B2A vs. B2B is easily explained: In B2B, you sell to businesses, in B2C to end customers. In B2A (Business to Agent), you first interact with an AI agent that searches, compares, and prepares a decision or transaction on behalf of a human. The AI agent is therefore the third target group alongside businesses and end customers. The agent doesn't replace human decision-making. However, the agent increasingly determines whether your business even makes the shortlist.
I have been working with small businesses for over 20 years on branding, websites, and visibility. During this time, I have witnessed many transformations: from business card websites to search engines, from search engines to smartphones, and from smartphones to social media.
The shift towards AI agents differs from these upheavals. For the first time, it's no longer necessarily a human who reads your website, but a machine that pre-sorts content for a human. In this article, I compare B2A, B2B, and B2C based on three questions: Who decides? Which signals count? Which content works?
B2A does not replace the B2B and B2C funnels. B2A is the upstream selection stage: The AI agent filters, the human decides.
B2A vs B2B vs B2C: the business-to-agent comparison in three axes
The most important difference between B2A, B2B, and B2C lies not in the industry, but in who receives the information and how that entity evaluates it. The following lists intentionally have the same structure so you can read the three models side by side.
Axis 1: Who decides?
- B2B: In B2B, a [someone] decides. Buying Center, that is, a group of people with different roles. According to Gartner Research A typical buying group for a complex B2B solution comprises six to ten decision-makers, each contributing their own independently researched information.
- B2C: In B2C, the decision is usually made by a single person, often together with family or friends, and frequently spontaneously.
- B2A: In B2A, the AI agent acts as a pre-filter. The AI agent researches, compares, and compiles a selection. The human remains the final decision-maker but only sees what the agent presents.
Axis 2: Which signals count?
- B2B: Trust, references, risk minimization, demonstrable competence and the question "Can I stand behind this decision internally?".
- B2C: Emotion, impulse, brand image, reviews and the feeling "This suits me".
- B2A: Structured facts, clear sources, and consistency are key. An AI agent favors providers whose services, prices, service area, languages, and availability are machine-readable and consistent. Conflicting information on your website, Google profile, and industry portal reduces the likelihood that the agent will recommend your business.
Axis 3: Which content is effective?
- B2B: Whitepapers, case studies, specialist articles, personal advice and recommendations from the network.
- B2C: Images, videos, stories, reviews and a clear brand experience.
- B2A: Structured data according to Schema.org, an llms.txt file, a service catalog, unique entities (who you are, what you offer, where, for whom), and precise FAQs. You can find technical details about performance data in my post on [topic missing]. Service catalog for AI agents.
In short: The difference between B2A, B2B, and B2C is that your content must first be understandable to a machine before a human even sees it. Specifically, when comparing B2A and B2B, this means that the buying center only sees the suppliers that the AI agent has previously identified accurately.
Customer journey comparison: Where B2A begins
The customer journey unfolds at different speeds and with different numbers of touchpoints in the three models.
- B2B Journey: Long cycles of weeks to months, many touchpoints, multiple stakeholders, formal approvals.
- B2C Journey: Short cycles of minutes to days, few touchpoints, strong role of emotion and convenience.
- B2A Journey: The research phase is condensed. Where a buyer previously had to open ten websites, an AI agent now delivers a shortlist of three to five suppliers in seconds.
This is where the strategic importance of B2A lies: The AI agent's shortlist determines whether you even enter the B2B or B2C funnel. Those not on the shortlist have no chance to impress with references or brand image. Therefore, B2A doesn't change the end of the customer journey, but rather the beginning.
Why B2A is no longer future speculation
Business-to-agent sounds like science fiction to many entrepreneurs. However, developments in 2025 show that the major platforms are already building the infrastructure for agentic commerce, i.e., agent-supported purchasing.
- OpenAI ChatGPT introduced Instant Checkout on September 29, 2025. It is based on the open-source Agentic Commerce Protocol (ACP), developed jointly with Stripe. Initially, US users could purchase from Etsy sellers; over one million Shopify merchants were expected to follow.Source: openai.com).
- Google Cloud On September 16, 2025, it introduced the Agent Payments Protocol (AP2). AP2 is an open protocol that enables AI agents to initiate and process payments across platforms. AP2 was developed with more than 60 partners, including Mastercard, PayPal, and American Express.Source: cloud.google.com).
- Adobe Adobe Analytics surveyed 5.000 US consumers at the beginning of 2025: 39% had already used generative AI for online shopping, 53% of them for product research. According to Adobe Analytics, traffic to US retailer websites driven by generative AI increased by around 1.200% between July 2024 and February 2025, but in absolute terms, it remains far below traffic from traditional search.Source: blog.adobe.com).
