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Customer first

Retail’s next evolution: Preparing for agentic customer experience

Retailers have spent years refining experiences for customers moving across search engines, websites, apps, digital marketplaces, and physical stores. But now, agentic AI is beginning to change how consumers engage with retailers throughout that journey.

Intelligent agents are more than just a hot topic. Retail customers and businesses alike are already recognizing their practical value. According to the Capgemini Research Institute’s Reimagining customer experience: Human-led, AI-powered report, 58% of consumers believe AI agents can save them time when making routine monthly purchases and payments. The same report indicates that 68% of organizations believe AI agents will outperform traditional CX channels.

As confidence in these technologies grows, retailers must prepare for a future where customers increasingly rely on AI agents to discover products, make informed decisions, complete purchases, and resolve issues.

“Agentic commerce is one of the most common questions we get from consumer products and retail clients. Consumers are already using LLMs to shape what they buy, and the leading retailers and consumer brands are treating that as a “channel” to win in.”

Dreen Yang, EVP Global Industry Leader, Consumer Products & Retail

Three considerations for agentic CX

Customer experience is one of the areas where agentic AI carries the greatest potential. But building an agentic customer experience model requires more than deploying a conversational interface or modernizing customer service.

Retailers must create experiences that understand customer intent, connect interactions to meaningful action, and preserve continuity across every touchpoint. As organizations prepare for this shift, we believe three areas deserve particular attention.

Many retail experiences are structured around channels, departments, or predefined customer journeys. The challenge is that customers rarely think in these terms. Instead, they’re focused on accomplishing a specific goal.

Whether a customer is researching a product, comparing options, making a purchase, or seeking support after delivery, the experience should adapt to the underlying intent behind the interaction. A shopper searching for products for an upcoming vacation has different needs than someone searching for a replacement after a product failure, even if both begin with similar queries.

Preparing for these models requires retailers to identify the signals that help recognize customer intent across discovery, purchase, and post-purchase interactions. By understanding the context surrounding a customer need, retailers can create experiences that remain relevant regardless of where or how engagement begins.

Understanding intent is only valuable when it leads to meaningful outcomes. An agent helping a customer find the right product needs access to inventory, pricing, promotions, and availability. An agent assisting with a delivery issue may require order history, fulfillment status, and service policies. Without access to trusted business systems and operational data, even the most intelligent agent can do little more than provide information.

Retailers should connect customer-facing agents with the systems that support commerce and service operations, while clearly defining the actions agents can perform at different stages of the customer lifecycle. The opportunity lies in moving beyond conversation alone and creating models where agents can take action on behalf of customers when appropriate.

Agentic experiences will not eliminate the need for human expertise. Certain purchasing decisions may benefit from specialist guidance, while some customer situations will continue to require human judgment and empathy.

When employees become involved, the customer context should move with them. Teams should have immediate visibility into customer intent, prior interactions, recommendations already provided, and any actions an AI agent has taken. This prevents customers from repeating information and enables employees to focus on resolving the issue or progressing with the customer’s request. Retailers should design these interactions across both commerce and service experiences so that context follows the customer wherever the journey leads next.

How Capgemini and Google Cloud can help

The challenge for retailers is turning these principles into operational capabilities. Delivering agentic customer experiences requires more than individual AI tools. It depends on connecting customer interactions, enterprise data, and business processes across the retail lifecycle.

At Google Cloud Next 2026, we showcased how our long-standing partnership with Google Cloud is helping retailers apply agentic AI across commerce and customer service. Our complementary solutions address both how customers discover and purchase products and how retailers support customer needs beyond each transaction.

Gemini Enterprise for CX

Gemini Enterprise for CX brings shopping and customer service together through an agentic solution that spans product discovery to post-purchase resolution. Using the solution, retailers can build and manage agentic systems that use advanced reasoning to understand customer intent and provide conversational support informed by customer preferences and consent.

Agentic commerce with Google Cloud

Agentic commerce helps transform customer intent into connected purchasing journeys. Intelligent agents can guide product discovery, compare options, coordinate transactions, and help manage post-purchase activities across multiple systems – supporting the path from discovery and evaluation through payment, delivery, and returns. It helps retailers move from conversational engagement toward action across the buying lifecycle.

Bringing the cloud to the restaurant

Using Google Distributed Cloud, we help quick service restaurants unlock a new era of in-store innovation. We combine Google Cloud technology with our industry expertise to scale cutting-edge AI experiences that transform restaurants into intelligent hubs that deliver hyper-personalized service and next-gen operational efficiency.

