2026 may be the first true year of AI commerce. If you run a merchant business and have not yet examined what is happening, now is the time.
Here are 11 trends worth knowing. Not the fluffy ones—the trends that are actually changing how merchants sell products and services.
11 AI Commerce Trends Every Merchant Should Know
1. Customers Are Asking AI Before They Search
More buyers are starting their journeys by asking ChatGPT, Claude, Perplexity, or Gemini rather than going straight to traditional Google Search. If your business is not included in those AI-generated answers, it may be invisible before a conventional search even begins.
2. AI Agents Are Becoming the New Storefront
Commerce has moved through physical stores, websites, and apps as customer behaviour has changed. AI agents are becoming the newest layer—and may be the first place customers, or their AI shopping assistants, encounter a merchant.
3. Product Discovery Is Getting Delegated
People used to search and browse for themselves. Now they can delegate the work: “Find me a good espresso machine under $500 with milk frothing.” AI assistants compare the available options and recommend a shortlist. If your product information is not structured clearly, the product may never enter that comparison.
4. Real Reviews Matter More Than Ever
AI agents may use reviews as evidence when evaluating merchants and products. Review volume, recency, quality, and recurring themes can all matter. Genuine customer reviews are more useful than large volumes of artificial or manipulated feedback that do not reflect real customer experiences.
5. Brand Storytelling Is Losing Ground to Facts
A beautiful hero image or well-produced video may persuade a human shopper, but it does not give an AI agent the practical information needed to compare an offer. Clear pricing, specifications, availability, delivery details, and return policies are more useful in an AI-assisted decision. Brand still matters to people, but once an AI agent enters the journey, verifiable facts become more important.
6. Pay-Per-Outcome Advertising Is Rising
CPM, or cost per thousand impressions, and CPC, or cost per click, are increasingly being challenged by outcome-based models such as CPA, cost per action, and CPS, cost per sale. Merchants are questioning the value of paying for impressions and clicks that do not convert. Platforms that connect spending to measurable actions or transactions are therefore becoming more relevant.
7. Agent-to-Agent Commerce Is Starting
In agent-to-agent commerce, a customer’s AI agent can communicate with a merchant’s AI agent to compare options, exchange information, and help prepare a transaction for human approval. It may sound futuristic, but early forms of this interaction are already emerging in categories such as travel and food delivery.
8. Attribution Is Getting Cleaner
Marketers have struggled for years to determine which interaction caused a transaction. AI-driven commerce can create a more structured path in which recommendations and conversions occur inside traceable interactions. Where the necessary tracking is available, this can make attribution more reliable and change how merchants allocate their budgets.
9. AI Readiness Is Becoming a Real Metric
Merchants have traditionally tracked SEO rankings, impressions, and clicks. They are now beginning to measure AI visibility as well: whether their brand or products appear in AI answers, how often they are mentioned, and whether they are described accurately. AI readiness is becoming another useful layer in marketing and commerce reporting.
10. The Infrastructure Layer Is Consolidating
Behind the scenes, networks are forming to connect AI agents with merchant offers and support workflows spanning discovery, payment, attribution, and settlement. This is the infrastructure layer of AI commerce. Merchants do not necessarily need to build all of it themselves; they can connect to infrastructure such as AON (Agent Offer Network), which helps make merchant offers available inside AI-assisted journeys.
11. Small Merchants Have a Real Window Right Now
Many large brands are slow to adapt because they still treat traditional SEO, social media, and Google Ads as the complete acquisition playbook. Smaller merchants may have an opportunity to move faster, improve their AI visibility, and test new acquisition models before larger organisations complete the same transition. That opportunity will not remain equally open forever.
What This Means for You
You do not need to react to all 11 trends at once. Choose the changes that fit your business and start with a small number of focused actions.
For many merchants, the most practical starting points are:
- Clean up product data so AI systems can understand and compare the offer.
- Build a steady flow of authentic reviews across relevant platforms.
- Test pay-per-outcome AI advertising where the desired action can be measured reliably.
None of this necessarily requires a huge team or a massive budget. It requires paying attention to where customer behaviour is moving and making consistent improvements over time.
Final Thoughts
AI commerce is not only a future possibility. It is already influencing how customers find, evaluate, and buy from merchants, although adoption is moving at different speeds across industries.
The merchants best positioned for 2026, 2027, and beyond will be those that notice the shift early and make small, consistent improvements to how their products are understood, trusted, and purchased.
FAQ
If AI assistants become the storefront, do I lose control over how my brand is presented?
Not entirely, but the source of control changes. You cannot control the exact wording an AI assistant uses, but you can improve the evidence it has by publishing clear, consistent information about your products, pricing, policies, and customer fit. Brand storytelling still matters to people; factual clarity reduces the need for an assistant to guess what your business offers.
My product pages are well designed. Why might an AI assistant still skip my products?
Visual polish does not tell an AI assistant whether a product satisfies a specific request. Make specifications, pricing, availability, compatibility, delivery details, and return policies clear in readable page content. If those facts are missing or inconsistent, the product may be difficult to compare even when the page is persuasive to human shoppers.
Should I clean up my product data or invest in getting more reviews first?
Fix the product data first when an AI assistant cannot accurately identify, compare, or qualify your products. Prioritise authentic reviews once the product information is complete but the offer still lacks independent proof and buyer confidence. Product data makes the offer understandable; recent, credible reviews help customers and AI systems evaluate whether the experience supports the claims.
I am a small merchant. Do I really have an advantage over bigger brands in AI commerce?
Potentially, but speed—not size—is the advantage. Smaller merchants can often update product data, policies, offers, and experiments faster than large organisations with slower approval cycles. Bigger brands still benefit from recognition, distribution, and a larger public footprint, so the opportunity comes from moving faster and being easier to understand, not from being small by itself.
How do I tell whether my AI commerce problem is discovery, trust, or conversion?
Look at where the customer journey is breaking down. If your products are absent from relevant AI prompts, investigate discoverability and product information; if they appear but competitors are preferred, examine reviews, value, and other trust signals; if AI-influenced visitors arrive but do not act, focus on pricing, policies, and conversion friction. Treat these as diagnostic signals rather than proof of a single cause.
Should I move my budget from clicks to pay-per-outcome advertising now?
No—not as a wholesale swap. Keep the channels that already produce profitable demand, then test pay-per-outcome advertising where the desired action and attribution can be measured reliably. Compare cost per sale, booking, or qualified lead against the incremental performance of your existing campaigns, rather than assuming a newer pricing model will automatically perform better.
