{"id":4447576,"date":"2026-05-27T09:34:00","date_gmt":"2026-05-27T07:34:00","guid":{"rendered":"https:\/\/www.deptagency.com\/?post_type=article&p=4447576"},"modified":"2026-06-08T15:36:07","modified_gmt":"2026-06-08T13:36:07","slug":"from-b2c-to-b2a-how-ai-is-rewriting-the-rules-of-the-customer-journey","status":"publish","type":"article","link":"https:\/\/www.deptagency.com\/en-uki\/insight\/from-b2c-to-b2a-how-ai-is-rewriting-the-rules-of-the-customer-journey\/","title":{"rendered":"From B2C to B2A: how AI is rewriting the rules of the customer journey"},"content":{"rendered":"
\n\t\n\t\t\n\t\t\t<\/mask><\/g><\/svg>\t\t\t\n\t\t\t\tInsights\t\t\t<\/span>\n\t\t<\/div>\n\t<\/div>\n\tFrom B2C to B2A: how AI is rewriting the rules of the customer journey<\/h1>
\n\t\t\t\n\t\n\t
\n\t\tIsabel Perry\t\t
\n\t\tVP of Emerging Tech \n\t\t\t<\/div>\n<\/div>\n\t
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\n\t\t\t\t\n\t\t\t\t\tDate\t\t\t\t<\/span>\n\t\t\t\t\n\t\t\t\t\tMay 27, 2026\t\t\t\t<\/span>\n\t\t\t<\/div>\n\t\t\t<\/div>\n\n\t\n<\/div>\n\n\n\tBy 2028, the customer journey will be split into two: the human and the AI.<\/p>\n\tConsumers won\u2019t navigate their own way to your brand\u2019s checkout window. Instead, trusted AI systems will assemble journeys on their behalf by identifying needs, narrowing options, personalising experiences, and facilitating transactions in real time.

In that world, brands won\u2019t simply compete for attention<\/em>. They\u2019ll compete for selection<\/em>.

And the distance between now and our agentic future is shorter than what most brand strategies currently account for.<\/p><\/div>\n\t\n\t<\/div>\n\n
\n\t\u201c<\/span>\n\tWe could be one Gemini update away from a fully Agentic Web. Yet the vast majority of brands have not made any significant changes to adapt to this new reality.<\/p>\t
\n\t\u201d<\/span>\n\n\t<\/blockquote>\n\n\n\tThe Agentic Web is happening now<\/h2>\n\tAlthough it might not feel like it yet, you are already:<\/p>\n\n\t
  • Losing touch with your audience.<\/strong> 69% of Google searches<\/a> end without a click to a website. People find answers without ever visiting your site, leading to a massive drop in traffic.<\/li>
  • Losing control of your brand.<\/strong> 47% of consumers<\/a> say AI shapes their trust in a brand. AI is becoming the new distribution layer and the first point of contact for shoppers.<\/li>
  • Losing out to competitors.<\/strong> 48% of AI prompts<\/a> represent new consumer behaviours. If you aren’t planning for these new needs, your competitors will, and you’ll miss out on new demand.<\/li><\/ul>\n\nThe bottom line is that we are moving from the Human Web<\/strong>, a world where humans are the primary users of the internet, to the Agentic Web<\/strong>, where AI agents work on behalf of humans.

    But it\u2019s not all bad news.\u00a0

    Brands that understand this new medium and adapt quickly will outpace their competitors, creating a new opportunity for future growth.

    At the same time, adapting to the Agentic Web requires significant changes. Retooling and (more importantly) rethinking your brand\u2019s strategy to embrace AI as a second audience.\u00a0

    We understand that this is easier said than done. Where human audiences reward emotion, creativity, and storytelling, AI rewards structured, consistent, verifiable information.\u00a0

    Many people in our industry have built a career on understanding human audiences. Asking themselves how these audiences think, search, consider, and act. Now we need to do the same for AI.<\/p>\n<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t<\/video>\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\n\t<\/div>\n\n\n\tThe new ABCs of marketing<\/h2>\n\tFor decades, marketing has built the mechanics for B2C and B2B marketing. Now, as brands work on embracing AI as a second audience, our industry has introduced Business-to-Agent (B2A) marketing strategies. This is called the new ABCs of marketing: B2A, B2B, B2C.

    B2A is the practice of optimising your brand for the AI systems that increasingly influence, mediate, or make decisions on behalf of consumers.

    This doesn\u2019t replace traditional marketing. Things that humans prioritise (like storytelling, creativity, and emotional resonance) still matter deeply. The difference is that, now, you must also account for the things AI systems prioritise. Like consistency, clarity, trustworthiness, structured information, and ease of integration.

    So what does it actually mean to market to an AI agent? It breaks down into three distinct disciplines, each with its own logic.

