McKinsey & Company's latest research, 'McKinsey Agentic Commerce Trends,' provides an authoritative look into the burgeoning landscape of agentic commerce and its profound implications for retail, automotive, and consumer-goods sectors globally. This comprehensive report, drawing on McKinsey & Company's extensive expertise, articulates how artificial intelligence is not merely augmenting but fundamentally reshaping consumer purchasing journeys, demanding a proactive strategic pivot from business leaders and enterprise teams.

The report's central thesis posits that agentic commerce, characterized by AI tools acting on behalf of consumers to fulfill shopping tasks, is rapidly moving from an emerging concept to a dominant force. It highlights an accelerating global adoption curve and quantifies the direct impact on conversion rates, basket values, and the competitive dynamics of online commerce. For enterprise leadership and market strategists, this research serves as a critical compass, delineating both the immense opportunities for growth and the significant operational and strategic hurdles that must be addressed to thrive in this evolving environment.

Methodology & Research Scope

The 'McKinsey Agentic Commerce Trends' report was synthesized by McKinsey & Company, a leading global management consulting firm, leveraging its deep domain expertise across retail, automotive, and consumer-goods sectors. The research was led by Elizabeth Silliman, Jack Trotter, and Kelsey Robinson and published on October 28, 2026. This global study draws on a rigorous evidence base, including primary consumer surveys across 11 key markets, analysis of transactional data, and insights gleaned from enterprise engagements. The scope encompasses the entire retail and e-commerce ecosystem, exploring consumer behavior with AI tools, the operational demands on retailers and brands, and the strategic implications for technology adoption and data management. The report's findings are grounded in a comprehensive view of both consumer-facing AI platform usage and retailer-specific AI assistant integration.

Critical Data Spine

McKinsey & Company's 'McKinsey Agentic Commerce Trends' report delivers a compelling quantitative breakdown of agentic commerce's impact:

  • AI Search Dominance: The report finds that AI search is over three times more influential than traditional search engines for AI shoppers. Nearly a third (29%) of global AI shoppers identify AI chat or search tools as the single biggest influence on their most recent purchase, making AI search 3.2 times more influential than traditional search engines (9%).
  • Accelerated E-commerce Growth: Agentic commerce is poised to significantly accelerate lagging e-commerce sectors, with the potential to lift US online sales by 11.5% by 2030. Retail categories that historically struggled with low US e-commerce penetration, such as food and beverage grocery (9% online share of retail sales in 2025) and beauty or personal care (22% share), are rapidly closing the gap, propelled by agentic tools.
  • Conversion and Spend Uplift: As documented in the study's case evidence, retailer-owned AI solutions demonstrate significant uplift. Amazon's Alexa for Shopping, following the retirement of its Rufus assistant, reported in July 2026 that shoppers using the assistant are 60% more likely to complete a transaction, with US users spending 40% more. Similarly, Shopify's structured product catalog doubles AI conversion rates, highlighting the power of optimized product information.
  • Global AI Shopping Adoption: Over half (53%) of adult consumers across 11 global markets now report using AI tools or retailer assistants for shopping tasks within the past three months, as platforms like ChatGPT and Gemini surpass one billion monthly active users. This adoption is led by China and India, which far outpace Western markets.
  • Surge in AI-Executed Purchases: The share of US AI users completing a transaction directly within an AI tool surged 70% year-over-year, rising from an average of 10% across categories in December 2025 to 17% in June 2026, and reaching 14% of AI users globally.
  • Demographic Leadership: Millennials and Gen Z are spearheading global AI shopping adoption, with 63% of millennials and 62% of Gen Z utilizing AI for retail tasks, compared to the 53% global average. Notably, older Chinese cohorts outpace Western youth in adoption.
  • Discovery vs. Checkout Usage: Across the overall shopping journey, 56% of consumers used stand-alone AI chat or search tools over the past three months compared to 27% who used retailer-operated AI assistants, with stand-alone platforms dominating early shopping discovery while retailer assistants gain ground at checkout.

Market Tensions & Strategic Challenges

The advent of agentic commerce, while presenting immense opportunities, also introduces significant market tensions and strategic challenges for enterprises. One primary friction point highlighted in the report is the chasm between burgeoning consumer willingness and current operational capabilities. While the share of US AI-executed purchases surged 70% year-over-year, OpenAI's scaling back of instant checkout ambitions underscores the massive architectural, configuration, and deployment work required to connect AI agents across thousands of global merchants. This suggests that while consumer appetite for automated purchasing is robust, the underlying integration complexities are constraining short-term fulfillment capabilities.

Another critical tension arises from the imperative to balance data openness with proprietary asset protection. As documented in the study, retailers must share product and inventory data openly with AI agents to facilitate frictionless purchasing. Simultaneously, they face the strategic challenge of strictly safeguarding proprietary customer and loyalty insights, which represent a core competitive advantage. Navigating this dichotomy requires sophisticated data governance and a clear understanding of what data is essential for agent performance versus what must remain ring-fenced.

