Hardly any other term is currently used as frequently and rarely explained as clearly as Agentic Commerce.
Time for a classification: What is already possible today? What is still the future? And where should retailers and manufacturers start now? We look at current examples from the market, share our assessment from practice and answer the questions that companies are currently most concerned with.
AI assisted commerce
AI supports people in their purchasing decisions. It makes recommendations, answers questions and compares products - but people decide and buy themselves. Conversational commerce, product search via ChatGPT or Perplexity, AI-based style advice: all AI assisted commerce.
Key feature: the human remains in the loop. The AI assists, it does not act.
Agentic commerce
Here, the user gives their authority to act to the AI. The AI searches, compares, decides and buys - autonomously, within predefined framework conditions. In the best-case scenario, the human only receives the confirmation message: "Done."
This is the decisive difference to classic process automation: no rigid trigger, no fixed rule. Instead, complex considerations, e.g. about price, quality, delivery time and availability - across systems, in real time.
Key feature: AI has genuine decision-making autonomy. The human delegates, not just the execution, but the purchase decision itself.
Agents for Commerce
This is the inward-looking perspective: AI agents that automate processes on the sales side - in ERP, in PIM, in the store backend, in customer service. No end customer sees this directly, but it changes how commerce organizations work internally.
The McKinsey report provides a clear figure: 84% of European consumers already use AI tools in their everyday lives. 63% of them also use these tools in their shopping journey - for research, comparison and inspiration.
At the same time, only 30% would trust an AI to complete an order automatically - even if the budget was limited in advance.
That's the real tension: the technology is partly there. The acceptance is not yet there.
What works today
What does not yet work (in Europe)
B2C: Agentic commerce begins where trust is less critical
In the consumer sector, technology is ahead of trust. The desire to make purchasing decisions oneself is deeply rooted.
This does not mean that B2C agentic commerce will not come. But it will take hold in low-involvement purchases first: Repeat orders, consumer goods, standard products without emotional attachment.
B2B: Better conditions for autonomous purchasing processes
The situation is fundamentally different in the B2B context:
This makes B2B purchasing perfect for agents because the organizational trust in automation has already been established.
A concrete scenario: an AI reads the CRM, identifies 1,000 customer contacts and orders Christmas cards. Not a huge technical effort, but a real process gain.
Assessment: Agentic commerce will arrive earlier and more widely in B2B than in B2C. The technology is similar - but acceptance in the business context is already much more advanced.
The good news first: it's not a revolution. Nobody has to start from scratch. But there are clear shifts that you should prepare for.
The customer journey is changing - but not dramatically
Awareness, discovery, consideration: these phases are increasingly being shaped by AI tools. Customers no longer necessarily come to your website via Google - they may come via a ChatGPT recommendation, a Perplexity response or a Google snippet that pulls directly from the product feed.
This changes how you have to think about visibility. And it changes which data points suddenly become important.
Brand takes on a new dimension
How does AI perceive my brand? What signals does it draw from the web? Which products appear in its recommendations - and which don't?
In the webinar experiment, ChatGPT favored products from About You - without any specifications. The reason: About You has the "most comprehensive, structured product catalog" known to the model. Branding in the AI age starts with data quality.
Your own store remains relevant
A frequently asked question: Do we still need the store if AI tools take over discovery? The answer: Yes - but for different reasons than before. The store will become less of an entry point and more of a contact point for customers who have already made a decision. And still important for brand presentation, after-sales and customer loyalty.
SEO remains relevant - but the mechanics are changing.
How AI tools obtain data today
Not all LLMs crawl the web in real time. OpenAI/ChatGPT, for example, in many cases simply queries Google - and aggregates the first organic hits. Anyone who is not visible on Google is also not visible to ChatGPT.
Other providers such as Anthropic or Perplexity actively crawl the web. But even there, being crawled does not automatically mean being taken into account. Between the collection of data and the actual inclusion in a result, there are validation steps, caching and model decisions that are difficult to comprehend from the outside.
Practical tip: Write content in such a way that it answers specific user questions. Users formulate their research in AI tools as a question, for example: "Which hiking boots are waterproof and under 150 euros?" It is precisely this question-answer mechanism that is made more relevant by LLMs.
Agents for commerce - i.e. AI agents for internal processes on the retailer side - are a topic in their own right and deserve a separate article. So here are just the key points:
Start immediately
Structure product data and make it machine-readable - for feeds, for AI, for search engines
Convert content to question-answer logic: How would a customer ask the question to which this text is the answer?
Ensure SEO visibility - it remains the basis for AI visibility
Identify and pilot internal use cases: Returns forecasting, copywriting, customer service - start small, learn, scale
Prepare for the medium term
Build or upgrade API infrastructure: No access for external agents without API
Test conversational commerce interface
Optimize and play out product feeds for Google and OpenAI - also think about new protocols such as UCP or ACP
Actively think about the brand in AI channels: What should the AI know about my brand - and where does it get it from?
Wait and see
Organizational
Is Agentic Commerce even legally permissible in the EU context?
As things stand today: No - at least not in the form of autonomous checkout. The EU AI Act, the GDPR and PSD2 each have their own requirements for autonomous purchasing decisions. This is one of the main reasons why Perplexity's Buy-with-Pro feature is not yet available in Europe. It remains to be seen how the legal situation will develop - but no rapid changes are expected.
How does the AI decide which store to buy from?
In a test, products from one provider were preferred because the product catalog was particularly extensive, clearly structured and easy to evaluate. This is exactly what makes the difference: if product data is complete, comprehensible and up to date, the chances of being selected increase.
For retailers, this means that data quality becomes a question of visibility.
Will the wider retail community be prepared to hand over the checkout to Agentic Commerce?
It will probably be a commercial decision: How much revenue will I miss out on if I don't participate? The parallel with Amazon is not inappropriate - those who sell there have largely given up direct customer contact and are primarily logistics and price providers. Similar dynamics could arise.
What is GEO (Generative Engine Optimization) - and do I need to tackle it now?
GEO is the term for optimizing content specifically for AI models. The basic principles are not new: clear structure, question-answer logic, good readability for machines. This has already been hinted at with voice search. The practical start: start by formulating your most important content in the way your customers would ask questions.
Agentic commerce does not start with the autonomous checkout. It starts with clean data, connectable systems and clearly prioritized use cases. Diconium supports companies in laying precisely these foundations - and in using agent-based AI where it delivers real added value in commerce.