Most experiences described as agentic today are still assistive. They help buyers search, compare, and navigate options — but they do not independently complete the full buying process. That distinction matters. Commerce leaders need a clear view of what agents can do now, what comes next, and what their organizations must build before autonomous buying becomes routine.
We’re proud to share that several Perficient experts were interviewed as part of the research process for Forrester’s The State of Agentic Commerce, Q2 2026 (Forrester Research, Inc., May 2026). To Perficient, their participation reflects more than where the market is heading. It reflects where Perficient is already delivering today, bringing AI, data, commerce platforms, customer experience, and operations together to create measurable outcomes.
What the Report Reveals
Forrester’s report examines how agentic commerce could reshape product discovery and purchasing across consumer and business markets — and the gap between the current hype and where the technology actually stands today.
That gap should not be mistaken for a reason to wait.
According to Forrester,
Currently, approximately one in 10 users who regularly use answer engines are authorizing answer engines to act semi-autonomously (i.e., without direct supervision) to complete tasks for them. Another 23% say they haven’t done so yet but would in the future.
Fully autonomous commerce may still be taking shape, but AI-powered interfaces are already changing how buyers find and evaluate products. Answer engines and AI assistants can assemble recommendations before a buyer reaches a website, contacts a sales representative, or requests a quote.
The buying journey is not disappearing. Buyers are entering it through new channels.
For commerce leaders, that raises a more immediate question: Can AI systems find, understand, and accurately represent their products?
Product Data Determines Whether Agents Find You
Traditional commerce strategies have focused heavily on websites, search, marketplaces, and sales channels. Those experiences remain important. But an AI agent does not evaluate a product the way a person does.
The agent relies on available data to understand technical attributes, applications, pricing, availability, delivery options, and compatibility. When that information is incomplete or inconsistent, the product can leave the consideration set before the company receives any signal of buyer interest.
A person may contact sales for clarification. An AI agent can simply recommend a competitor.
This is especially critical in B2B commerce, where companies manage thousands of complex SKUs, account-specific catalogs, negotiated prices, and configuration-dependent products. Product information management cannot remain a one-time cleanup project. It must become an operating discipline supported by governance, structured attributes, consistent syndication, and clear ownership.
Agentic Commerce Readiness Goes Beyond Discovery
Product data is the foundation, but readiness does not end there.
Agent-driven transactions will place new demands on commerce platforms, order management systems, inventory services, and fulfillment operations. If an agent cannot confirm stock, validate account pricing, reserve inventory, or provide an accurate delivery date, it will route the transaction elsewhere.
That loss may happen quietly. No abandoned-cart alert. No support ticket. No opportunity for a sales team to intervene.
Measurement must evolve as well. A buyer may discover a product in an answer engine and complete the purchase through a distributor, marketplace, procurement platform, or sales representative. Traditional analytics may capture the transaction without recognizing where the decision began.
Commerce teams need to treat AI-mediated discovery as an influence channel. That means tracking answer-engine referrals, assisted conversions, agent interactions, and the product attributes that improve visibility.
How Perficient Helps Commerce Organizations Prepare
Our team connects commerce strategy, data, AI, customer experience, and delivery. We help organizations tie pilots to the data, platforms, and operating processes needed to measure results.
That work includes strengthening product data foundations, modernizing commerce and order management architectures, improving product findability, deploying practical AI use cases, and building measurement models for emerging customer journeys.
Our AI-first approach applies AI where it removes friction, improves decisions, and produces measurable results. That is what it means to be Different for real: AI-first solutions backed by disciplined delivery and measurable outcomes.
Preparing for What Comes Next
Commerce leaders do not need to predict exactly when agentic commerce will reach full autonomy. They need to prepare for a buying environment in which agents play a larger role in discovery, evaluation, and transactions.
Strengthen product data first. Then test real-time fulfillment capabilities and measure AI-driven discovery. Build a readiness roadmap using short execution cycles.
Agentic commerce is still maturing. The companies building the right foundations now will be ready when buyer behavior catches up.
Forrester clients can access The State of Agentic Commerce, Q2 2026 directly through Forrester.
