Originally published July 2025. Updated November 2026 to add what happens when AI becomes the customer, agentic content production, and current Amplience product names.
Agentic AI is AI that acts on goals instead of waiting for prompts. In retail, AI agents watch for triggers such as a new product, a price change or a trend, then plan and complete multi-step work across your systems, from content and pricing to service, with people approving what matters.
But a new evolution is taking center stage now: agentic AI. This leap beyond simple robotic process automation (RPA) allows for dynamic, intelligent decision-making instead of just repetitive task execution, making it especially impactful in the retail sector, where dynamic workflows and customer experience are critical to success.
Here’s what agentic AI is, how it differs from generative AI, and how it’s changing retail workflows.
Key takeaways
Generative AI answers. Agentic AI acts, planning and carrying out multi-step work toward a goal.
Retailers are using agents for supply chain, pricing, service and content production.
AI shopping agents are now customers too, and they need structured content plus live price, stock and policy data.
Agents are only as good as the systems they connect to, so API-first platforms come first.
People set the goals and approve what matters. Agents handle the volume.
What is agentic AI?
Agentic AI combines new forms of artificial intelligence (AI) like large language models (LLMs), traditional AI such as machine learning, and enterprise automation to create autonomous AI agents that can analyze data, set goals and take actions to achieve those goals — with as much human oversight as you choose. These agents are capable of decision making, learning, and problem-solving, improving through every interaction.
How agentic AI works: key capabilities of agentic AI:
Autonomous decision-making
Goal-oriented behavior
Iterative task execution
Adaptability to dynamic environments
Agentic systems are more than just “smart tools“— they are digital collaborators capable of operating in complex, continually changing environments. By enabling machines to act independently in these environments, agentic AI is redefining what automation can achieve.
Agentic AI vs. Generative AI: what’s the difference?
While generative AI (e.g. ChatGPT, DALL·E, Midjourney) focuses on creating new content such as text, images, and video, agentic AI focuses on acting autonomously to make decisions and take actions. It can not only generate content but also plan, coordinate, and execute actions over time to achieve specific objectives.
Generative AI: Focuses on creating new content. It answers.
Agentic AI: Focuses on achieving specific goals. It acts.
Real-world applications of agentic AI in retail
The retail industry thrives on efficiency, personalization, and timing — all areas where agentic AI excels. According to Salesforce’s Connected Shoppers Report, 43% of retailers are piloting autonomous AI, with another 53% evaluating its use cases.
Here’s how agentic systems are revolutionizing retail workflows:
Supply chain optimization
Agentic AI can monitor inventory levels, analyze trends, and automatically reorder stock, reroute shipments, or identify supply chain disruptions. These agents can act across systems—ERPs, warehouses, and logistics platforms to ensure real-time optimization, which minimizes overstock and stockouts, ensuring that products are always readily available for consumers.
Dynamic pricing and promotion management
Retailers can use agentic systems to adjust prices on the fly based on demand, competitor pricing, seasonality, and customer behavior. Promotions can be launched, paused, or tailored dynamically without human oversight.
Omnichannel coordination
Agentic AI helps to create consistent omnichannel experiences with Amplience CMS by synchronizing data across in-store and digital platforms, ensuring real-time inventory visibility, unified pricing, and consistent promotions across all customer touchpoints.
Proactive issue resolution
From delivery delays to customer service requests, agentic AI can autonomously identify problems and present solutions — e.g. sending notifications, rerouting shipments, or escalating issues to humans only when needed.
Content production
When a new product arrives, Amplience Workforce can pull its data from the PIM, write on-brand descriptions, build localized versions and tag its assets in Amplience DAM, then route everything for approval before it goes live. Landmark Group uses Amplience Workforce to generate product descriptions, and Tapestry generates alt text across its product library for brands including Coach and Kate Spade.
Spotting search trends
Agents can watch search trends and customer behavior and flag opportunities. If searches for “vegan leather handbags” start to rise, an agent can alert the marketing team, or draft a landing page for them to review.
