Agentic Commerce: Hype or is AI Transforming Online Shopping?

TL;DR

Agentic commerce is transforming online shopping by empowering autonomous AI agents and large language models (LLMs) to independently manage the entire purchasing process-from search and negotiation to checkout-delivering hyper-personalized experiences, greater efficiency, and lower costs, while requiring businesses to optimize for AI discoverability and navigate new challenges in authentication and payments, ultimately signaling a fundamental shift in digital retail where AI agents become the primary decision-makers.

Intro

The digital retail landscape is undergoing a seismic shift. As traditional e-commerce is in decline after COVID-19, a new paradigm—Agentic Commerce—is emerging, powered by autonomous AI agents and large language models (LLMs) that not only assist but independently optimize and execute shopping tasks. This evolution is redefining how consumers interact with brands, how businesses operate, and how the entire ecosystem of online shopping functions.

What is Agentic Commerce?

Agentic commerce represents the next frontier in digital retail, where AI-powered agents autonomously search, negotiate, and complete transactions on behalf of users and businesses. Unlike traditional e-commerce, which relies on manual browsing and purchasing, agentic commerce leverages intelligent agents to manage the entire process, from discovery to delivery, with minimal human intervention. These agents, built on advanced machine learning and large language models, are capable of:

• Predicting consumer needs before they arise
• Personalizing product recommendations in real time
• Negotiating prices and applying discounts

This approach delivers unprecedented efficiency, personalization, and cost savings, fundamentally changing both the consumer experience and business operations.

Agentic Commerce vs. Agent-Led Commerce vs. Traditional E-Commerce

How Do AI Agents Work in Agentic Commerce?

AI agents in agentic commerce go far beyond the capabilities of traditional e-commerce tools. Their core features include:

• Action Chaining: Rather than handling isolated tasks, agentic AI agents link multiple actions—searching, comparing, purchasing, tracking—into a seamless, end-to-end process.
• Contextual Intelligence: These agents analyze vast datasets in real time, adapting to changing circumstances and refining decisions based on ongoing feedback.
• Conversational Commerce: AI agents engage shoppers through natural language, answering questions, making recommendations, and facilitating transactions instantly.

Shopping agent capabilities

LLMs, much like Google, know the customer better than they know themselves due to their search history. Shopping agents in agentic commerce are defined by:

• Deep Personalization: Leveraging user data, preferences, and behaviors to provide hyper-relevant suggestions.
• Proactive Engagement: Anticipating needs and offering solutions before the user initiates a search.
• Operational Efficiency: Reducing manual effort, speeding up decision-making, and increasing conversion rates for e-commerce shops.

Impact: Businesses optimizing for AI agents experience higher conversion rates, reduced cart abandonment, improved customer retention, and lower operational costs.

How to make an LLM discover your website: GEO & AEO

• Generative Engine Optimization (GEO): Ensures content is optimized for generative AI model training, making it recognizable and relevant.
• Answer Engine Optimization (AEO): Focuses on structuring information for direct, concise answers, crucial for AI-driven search and conversational commerce, especially for content and product data.

Find our best practices in our separate blog post: Top 5 Strategies for LLM Visibility

Overcoming Challenges: Navigation and Authentication

While agentic commerce promises a frictionless experience, several challenges remain:

• Navigation: Current AI agents often mimic human interactions on websites, which is inefficient. OpenAI Operator, for example, uses screenshots as context for their ChatGPT to make the next click for the user. The future will see the rise of agent-optimized platforms and APIs designed for direct agent-to-system communication. This is where model context protocols (MCPs) and llms.txt will most likely play a pivotal role for a modern e-commerce shop.
• Authentication: Is this AI Agent sent by a human with an intent to buy or a competitor with a spying intent? That is a question not solved yet, leaving room for start-ups in the future. Also, payment remains a hurdle as storing card details in AI memory is not PCI DSS compliant. As a potential solution, it is estimated that digital wallet usage to rise by 50% by 2026, and biometric authentication could secure 90% of online transactions by 2027.

The Agentic Commerce Revolution: What’s Next?

Agentic commerce is more than just a technological upgrade—it is a structural shift in digital retail.

By harnessing autonomous AI agents, businesses can deliver smarter, faster, and more intuitive experiences while staying ahead of e-commerce trends. As agent-led commerce becomes a sub-layer within this broader revolution, the winners will be those who adapt their strategies for a world where AI agents, not just humans, are the new decision-makers.

Similar to brick and mortar retail stores in the early 2000s, thinking that the internet is hype, webshops are now at the pivotal crossroads deciding if they want to embrace agentic commerce or risk becoming irrelevant in the future.