Intelligence-powered store management

Together with Google Cloud, we help grocery stores run more intelligently. Combining Google Distributed Cloud for resilient in-store systems and Vertex AI for predictive analytics, we help grocers predict demand, optimize inventory, and build customer loyalty through personalization.

Enabling next-gen monetization

Using Google’s immersive AI technologies, we connect the digital and physical worlds to enable stores to create hyper-realistic, interactive shopping experiences. Our solution allows customers to virtually “try on” products or explore digital twins of physical store locations, blurring the lines between channels to drive higher engagement, confidence, and sales.

Building an intelligent B2B supply chain

Using Google’s core AI platform, we’re helping build more efficient wholesale supply chains. Our solution helps wholesale retailers manage inventory, enhance procurement, and create shared visibility across the supply chain to improve fill rates and margins.

These joint solutions exemplify how we’re driving real value across retail with Google Cloud. Our approach has been recognized by Everest Group, which ranked Capgemini as the leading Google Cloud service provider in the 2026 PEAK Matrix® assessment. According to Everest Group, “BSFI, retail, and telco enterprises prioritizing CX modernization at scale can benefit from Capgemini’s newer agentic AI-led CX capabilities on Google Cloud to scale AI-driven service operations.”

Meeting evolving customer expectations

As consumers become more comfortable using AI agents to support purchasing decisions, resolve issues, and navigate complex interactions, expectations will continue to evolve. Retailers that organize experiences around customer intent, enable agents to take meaningful action, and preserve context across every interaction will be better positioned to meet those expectations.

Success depends on crafting experiences that remain seamless, connected, and responsive regardless of whether the interaction begins with a person or an AI agent.

Ready to explore how your enterprise can make intelligence real? Connect with our Google Cloud experts to begin your journey toward business impact: googlecloud.global@capgemini.com

Research and insights

Capgemini Research Institute

Reimagining customer experience: Human-led, AI-powered

capgemini-research-institute capgemini-research-institute

Expert perspectives

Data and AI

Living in an agentic world with Gemini-powered AI agents 

Herschel Parikh
Oct 9, 2025

Meet our experts

Herschel Parikh

Herschel Parikh

Global Google Cloud Partner Executive
Herschel is Capgemini’s Global Google Cloud Partner Executive. He has over 12 years’ experience in partner management, sales strategy & operations, and business transformation consulting.
Franco Amalfi

Franco Amalfi

Director, Sustainability Strategic Initiatives and Partners – Americas
Accomplished professional with extensive experience, spanning sustainability, strategy definition, value selling, management consulting, software development, software implementation, and business development. Experienced in multiple industries; have worked with consumer products, financial services, government, telecommunications, high-technology, pharmaceutical and retail companies.
Jennifer Marchand

Jennifer Marchand

Enterprise Architect Director and GCP CoE Leader, Capgemini/Americas
Jennifer leads the Google Cloud COE for Capgemini Americas, with a focus on solutions and investments for the CPRS, TMT, and MALS MUs, and supporting pre-sales across all MUs. She has been with Capgemini for 18 years focusing on cloud transformation since 2015. She works closely with accounts to bring solutions to our clients around GenAI, AI/ML on VertexAI and Cortex, Data Estate Modernization on Big Query, SAP on Google Cloud, Application Modernization & Edge, and Call Center Transformation and Conversational AI. She leverages the broader Capgemini ecosystem across AIE, Invent, ER&D, I&D, C&CA, and CIS to shape cloud and transformation programs focusing on business outcomes.
Chris Corso

Chris Corso

Sr. Solution Architect
Chris is a member of the Cloud and Custom Applications team for Capgemini with a focus on Google Cloud. He has more than 20 years of experience across a broad range of industries and functions, helping clients increase their IT agility and leverage technology to transform their business.
DanielWolff

Daniel Wolff

Financial Services – Global Head Google Cloud CoE
Daniel leads the Global Google Cloud Platform Center of Excellence. He is a senior technology executive known for accelerating sustainable company growth within financial services. He focuses on unlocking new opportunities for improved competitive advantage, cost containment, process re-engineering, and business agility.
Hemank Lowe

Hemank Lowe

Senior Director – Global Google Cloud Sub Practice Leader for Cloud and Custom Applications
Hemank is an experienced cloud expert with over 5 years in Google Cloud architecture, Generative AI, and data analytics, holding three Google certifications (Cloud Architect, Data Engineer, Cloud Digital Leader) and a Master’s in Computer Applications. With 22+ years of diverse industry experience, excels in delivering Enterprise architecture solutions on the Google Cloud Platform and advocating for technology in business transformations.
Rachel Belmonte

