Agentic AI commerce reshapes retail: what leaders must do now

Agentic AI commerce reshapes retail in front of our eyes. Within the space of a few product launches and forecasts, businesses now face new retail channels, automated tax work, and agents that can act on the web. Therefore, leaders must move from planning to practical decisions about product, compliance, and operations. This post walks through five linked developments and shows clear steps companies can take to keep growth on track.

## Agentic AI commerce reshapes retail: the new market in plain terms

The idea is simple but powerful: shopping may move from websites and apps into conversations that act for the buyer. Scot Wingo and others now estimate intelligent shopping agents could already support hundreds of billions in annual commerce. Therefore, what looks like a research trend is quickly becoming a market-scale channel. If agents can answer product questions and complete transactions, they will divert traffic and sales away from traditional storefronts.

For retailers and brands, this changes where and how customers discover products. Instead of optimizing search pages and paid search, companies will need to make products discoverable and verifiable by agents. Additionally, pricing, inventory visibility, and return policies must be agent-friendly. That means building structured product data, clear rules for substitution, and frictionless verification flows. Smaller players will either need middleware that exposes clean catalogs to agents or risk becoming invisible.

Impact and outlook: Agentic AI commerce is not an optional experiment. It will pressure retailers to rethink product data, listings, and customer rules. Businesses that prepare structured, agent-ready experiences will capture early share. Those who wait will see more revenue flow through agent-led channels.

Source: Digital Commerce 360

Agentic AI commerce reshapes retail: web-capable agents like Gemini 2.5

Google’s Gemini 2.5 moves the conversation forward by letting AI interact with websites on behalf of users. In practice, that means agents can browse, click, and complete tasks like a human would. Consequently, integrations and automation now matter more than ever. Companies must decide how much control to give web agents and how to protect experiences and conversions.

For product and engineering teams, the new capability raises several immediate questions. Will agents see the same product pages as humans? Will they favor specific signals like schema markup or API endpoints? Therefore, teams should prioritize machine-readable product data and robust APIs. Additionally, customer flows must account for automated agents making purchases or requesting returns. This creates both risk and opportunity: agents can increase conversion and cut friction, but they can also trigger unforeseen edge cases and fraud vectors.

For commerce leaders, the clear path is to test agent interactions now. Start by exposing structured data, monitoring agent-driven conversions, and building guardrails around pricing and substitutions. Also, collaborate with platform partners to ensure that web-capable agents respect your policies. Over time, those who treat agents as a first-class channel will win visibility and trust.

Source: news.google.com

Agentic AI commerce reshapes retail: automating tax, compliance, and paperwork

Avalara’s rollout of AI agents for tax and compliance shows that agentic automation is moving into operational back offices. Tax rules are complex and vary by district. Therefore, automating calculations, filings, and reporting could save time and reduce human error. Avalara’s agents are designed to sit in the compliance flow and handle these tasks for multi-district ecommerce operations.

This matters because tax and regulatory friction often slow cross-border expansion and marketplace growth. If AI agents can accurately map rates, file returns, and produce reports, small and mid-size sellers can scale faster without hiring large compliance teams. However, companies should implement strong oversight. Automated tax work still needs human audits and clear exception processes. Additionally, platforms and sellers must verify that agent outputs meet legal and accounting standards.

For commerce operations, the recommended steps are clear. First, pilot agentic compliance tools on lower-risk flows. Second, set up human review gates for filings. Third, monitor discrepancies and keep audit trails. Over time, compliance agents can become a competitive advantage, enabling more rapid marketplace expansion and cleaner financials.

Source: Digital Commerce 360

Marketplace scaling meets agentic AI: ditching manual work to grow faster

New survey data shows marketplace sellers are active on about six platforms on average. However, many of them still wrestle with manual workflows. Consequently, growth often gets choked by tasks like inventory updates, pricing changes, and order routing. Agentic AI can help by acting on marketplaces and systems to reduce manual toil and speed decisions.

For sellers, the most significant friction points are integration and scale. Posting the same product on multiple marketplaces requires constant updates. Therefore, sellers either centralize data with integration platforms or automate repetitive tasks. Agentic agents that can act across systems could remove layers of manual labor. But effective use requires clean master data and clear business rules. Agents should be trained to follow substitution rules, handle returns, and reconcile orders automatically.

Operational impact: Companies that adopt agentic automation for marketplace tasks will free staff to focus on merchandising, customer service, and strategy. Meanwhile, those that ignore automation will find margins squeezed by manual labor. The practical advice is to prioritize integration platforms and pilot agentic workflows for the highest-volume tasks first.

Source: Digital Commerce 360

Holiday demand and agentic AI commerce reshapes retail planning for peak season

Adobe’s 2025 holiday forecast predicts online sales will grow more than 5% versus 2024, and that AI’s influence will peak before Cyber 5. Therefore, marketing and operations teams must plan for an agent-driven holiday bump. Consumers will increasingly lean on generative AI and agents to discover products, compare deals, and complete purchases in the run-up to the biggest shopping days.

This changes the calendar for promotions and ad spend. If AI use peaks early, then retailers should start agent-optimized campaigns well before typical Cyber Week windows. Additionally, product data and promotions must be ready for agent queries. That means clear descriptions, standardized attributes, and predictable inventory signals. From an operations view, forecasting must account for agent-driven demand spikes and the possibility of different conversion patterns.

Actionable steps include testing agent interactions before the season, ensuring inventory control systems are agent-ready, and aligning promotions to be machine-readable. Consequently, retailers who build agent-aware holiday plans will capture early shoppers and avoid last-minute stockouts.

Source: Digital Commerce 360

Final Reflection: Preparing for an agent-driven commerce future

Across these five developments a single theme is clear: agentic AI commerce reshapes retail in ways that touch customer experience, back-office compliance, marketplace operations, and seasonal planning. Therefore, companies should treat agents as a real channel, not an experiment. The practical path is iterative: expose structured data, pilot agent workflows, automate compliance with oversight, and redesign holiday plans around agent behavior. Additionally, invest in monitoring and audit controls to manage risk.

This shift favors organizations that combine product discipline with operational rigor. Those who prepare will unlock new revenue channels, lower operating costs, and scale faster. Meanwhile, late movers risk losing discoverability and facing higher manual costs. The good news is that the tools and vendor support are already arriving. Consequently, the time to act is now: test small, govern firmly, and scale what works.