Agentic AI: Reshaping Commerce, Redefining Trust
The morning ritual was sacrosanct for Maria: a quiet cup of chai on her balcony, the city just beginning to stir below.
Yet, these days, even her solitude felt subtly augmented.
She recalled last week, needing new shoes for her daughter.
Instead of endlessly scrolling through sites, she simply murmured her intent to her smart assistant while stirring her tea.
Find durable, stylish, red sneakers, size 3, under $70, delivery by Friday.
A quiet chime, then a prompt approval.
Done.
No clicks, no comparisons, no shopping carts.
Later that day, a notification: Your daughter’s sneakers are on their way.
It felt like magic, yet it was simply an agent, her trusted digital proxy, acting on her behalf, navigating a vast ocean of options, making decisions, and completing a transaction.
This was not a futuristic fantasy, but a glimpse into the agentic commerce that is already reshaping how we buy and sell.
The ease, the speed, the almost invisible nature of the transaction highlights a profound shift: commerce is becoming less about the storefront and more about the intent, trust, and the intelligent agents mediating between us and the brands we choose.
It is a quiet revolution, but one that demands our attention, for it touches the very core of how businesses connect with their customers.
In short, Agentic AI is transforming retail by moving beyond traditional search to proactive discovery, autonomous payments, and trusted experiences.
This fundamental shift requires retailers to prepare now by building intelligent foundations for data, payments, and loyalty to thrive in this new era of agentic commerce.
Why Agentic AI Matters Now
The shift Maria experienced is far from isolated.
Agentic AI was the undercurrent of many industry conversations, hinting at a future where commerce is less a destination and more an embedded function of our daily lives.
This is not theoretical; it is here.
Agentic AI systems, unlike their reactive predecessors, act on intent.
They learn preferences, proactively recommend, and can even complete transactions autonomously.
This fundamental change is making AI agents the new starting point of the buying journey, dictating how brands compete for visibility, trust, and loyalty, according to SAP research.
The implications for retail and customer experience are significant.
Consider the scale of challenges retailers already face: global returns have surpassed $1.9 trillion annually and are growing faster than sales, as reported by IHL Group.
This is not merely a cost; it is a symptom of a disconnect, a friction point that agentic AI, when harnessed intelligently, promises to redefine.
Moving beyond the hype, the focus at SAP is squarely on turning this potential into real, scalable outcomes for retailers today.
Discovery Shifts: From Search to Intelligent Agents
For decades, the path to purchase was well-trodden: search engines, marketplaces, then a brand’s own storefront.
That model is now actively shifting.
Answer engines and AI shopping agents are emerging as new entry points for commerce, often engaging shoppers before they ever consider visiting a retailer’s site, SAP notes.
This is more than just a new channel; it is a new mediator.
AI agents do not just present options; they reason, decide, and act on a shopper’s behalf.
This introduces a counterintuitive insight: success is no longer about simply ranking on a search page.
It is about ensuring your products are visible, understandable, and trusted by machines that influence human purchase decisions.
Imagine a retailer who has meticulously optimized their website for human search queries, only to find their products invisible to a shopper’s AI agent because the underlying product data is not machine-readable.
This calls for a fundamental re-evaluation of where marketing attention should be directed.
A New Frontier for Product Content
In this agent-driven world, product content transcends its traditional role as a marketing asset.
It becomes, quite literally, operational infrastructure.
An AI agent cannot recommend what it cannot interpret.
Every attribute, image, specification, availability signal, and proof point directly influences whether a product is surfaced, compared, or selected, according to SAP.
This is where the concept of generative engine optimization (GEO) emerges, demanding that optimization serves two distinct audiences: humans and machines.
Product data must be structured, consistent, and enriched to allow AI agents to confidently represent it to shoppers.
The Catalog Optimization Agent in SAP Commerce Cloud offers a glimpse into this future, transforming how merchants manage vast product data.
This AI agent can clean catalogs, enrich attributes, standardize details, fill gaps, and support multilingual content using real-time data.
It scales to catalogs with over 10 million items, helping teams improve content 70 percent faster, increase data completeness by 5 percent, and reduce maintenance effort by 63 percent, according to SAP Commerce Cloud insights.
With such AI-ready product data, retailers can precisely match shopper intent, optimize merchandising across channels, and make smarter pricing and delivery decisions.
The Agentic Commerce Playbook: Data, Payments, and Returns
As these intelligent agents mediate more interactions, retailers must rethink core operations.
SAP’s vision for agentic commerce is bold, showcasing a future where humans and AI agents collaborate to drive intelligent recommendations, proactive operations, and deeper customer relationships.
While the vision points forward, SAP’s focus remains firmly grounded in providing practical, actionable steps today.
The research tells us that agentic AI acts on intent, not just prompts, fundamentally changing the starting point of the buying journey and influencing how brands vie for visibility and loyalty.
Therefore, retailers must now strategize for agent visibility, crafting content and experiences that appeal to algorithmic decision-makers.
It also highlights that product content is the new operational infrastructure; for AI agents to recommend products effectively, the underlying data must be structured, consistent, and enriched.
This means investing in tools like the Catalog Optimization Agent in SAP Commerce Cloud can significantly boost content management efficiency and data quality.
Furthermore, payments must become invisible and flexible.
Fragmented buying journeys across devices, channels, and agents demand payment solutions that are seamless and secure, integrating directly into agent workflows.
This necessitates adopting modern, headless payment architectures that support diverse methods and ensure compliance.
Finally, returns are evolving into a strategic intelligence engine.
