agents expand discovery beyond well-known brands, uncovering niche products that better fit individual preferences, while leveraging visualizations to show products in customers’ environments, thus enriching evaluation and decision-making.

AI conversational avatars are redefining brand engagement by delivering natural, human-like interactions that guide, explain, and personalize the shopping experience across diverse platforms—from apps to XR environments. This convergence of advanced language models, voice synthesis, and expressive digital characters creates adaptive, real-time interfaces that transform complex information into simple, conversational exchanges, fostering deeper shopper connection and sustained engagement in ways traditional interfaces cannot match.

By early 2026, consumers are engaging with a complex web of digital touchpoints—ranging from social media platforms like Instagram and TikTok to AI chat tools such as ChatGPT—before making purchases, with 94.4% interacting across multiple channels. This multi-channel engagement is driving top-performing brands to integrate marketing campaigns seamlessly across streaming, searching, scrolling, and shopping behaviors, resulting in an average performance boost of 11%, as treating these behaviors as a unified journey rather than isolated funnels becomes critical.

AI is revolutionizing the retail experience by embedding itself across diverse digital touchpoints, exemplified by platforms like Whatnot that blend live shopping, community interaction, and expert guidance to replicate in-person boutique experiences online. Concurrently, AI-driven discovery and checkout are accelerating funnel velocity, with Shopify reporting an 8x year-over-year increase in AI-powered store traffic and a 13x surge in orders from AI searches in Q1 2026, underscoring AI’s role in enabling highly personalized and interactive purchase journeys.

Checkout processes are rapidly evolving into AI-enabled, agentic experiences embedded within search engines and voice assistants, as seen with Amazon’s Alexa for Shopping and Google’s rollout of integrated checkout features. While these innovations promise seamless purchase flows directly inside AI environments, consumer preferences remain cautious; EMarketer CEO Matthias Braun notes that many AI users still favor traditional search or app-based shopping, indicating a gradual transition where AI is primarily leveraged for research and discovery rather than finalizing purchases.

In response to trust challenges and the risks of third-party AI platforms, retailers like Target are increasingly investing in owning their AI commerce experiences to maintain control over the consumer journey and checkout accuracy. According to a Commercetools white paper, these owned AI experiences empower brands to deliver personalized recommendations and proactive service, striking a balance between speed and trust that is essential for strengthening customer relationships in an agentic commerce landscape.

Consumers are increasingly comfortable relying on AI for product discovery, with over half using AI-generated email summaries to inform decisions and 63% of Australians expressing interest in AI shopping tools. However, trust remains fragile; only 10% fully trust AI summaries, and concerns about privacy and data misuse persist, with 25% citing this as their top worry. This skepticism is compounded by consumers’ preference to verify AI recommendations through trusted retailer or review sites before purchase, highlighting a cautious adoption pattern where AI aids browsing but rarely commands final transaction control.

Despite growing consumer openness—such as over half of U.S. shoppers willing to let AI handle entire shopping journeys—actual adoption of AI-driven checkout remains limited due to concerns over security and personalization. Australian shoppers, for example, overwhelmingly reject AI assistance at payment points, with only 4% willing to use it at checkout, underscoring the critical role of perceived security and trust. Consumers expect AI tools to meet or exceed existing payment security standards, and trust is often placed more in payment providers like PayPal than in tech giants expected to launch these tools, revealing a nuanced trust landscape that retailers must navigate carefully.

Retailers and marketers face a disconnect between their AI investments and understanding of consumer trust dynamics, with 49% of marketers admitting limited grasp of how consumers use AI for research and 74% unable to measure AI’s impact on discovery. Premature launches of AI shopping assistants, driven by FOMO, have led to consumer frustration and skepticism, as noted by Forrester’s Emily Pfeiffer. To bridge this gap, brands must enhance transparency by providing provenance, explainable product attributes, and clear source attribution, while leveraging rich, accurate product data to empower AI tools to deliver genuinely personalized and trustworthy recommendations.

Humanizing AI interactions through video communication emerges as a promising strategy to build consumer trust and overcome skepticism. Doug Dbert Jr. highlights that video conveys nonverbal cues absent in text, making AI-driven commerce feel more personal and relatable. Platforms like Magnify enable marketers to integrate video into AI chat and email automation, helping brands stand out and accelerate deal closures by fostering a more authentic connection with consumers wary of AI-generated content.

Retailers and retail media networks are strategically pivoting to integrate AI-driven agentic commerce by embedding advertising within large language models (LLMs) and AI platforms, as exemplified by Mondelez’s early pilots across various AI tools beyond ChatGPT. This shift addresses the threat AI shopping agents pose to traditional retail media by potentially diverting shoppers away from retailer websites, forcing a reevaluation of retailers’ roles in the shopper journey and advertising spend. As Mondelez emphasizes, maintaining close ties with retail and consumer platforms remains critical amid a changing value chain, with those retailers adapting effectively poised to capture increased market share.

The rise of AI shopping assistants as a top digital investment—chosen by 37% of retailers—reflects a strategic reallocation of resources away from traditional digital commerce features like mobile apps and cross-channel shopping. This prioritization is driven by consumer behavior, with 47% of online shoppers already using AI during purchases and 64% expecting to engage AI shopping agents within two years. Retailers like David’s Bridal are capitalizing on this trend by launching AI-enabled storefronts through platforms like Shopify’s Agentic, enabling seamless in-chat purchases and enhancing frictionless shopping experiences both externally and internally across departments.

To navigate the fragmented and evolving discovery landscape, retailers are investing heavily in AI visibility and monitoring solutions such as Ipsos Synthesio AI Visibility, which benchmarks brand presence across emerging AI search engines like ChatGPT, Gemini, and Amazon Rufus. These tools empower brands to optimize their positioning in AI-generated search results and respond strategically to competitive pressures. Concurrently, retailers are embracing multi-channel marketing strategies that leverage social commerce, creator content, and AI-powered live chat to engage younger consumers, with 67% of New Zealand shoppers using social platforms for product discovery and 44% of younger shoppers utilizing virtual assistants during product comparison.

Industry leaders recognize that succeeding in agentic commerce requires dual marketing tracks tailored to both human and AI-driven customers, underpinned by clean, discoverable data as foundational to trust and operational success. This insight is reinforced by pioneering Chinese companies like Alibaba and Tencent, whose innovations in embodied AI and robotics prompt global retailers to rethink transactional models and forge executive-level partnerships with AI hardware and software providers. As one expert notes, 'trust is the product that we're marketing here in this moment in time,' highlighting the strategic imperative to adapt rapidly and thoughtfully to the agentic economy’s competitive landscape.