Furthermore, the report implicitly surfaces a governance vacuum within many enterprises. The cross-functional nature of agentic commerce, spanning product, marketing, IT, and operations, necessitates a coordinated strategy. Without an empowered senior leader to coordinate cross-functional governance and rapid decision-making, organizations risk fragmented efforts and missed opportunities in a rapidly evolving market landscape.

The 3 Core Trends

Building the Foundation: Owned Retailer AI Infrastructure and Data Readiness

The foundational shift articulated by McKinsey & Company is the imperative for retailers to invest strategically in their own AI infrastructure and ensure pristine, AI-ready product information. The underlying market mechanism is the direct correlation between streamlined, accurate data and enhanced conversion and customer experience. According to McKinsey & Company's research, investing in retailer-owned AI shopping assistants drives higher conversion and basket value by removing friction at the point of purchase. The report emphasizes that connecting AI agents to clean, real-time product catalogs doubles conversion rates compared to relying on scraped web data.

The practical implementation reality involves significant data hygiene efforts, establishing real-time data feeds, and architecting robust AI assistant platforms. As documented in McKinsey & Company's case evidence, organizations like Amazon, with its Alexa for Shopping tool, and Shopify, with its structured catalog, exemplify the benefits. Amazon reported that shoppers using Alexa for Shopping are 60% more likely to complete a transaction, with US users spending 40% more. Shopify's ability to double AI conversion rates through its structured catalog highlights the direct business impact of this readiness. The business risk of falling behind on this trend is severe: reduced conversion, fragmented customer journeys, and ultimately, erosion of market share to more agile, data-optimized competitors.

Expanding Horizons: Accelerated Market Penetration and Global Adoption

This trend highlights the dual acceleration of agentic commerce, both geographically and across previously lagging e-commerce categories. The market mechanism driving this shift is the ability of AI agents to simplify complex purchasing decisions and remove friction in historically underserved online sectors. McKinsey & Company finds that more than half of global consumers now use AI tools for shopping, with China and India significantly outpacing Western markets in adoption. This indicates a rapid normalization of AI as a shopping interface.

Moreover, agentic commerce is unlocking rapid online growth in historically underpenetrated e-commerce categories. The report notes that sectors like grocery (which held only a 9% online share of retail sales in the US in 2025) and beauty/personal care (22% share) are rapidly closing the gap in online penetration thanks to agentic tools. The practical implementation involves adapting AI solutions to the specific complexities of these categories, such as managing perishable goods in grocery or personalized recommendations in beauty. The business risk of neglecting this trend is missing out on substantial new revenue streams and allowing competitors to establish early leadership in these burgeoning online segments, particularly in high-growth international markets.

Redefining Engagement: Winning the AI Consideration Set and Measurement Imperatives

The third core trend centers on the strategic imperative for brands to adapt their marketing and measurement frameworks to the agentic era. The underlying market mechanism is the shift in how consumers discover and choose products, moving from traditional search and advertising to AI-driven shortlists and recommendations. The report explicitly states that CMOs must reallocate budgets toward AI search optimization and third-party authority to secure a place on agent shortlists.

Practical implementation demands a fundamental rethink of marketing spend and a new focus on 'AI consideration set' strategies, defending a shrinking group of non-AI users at minimal cost, and capturing fast-growing AI samplers early. Concurrently, brands need continuous, automated measurement systems to track how AI agents interpret consumer intent and rank products. This necessitates robust analytics capabilities to understand AI agent behavior and optimize product visibility within these new interfaces. The business risk of failing to adapt marketing strategies is direct: brands will become invisible to a rapidly growing segment of AI-driven shoppers, losing critical market share and brand relevance as purchasing decisions are increasingly mediated by intelligent agents.

Strategic Implications & Practitioner Verdict

Based on McKinsey & Company's 'McKinsey Agentic Commerce Trends,' executive leadership and enterprise teams must prioritize a multi-faceted strategic response. First, a data-first mandate is critical: invest heavily in clean, real-time product information and the infrastructure for owned AI shopping assistants. This forms the bedrock for agentic readiness. Second, recalibrate marketing budgets to explicitly target AI search optimization and build third-party authority, understanding that the AI consideration set is the new battleground for brand visibility. Third, establish cross-functional agentic commerce governance with an empowered senior leader to drive rapid decision-making and break down organizational silos. Lastly, develop robust, continuous measurement systems to understand and optimize how AI agents interpret consumer intent and rank products, ensuring adaptability in a dynamic environment.

Nathan Grotticelli, Founder and CEO of SearchShopAI and Growth Marketing Lead at Google, offers a compelling conceptual lens that views agentic commerce, MCP (Multi-Channel Platforms), and XR (Extended Reality) as a converging stack. When their Human Agent is queried through Fodda, it explains that the future of commerce will arrive rich and cross-media, rather than as a simplistic text box, emphasizing the need for brands to prepare for an immersive and interconnected shopping experience where agents operate across diverse digital environments.

The strategic takeaway is clear: future resilience will be predicated on proactive investment in AI-ready data infrastructure, dynamic marketing adaptation to AI-mediated discovery, and agile governance structures, all while anticipating a rich, cross-media agentic future rather than a text-box constrained one.

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