Agentic commerce and AI agents: what business leaders must know

Agentic commerce and AI agents are no longer theoretical. They are actively changing how people find, compare, and buy products online. In the past year, businesses saw a dramatic jump in AI adoption. Therefore, leaders must understand how AI agents shift customer control, media buying, and supply chains. This post walks through five clear trends drawn from recent reporting. It explains what is happening, why it matters, and what leaders should do next. The goal is practical clarity for managers and marketers.

## 1. Agentic commerce and AI agents are taking customer control

AI shopping agents are shifting power away from individual retailers. A new analysis highlighted by Digital Commerce 360 points to a Boston Consulting Group report that describes "agentic commerce" as a realignment in digital retail. In short, consumers will increasingly use AI tools to search, curate, and complete purchases on their behalf. These agents can compare prices, filter based on preferences, and act across multiple sites. Therefore, the direct relationship between shopper and retailer may weaken. Retailers that once controlled the storefront and data may find AI agents mediating many interactions.

This trend matters because customer loyalty and first-party data are both at stake. However, there is opportunity. Retailers who expose structured product data, open APIs, and commerce-friendly interfaces can be the preferred partners for agents. Additionally, brands that focus on unique value — like exclusive bundles, trusted fulfillment, or memorable service — create reasons for agents to choose them. Expect a transition period where marketplaces, brands, and platforms experiment with how to align incentives with agent developers. The bottom line: prepare for more mediated shopping journeys and rethink where value sits in the funnel.

Source: Digital Commerce 360

2. agentic commerce and AI agents are accelerating enterprise AI adoption

Enterprise adoption of AI is surging. Salesforce reported a 119% upsurge in AI use during the first half of 2025, based on its Agentic Enterprise Index. Therefore, companies are rapidly moving AI from pilots to real customer-facing roles. The data show that both consumers and businesses are more willing to interact with AI agents, especially in service and discovery tasks. This acceptance lowers a key barrier to agentic commerce: user trust in automated helpers.

For enterprises, this shift demands change in capabilities and governance. First, customer experience teams must redesign interactions to account for agents acting autonomously for customers. However, it's not only UX work. IT and product teams must consider integration points where agents pull catalog data, prices, and availability. Additionally, legal and compliance teams should set policies for how agents can access customer data and act on behalf of users. Companies that move fast will gain a foothold by offering agent-friendly APIs and transparent data practices. Therefore, plan investments across CX design, data hygiene, and policy to harness this rapid adoption.

Source: CX Today

3. agentic commerce and AI agents could change how customers browse and decide

Browser-level AI is turning passive browsing into active assistance. OpenAI’s Atlas browser integrates ChatGPT directly into web browsing, offering search, summarization, and agent-style capabilities. Therefore, shoppers may soon use browsers that summarize product pages, compare options across stores, and even complete checkout flows. This makes browsing an active, agent-driven experience rather than a manual search process.

For e-commerce teams, this is both a threat and an advantage. On one hand, retailers could lose control of the narrative if agents rewrite or summarize product pages without context. However, on the other hand, businesses that optimize content for agent consumption — clear specs, structured data, and strong trust signals — will surface more accurately in agent queries. Additionally, UX teams should test how product content reads when summarized. Simple changes to descriptions, headlines, and metadata can improve how agents represent your products. In short, prepare for a browsing environment where the browser itself is an assistant. Companies that adapt content and technical plumbing will shape how agents recommend them.

Source: CX Today

4. Programmatic ads and media buying must adapt to cross-channel agent influence

Agentic shopping will ripple into advertising. Comcast’s move to include linear TV in cross-channel programmatic ad buys shows how media firms are unifying inventory across digital and traditional channels. Therefore, as AI agents steer more shopping decisions, marketers will need unified measurement and buying tools that reflect where attention — and agent recommendations — actually occur.

This development matters for growth teams and media planners. If agents favor certain brands or marketplaces, ad attribution models must adjust to capture that influence. Additionally, a unified bidding workflow across TV and digital allows marketers to reach audience segments at scale while measuring impact consistently. However, advertisers must also rethink creative. Short-form, clear messaging that translates well to agent summarization will likely perform better. Finally, coordination between media buying teams and product/commerce teams will be crucial. Therefore, invest in cross-channel planning, measurement, and creative testing to ensure ads contribute to the agent-driven purchase paths.

Source: Marketing Dive

5. Logistics and fulfillment strategies become competitive levers in agentic commerce

As shopping becomes mediated by agents, speed and reliability grow in importance. Essendant’s decision to exit a legacy market and accelerate e-commerce and logistics modernization illustrates this point. The company formed a three-year partnership with Hub Group to introduce a managed delivery model aimed at improving fulfillment offerings. Therefore, distribution and delivery capabilities are now core parts of the customer promise.

This matters because AI agents will rank offers not only on price and reviews but also on delivery certainty and convenience. Companies with agile logistics can win recommendations. Additionally, investing in managed delivery or better tracking reduces friction for both customers and agents. However, logistics modernization takes time and budget. Prioritize initiatives that improve visibility and lead times. For example, partner networks and managed services can accelerate capability while limiting capital outlays. Ultimately, the firms that link strong logistics to agent-friendly data signals will capture higher conversion and loyalty.

Source: Digital Commerce 360

Final Reflection: Preparing for an agent-first commerce era

Taken together, these stories point to a clear arc: AI agents are becoming active participants in commerce. Therefore, retailers, brands, and marketers must rethink where value sits in the customer journey. Start by exposing structured product and fulfillment data. Next, align CX, legal, and IT around agent access and permissions. Additionally, adapt creative and measurement to account for agent-influenced touchpoints across TV, web, and apps. Finally, treat logistics as a strategic differentiator rather than a cost center.

The good news is practical steps can deliver early wins. Structured data and clearer product pages improve visibility quickly. Pilot partnerships with logistics providers can shorten timelines. And integrated media buying gives marketers better feedback loops. However, this transition will reward organizations that plan across product, marketing, and operations. Therefore, move from experimentation to intentional capability-building. The next five years will favor businesses that meet the agent where it lives — in the browser, in the ad stack, and in the supply chain — and that design for trust, speed, and clarity.