With global returns exceeding $1.9 trillion annually and growing faster than sales, returns are no longer just a cost center.
AI-enabled decision-making for keep, reject, or return based on loyalty, margin, and lifetime value can transform returns into a powerful loyalty builder and improve operational forecasting and product quality, SAP research shows.
Building Foundations for Agentic Trust and Loyalty
To thrive in this new landscape, retailers need a proactive playbook focused on building the right foundations.
This involves mastering product data through generative engine optimization, treating product content as operational infrastructure, and standardizing, enriching, and validating data for machine readability.
Tools like the Catalog Optimization Agent for SAP Commerce Cloud can improve content 70 percent faster.
Another crucial step is enabling agent-first discovery, ensuring products are visible and understandable to AI agents by utilizing solutions like the storefront MCP server for SAP Commerce Cloud, which enables engagement with various AI agents and supports channel-less commerce across multiple protocols.
Future-proofing payments is also vital, requiring the adoption of flexible, headless payment architectures such as the open payment framework for SAP Commerce Cloud.
This supports diverse payment methods and seamlessly integrates into agent workflows, enabling frictionless, secure transactions.
Retailers should also transform returns into an intelligence function, shifting from viewing returns as a cost to a strategic data source.
Implementing AI-powered returns management, such as SAP Order Management Services, can analyze loyalty, margin, and lifetime value, turning a revenue drain into a growth lever.
Cultivating cross-channel loyalty means designing adaptive loyalty strategies that reward engagement across all touchpoints, whether traditional or agent-mediated.
SAP Customer Loyalty Management enables personalized offers based on real-time behavior.
Finally, unifying data and operations involves integrating core systems like SAP ERP and SAP Commerce Cloud to create a single source of truth.
Organizations using both platforms have achieved up to 80 percent lower total cost of ownership (TCO) and up to 105 percent to 245 percent revenue uplift from hyper-personalized experiences, according to Enterprise Strategy Group.
Navigating the Ethical Horizon of Agentic Commerce
As agentic systems influence more of commerce, trust emerges as the most valuable asset a retailer can protect.
Consumers must have absolute assurance that their data, preferences, and payments are secure and governed responsibly.
Retailers and commerce providers are increasingly becoming AI trust custodians, tasked with balancing the immense power of intelligence with deterministic constraints and ethical governance, as highlighted by SAP.
This requires transparency about how agents operate, clear opt-in preferences for data usage, and robust security protocols.
On-site AI can scale associate expertise and personalization, but it must do so while preserving brand integrity and customer confidence.
The ethical dimension is not an afterthought; it is the core responsibility in an intelligent commerce ecosystem.
Essential Tools and Metrics for Agentic Success
To effectively navigate this new frontier, retailers need the right tools and a clear framework for measuring success.
The SAP Commerce Cloud ecosystem offers a robust foundation, including SAP Commerce Cloud with its storefront MCP server for agent engagement and Catalog Optimization Agent for data quality, SAP Order Management Services for intelligent returns and unified order/inventory visibility, and SAP Customer Loyalty Management for adaptive, agent-aware loyalty programs.
Key Performance Indicators (KPIs) for the agentic era include Agent-Initiated Purchase Conversion Rate, which tracks the percentage of transactions completed by AI agents; Product Data Completeness Score, a metric of how well product attributes are structured for AI interpretation; Returns Rate by AI-driven Decision, tracking the effectiveness of AI in managing returns and its impact on customer loyalty; Customer Lifetime Value (CLTV), comparing CLTV for agent-mediated versus direct purchases; and Agent Interaction Resolution Rate, measuring how effectively AI agents resolve customer intents without human intervention.
Reviewing these metrics quarterly for strategic adjustments and monthly for operational performance will be crucial to refine your approach to agentic commerce.
Frequently Asked Questions
Agentic AI in commerce refers to systems that act on a shopper’s intent, proactively learning preferences, making recommendations, and completing transactions on their behalf, a contrast to traditional AI that simply responds to prompts, as SAP explains.
This paradigm shift means product discovery changes fundamentally, moving from consumers actively searching on websites to AI shopping agents and answer engines finding products for them, often before they even visit a retailer’s site.
SAP plays a crucial role in agentic commerce by providing foundational technologies like the storefront MCP server for channel-less engagement with AI agents, the Catalog Optimization Agent for product data, and flexible payment frameworks.
These tools enable retailers to participate and benefit from agentic commerce, leading to improvements in content management and data completeness.
Trust is paramount in an agentic AI world because as AI agents mediate more interactions, consumers must trust that their data, preferences, and payments are secure and handled responsibly.
Retailers become AI trust custodians who must balance intelligence with governance.
The Human Heart of Commerce
Maria’s seamlessly delivered sneakers might seem like a small detail in the grand scheme of commerce, but it embodies the profound shift underway.
It speaks to a future where convenience is not just about faster delivery, but about an almost prescient understanding of needs.
Commerce is becoming an ecosystem of intelligent interactions, where discovery, payments, fulfillment, and returns are all connected by agents acting on behalf of both shoppers and businesses.
The winners in this new era will be those who align product intelligence, flexible payments, data-driven returns, and above all, trust, across every touchpoint.
Agentic AI can make commerce more personal, efficient, and scalable—but only for those who build the right foundations today, emphasizes Kollen Glynn, Global Head of SAP Commerce Cloud for SAP Customer Experience.
Embrace this moment, build those foundations, and reimagine the very fabric of retail.
To learn more about how SAP Commerce Cloud is powering AI-driven commerce, visit sap.com/commerce.