These figures need context: The growth is steep, the absolute volume is still small, and the data originates from the USA. For a business in South Tyrol, this means: You don't need to panic, but you should lay the groundwork now. Data quality isn't built overnight.
Supplementing instead of replacing: B2A as a preliminary selection stage
In conversations with entrepreneurs, I hear two extremes. Some say: "AI agents don't affect me; my customers know me." Others ask: "Do I no longer need a beautiful website if only machines will be reading it anyway?" Both positions are too simplistic.
- Those who optimize only for humans, It is dropped from the shortlist because the AI agent cannot clearly assess the performance.
- Those who optimize only for agents, Differentiation is lost. An agent can compare facts, but cannot sense an attitude. At the latest when a person chooses between three providers, positioning, brand psychology, and personal relationship become the deciding factors.
That's why I always consider B2A in conjunction with the brand. A clear brand strategy and positioning are prerequisites for structured data to describe anything unambiguous at all. An agent can only speak about you as clearly as you speak about yourself.
The AI agent decides who makes the shortlist. The brand decides who is chosen from the shortlist.
Practical examples from South Tyrol: before and after
The following three scenarios are typical situations I repeatedly encounter in South Tyrolean SMEs. These scenarios illustrate where B2A logic comes into play in everyday business.
Craftsmanship: “Electrician in Bolzano with PV experience”
- Before: An electrical company has been installing photovoltaic systems for years. However, their services are only documented in a PDF folder and in photos from construction sites. If someone asks an AI assistant for an electrician in Bolzano with PV experience, the company doesn't appear because the system can't find their PV expertise, either as text or as a structured service description.
- Later: Each service has its own clearly labeled page with area of application, languages (German, Italian), reference projects, and structured data according to Schema.org. The AI agent can answer the question unambiguously and identify the company.
Tourism: the agent compares hotels
- Before: A family hotel in the Vinschgau Valley only communicates prices upon request, room types only via image galleries, and the languages spoken by its staff not at all. An AI agent comparing availability, price range, and child-friendly offers for a family from Munich has hardly any usable data.
- Later: Room types, price ranges per season, amenities, languages, and arrival conditions are machine-readable and consistent in German, Italian, and English. The agent can easily categorize the hotel and include it in comparisons. How to publish agent-friendly prices without engaging in price wars is a separate topic that I will address here.
B2B service providers: the shortlist for purchasing
- Before: An engineering firm is booked almost exclusively through referrals. Its website describes "tailor-made solutions" but doesn't specify any services, certifications, or industries. A buyer uses an AI agent to generate a shortlist for fire protection planning in South Tyrol, but this firm is missing from it.
- Later: Services, certifications, project sizes, and industries are described as clearly defined entities. The firm appears on the shortlist. In the subsequent discussion with the buying center, references and trust—classic B2B strengths—again come into play.
My view: B2A is an opportunity for small businesses, with honest boundaries.
What motivates me about B2A: AI agents respond to clarity and data quality, not advertising budget. A small carpenter from the Puster Valley with clearly described services can appear in an agent response just as easily as a large provider with expensive campaigns.
For me, this represents a step towards greater fairness in the market, and strengthening smaller businesses is something I'm passionate about. When tradespeople receive relevant inquiries, clients find the right provider more quickly, and there's less wasted effort, everyone wins.
But I don't want to sugarcoat anything. B2A has limitations you should be aware of:
- AI agents can make mistakes. Language models confuse providers, use outdated information, or invent details. Consistent data reduces the risk, but does not eliminate it.
- Platforms control visibility. Which providers an agent prefers also depends on the rules and business interests of the platform operators. You cannot influence these rules.
- Data sovereignty is therefore mandatory. If your performance data is only stored on external portals, others determine how your business is described. Your own website as the single source of truth is your safeguard.
First steps in the correct order
The order is crucial. Those who start with the technical aspects will ultimately bring structure to the confusion. I recommend these five steps:
- Clarify positioning: Who do you work for, what do you stand for, what exactly do you offer? Without this answer, any data structure remains arbitrary.
- Structuring services and prices: Each service is given a name, description, target group, catchment area, languages and, where appropriate, a price range or "starting from" price.
- Building a Single Source of Truth: All information is maintained in one place and then distributed from there to the website, Google profile, and other channels. This prevents any inconsistencies.