Rachel Belmonte

Head of Google Cloud Uk
Experienced Regional Head of Delivery with 13+ years extensive experience in IT Programme Delivery Management, primarily in Cloud and Digital Transformation. Led cross-functional teams of 80+ people. Proven record of operational excellence, customer and business relationship management, delivery management, employee development with strong commercial and business acumen.
Rob Kernahan

Rob Kernahan

Chief Architect for Cloud and a Global SME on Cloud Technology, Data and IT Operating Models
Rob is a member of the Capgemini CTO group as UK Chief Architect for Cloud and a Global SME on Cloud Technology, Data and IT Operating Models. Rob has over 20 years’ experience in Architecture and Delivery across a variety of sectors. Over the years he has led large transformational initiatives and has combined technology and people to create powerful outcomes.
Lauren Kenner

Lauren Kenner

Google Partner Development Executive
As a Google Partner Development Executive at Capgemini, I lead strategic growth and joint go-to-market efforts across the Google Cloud portfolio, aligning Google’s strengths with Capgemini’s expertise to drive client impact and market expansion. I work closely with Google teams and Capgemini stakeholders to enhance partner alignment, deepen client relationships, and create scalable solutions for measurable results. Holding a BFA from the University of Michigan, I apply a creative, human-centered approach to my work. Additionally, I’m committed to fostering culture and community through initiatives like Welcome Wednesdays and leading Capgemini’s HOLA ERG.
Geoffroy-Pajot

Geoffroy Pajot

Vice-President and Chief Technology and Capability leader for the global Google partnership
Geoffroy brings over 20 years of distinguished experience in Business and Technology transformation, with a strategic emphasis on global partnership development to drive sustainable growth. Currently, he leads the cloud and custom app Google Cloud practice and oversees pivotal initiatives, including the Google Cloud Generative AI Center of Excellence. His expertise centers on advancing data & AI business transformation and innovation while enhancing group-wide Google Cloud capabilities. Beyond his professional commitments, Geoffroy is passionate about wellness and athletic pursuit.

    Partner

    Google Cloud

    Frequently asked questions

    Agentic customer experience in retail refers to the use of AI agents that can understand customer intent, reason across available information, and support actions across the shopping and service journey. Unlike traditional digital experiences that are often structured around channels or predefined journeys, agentic CX is designed around what the customer is trying to achieve, whether that is discovering a product, comparing options, completing a purchase, or resolving an issue after delivery.

    AI agents can improve customer experience by helping shoppers find relevant products faster, compare options more easily, receive personalized support, and resolve routine issues with less friction. When connected to trusted business systems, agents can move beyond answering questions to supporting meaningful actions, such as checking availability, guiding purchase decisions, tracking orders, or assisting with returns. This can create more seamless, responsive, and context-aware experiences across discovery, commerce, and service.

    Retailers should organize customer experience around customer intent because customers are focused on accomplishing a goal, not navigating internal channels, departments, or predefined journeys. A customer researching a gift, replacing a failed product, or checking delivery status may use similar entry points but have very different needs. By recognizing the intent behind each interaction, retailers can provide more relevant support and create experiences that adapt to the customer’s context across discovery, purchase, and post-purchase moments.

    Customer-facing AI agents should connect to the systems that enable accurate information and meaningful action. These may include inventory, pricing, promotions, product data, order history, fulfillment status, CRM, loyalty platforms, service policies, and customer preferences where consent has been provided. By connecting agents to trusted commerce and service systems, retailers can help ensure that AI-led interactions are not limited to conversation but can support practical outcomes across the customer lifecycle.

    Agentic customer experience goes beyond the capabilities of a traditional chatbot. A chatbot typically answers predefined questions or guides users through scripted interactions. An agentic experience can understand intent, reason across context, connect to business systems, and support actions when appropriate. In retail, this means an AI agent could help a customer compare products, check availability, coordinate a transaction, or support post-purchase service rather than simply responding to a basic query.

    Employees continue to play an important role in agentic customer experiences, especially when situations require specialist knowledge, judgment, or empathy. AI agents can support routine interactions and provide context, but human teams remain essential for complex decisions, escalations, and high-value customer moments. The key is ensuring that when an employee becomes involved, the customer’s context moves with them, including prior interactions, customer intent, recommendations, and actions already taken by the AI agent.

    Capgemini and Google Cloud help retailers implement agentic customer experience by connecting customer interactions, enterprise data, AI capabilities, and business processes across the retail lifecycle. Through solutions such as Gemini Enterprise for CX and agentic commerce with Google Cloud, retailers can build experiences that support product discovery, purchasing journeys, customer service, and post-purchase engagement. Capgemini brings industry and transformation expertise to help retailers operationalize these capabilities and create connected, AI-powered customer experiences.