What happens when AI becomes the customer?
Agentic AI isn’t only working inside retailers. It’s shopping on behalf of customers too. Forrester found that 34% of UK and 26% of US online adults used ChatGPT to search for products in 2026, and AI agents increasingly find, compare and recommend products before a shopper visits a site.
To be chosen, products need two things. The first is meaning: structured product content an agent can read and compare. The second is live truth: up-to-date price, stock, delivery and policy data from the brand’s own systems.
Amplience provides the meaning. Amplience CMS models content as structured, AI-ready objects, Amplience DAM stores assets with the metadata machines need, and Amplience Workforce runs the content supply chain that keeps it all current. Read more on how to get products cited in AI search.
How agentic AI improves the customer experience
As back-end workflows become more intelligent and efficient, the front-end experience for customers improves dramatically.
Better customer service
Agentic systems can handle routine requests instantly — like tracking an order or issuing a refund — minimizing wait times and improving customer satisfaction.
Agentic AI systems can also keep track of all the interactions a customer has with a retailer, across all their channels. That means, for example, that customers who initially emailed with a query don’t have to repeat information when following up with a phone call, giving them an easier and less stressful service.
Hyper-personalization
With access to customer behavior and inventory data, AI agents can provide tailored recommendations, personalized promotions, and even assist in virtual shopping through AI-powered personal assistants. Agentic AI is capable of perfecting the balance of delivering personalized experiences without compromising the privacy and security of customers’ personal data.
Fewer errors
Automation reduces human error in order fulfillment, pricing, and communication, creating a more reliable and trustworthy brand experience.
Seamless omnichannel experience
Whether a customer is shopping online, in an app, or in a physical store, agentic AI ensures consistency in product availability, pricing, and support.
How retailers can increase productivity and create value for customers with agentic AI
By powering next-generation AI agents to perform a wider array of tasks, agentic AI vastly expands what can be automated. Furthermore, it improves the quality of interactions between agents and humans. Rather than replacing human employees, agentic AI systems can enhance human performance, productivity, and engagement. By seamlessly integrating with existing systems and processes, agentic AI systems can form a powerful partnership with retail workforces.
And by providing personalized and responsive experiences at scale and speed, agentic AI helps retailers revolutionize customer interactions to deliver better digital experiences. Leveraging sophisticated models, AI agents can infer customer intent, predict needs, and offer tailored solutions, all while operating 24/7 to ensure consistent and efficient support.
Putting agentic AI to work: key considerations for retail
Adopting agentic AI is more than a technology upgrade; it’s a strategic shift. To ensure success, retailers should focus on a few key principles.
Start with a high-impact use case
Begin by targeting a single, well-defined business problem. This could be optimizing stock levels for a key product line or automating the creation of a personalized product discovery experience. Success requires clean, accessible data from your entire tech stack, from your PIM and CMS to your commerce platform.
Prioritize API-first integration
Agentic AI is only as powerful as the systems it can connect to. To be effective, it must integrate seamlessly with your headless CMS, DAM, and commerce tools through a robust set of APIs. This creates the unified workflow necessary for real-time, autonomous action across your entire content and commerce supply chain.
Keep your teams in charge
The goal isn’t to replace merchandisers and marketers. Teams set the goals and rules, agents handle the repetitive work, and people approve what matters. In Amplience Workforce, you decide which content goes to a person for approval and which can publish automatically.
The future of retail is agentic
Agentic AI for retail gives businesses the opportunity to transform their operations and embrace innovation, improving workflow efficiency and delivering better customer experiences.
As retail businesses continue to embrace this next generation of AI, those that adopt agentic AI early will gain a competitive edge in both operational efficiency and customer loyalty.
Book a meeting with us today and find out how Amplience Workforce can help you automate tasks, enhance your workflows, and deliver exceptional, scalable digital experiences.