- Deliver in machine-readable format: Schema.org markup, llms.txt, clear FAQs, and clean multilingual support ensure your content is reliably readable for AI agents. These measures form the core of Generative Engine Optimization.
- Check AI visibility: Regularly ask ChatGPT, Gemini, and Perplexity the questions your customers would ask, and check if and how your business is mentioned.
For steps three and four, we at Berger+Team developed our own foundation with btlabs Core: a central content repository that feeds the website and future channels, trilingual, with llms.txt, brand.json, and structured data right out of the box. I describe how this AI-ready website foundation is built in detail in a separate article. It's important to note that AI booking agents are a technically pre-configured upgrade in btlabs Core, not a standard feature.
Questions? Answers!
What is B2A?
B2A (Business to Agent) refers to the alignment of a company's offerings, data, and communication with AI agents that research, compare, and prepare transactions on behalf of humans. Alongside B2B and B2C, the AI agent thus represents a third target group. For you, this means: your services must not only be compelling but also unambiguously machine-readable.
B2A vs B2B: What is the difference?
In B2B, you convince a buying center of several people with trust, references, and advice. In B2A, you first convince an AI agent with structured, consistent facts to even make the buying center's shortlist. B2A is therefore the preliminary stage, B2B the decision-making stage.
B2A vs B2C: What is the difference?
In B2C, emotions, images, and reviews have a direct impact on an individual. In B2A, an agent reads the content first, and while they don't perceive emotions, they compare facts such as price, availability, language, and location. The emotional impact of a brand remains important, but it only unfolds when the individual considers the agent's selection.
Is B2A the same as B2B2C?
No. B2B2C describes a sales model in which one company sells to end customers via another company, for example, a manufacturer through a retailer. B2A does not describe a sales channel, but rather a new target audience: the AI agent as an intermediary that pre-sorts in both B2B and B2C markets.
Does my small business already need a B2A strategy?
You don't need a dedicated B2A department, but you should lay the groundwork now : clear positioning, structured services, and consistent data. Small businesses especially benefit because AI agents respond to data quality, not advertising budgets. Those who are well-positioned early on gain a head start that's difficult to catch up with later.
Does B2A replace search engine optimization?
No, B2A is built on SEO. Many AI assistants use search indexes as a source, and the fundamentals of good SEO, such as fast loading times, clear structure, and unambiguous content, also help AI agents. Generative Engine Optimization complements SEO with machine-readable facts, entities, and citable answers.
What data does an AI agent need from my company?
An AI agent primarily needs clear, consistent facts : company name, location, service area, services with descriptions, price range, languages spoken, opening hours, contact methods, and references. This information should be provided as structured data according to Schema.org and be identical across all channels. The clearer the data, the lower the risk of the agent misrepresenting you.
Can AI agents already book and pay today?
Yes, in certain ecosystems: OpenAI has enabled purchases directly within ChatGPT since September 2025 with Instant Checkout , initially for US users of Etsy sellers, and Google has introduced AP2, a payment protocol for agents. However, for most SMEs in South Tyrol, booking agents are still a development and not yet an everyday reality. You can read how to prepare your website step by step in the article on transaction-enabled websites for AI agents.
How do I check if AI agents can find my business?
Ask ChatGPT, Gemini, and Perplexity the questions your customers would ask , such as "Who offers X in Bolzano?", and document whether and how your business is mentioned. Verify the accuracy of the information provided and repeat the test every few weeks. Additionally, server logs will show whether AI crawlers like GPTBot or PerplexityBot are even visiting your website.
What are the costs associated with getting started in B2A?
The costs depend on how clear your positioning already is and the condition of your website and data. Often, clarifying the services and ensuring clean, structured data can achieve a great deal before larger investments are necessary. We can best discuss a specific framework in a no-obligation introductory meeting as part of our consulting services . Please contact me at info@berger.team to arrange this.
Does B2A make my brand obsolete?
On the contrary. The agent puts you on the shortlist, but the brand decides who gets chosen . Without clear positioning, your data only describes interchangeable things, and ultimately, people have no reason to choose you.
Sources
- Gartner: The B2B Buying Journey — gartner.com
- OpenAI: Buy it in ChatGPT: Instant Checkout and the Agentic Commerce Protocol — openai.com (2025)
- Google Cloud Blog: Announcing Agent Payments Protocol (AP2) — cloud.google.com (2025)
- Adobe Digital Insights / Adobe Analytics: Traffic to US retail websites from generative AI sources jumps 1,200 percent — blog.adobe.com (2025)