    <\/p>\nInfluence the agents<\/h3>\n\nWhen an LLM like ChatGPT, Gemini, or Claude is asked about your brand or your product category, it synthesizes patterns from across the web, from everything it has ever been trained on. It builds a picture of your brand based on how consistently it\u2019s communicated, how much authority it has on a topic, and what the sentiment is around it. LLMs then present that picture as a confident recommendation to someone who has already decided to trust it.\u00a0

    This changes the rules of discoverability because, where traditional SEO could tolerate some inconsistency or negative sentiment on social, LLMs punish you for it.\u00a0

    If your website says one thing, customer reviews suggest another, and third-party sources tell a different story entirely, AI systems may treat your brand as unreliable. Conversely, brands with coherent messaging and strong external validation are more likely to be surfaced confidently in recommendations.

    This means your owned channels (website, blog, product listings, etc.) need to be in order. But it also gives new weight to your earned<\/em> channels. Press mentions, Reddit discussions, creator reviews, and third-party credibility all become part of the recommendation layer AI systems use to evaluate trust.

    <\/p>\n\nEquip the agents<\/h3>\n\nIn the near future (and, in some categories, already) AI agents will generate brand experiences on behalf of your customer. A landing page, generated in real time, personalised to that specific individual, behind a login, and shaped by their specific goals and context.\u00a0

    As AI-generated interfaces become more common, brands will increasingly appear through experiences they don\u2019t fully control. Instead of fixed landing pages and static templates, AI systems will dynamically generate interfaces based on individual context, intent, and preferences. Google\u2019s latest announcements on the future of search are a testament to the speed of this change coming.\u00a0

    That creates a new operational challenge. Brand guidelines that were written for a world of fixed templates and controlled placements need to be rethought for a world where the interface itself is generated on the fly.

    The companies best positioned for this future are already investing in AI-native design systems, structured content, and clean product data.

    <\/p>\n\nConnect to the agents<\/h3>\n\nFor years, proprietary data was considered a competitive moat. But in an AI-mediated economy, brands must either:<\/p>\n\n\n\t
  • Participate and increase transaction volume, but lose the site visit, cross-sell opportunity, and CRM data capture.<\/li>
  • Or opt out, and risk invisibility as consumer behaviour shifts toward agent-driven shopping.<\/li><\/ul>\n\nIt\u2019s a dilemma that will force brands to choose between accessibility and exclusivity. And, for us, the choice is obvious.

    AI systems can only serve customers effectively if they can access reliable brand information quickly and cleanly. That means brands must rethink how much data they expose, how they structure it, and how easily AI systems can interact with it.\u00a0

    Of course, now that AI accessibility has become a priority, data is no longer the competitive moat it once was. However, in its place, a new differentiator has arisen: speed to convenience.

    The brands that are easiest for AI systems to understand, integrate with, and act on behalf of will increasingly become the brands customers encounter first. Meanwhile, companies that keep information fragmented, inaccessible, or locked behind outdated systems risk becoming invisible within AI-driven experiences.

    <\/p>\n\n\n\nAll of this is somewhat abstract until you see it in motion. So let’s make it concrete with an example of a near-future customer journey.<\/strong><\/p>\n<\/div>\n\t\n\t<\/div>\n\n\n\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t<\/video>\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\n\tWhat the 2028 customer journey looks like<\/h2>\n\tMeet Rod.

    He\u2019s in his late twenties, reasonably fit, and has decided he wants to run a half-marathon this summer. To prepare, he doesn\u2019t start with a Google search. He opens Gemini and explains his situation: his fitness level, his goal, and the park near his house where he\u2019d like to train.<\/p><\/div><\/div>\n\n\n\t\n\tGemini responds with a four-week training plan tailored to his schedule and ability. Then it asks whether he\u2019d like recommendations for running shoes.

    Rod selects DEPT\u00ae Running. A brand agent joins the conversation. Not a scripted chatbot, but an AI system that already understands the context of his goals and preferences. It asks to see a photo of the sole of his current shoes. Seconds later, it analyses his gait and recommends a specific model and fit. Rod is intrigued, but not quite ready to buy.<\/p><\/div>\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\n\t<\/div>\n\n\n\t\n\tLater that evening, Rod scrolls through Instagram and sees an ad for the same shoe, now discounted. He clicks through to a landing page generated specifically for him, complete with personalised running routes and a price tailored to his profile.

    He decides to buy.<\/p><\/div>\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\n\t<\/div>\n\n\n\tWhere brands should start now<\/p>\n\tRod never typed a brand name into a search bar. He never visited a website unprompted. He never compared spec sheets or read reviews across ten tabs. The brand reached him through systems that had already earned his trust, with an experience so relevant it barely felt like marketing at all.

    Rod\u2019s customer journey may still sound futuristic, but it is a fast-emerging reality. However, the best way of optimising your brand\u2019s marketing strategy is not to rebuild everything overnight.

    The best course of action is to make focused changes that will compound over time as AI-mediated experiences become more mainstream.

    That\u2019s where our     Growth Invention Framework<\/a> comes into play. We\u2019ve been helping some of the world\u2019s most future-ready brands embrace this philosophy by taking smart, strategic steps like these:<\/p>\n\n\t
  • Conducting AI visibility audits that expose exactly where brands show up (and where they don’t) in AI-generated responses.<\/li>
  • Helping control how their product information flows across owned sites, retail platforms, and social channels to boost AI visibility.<\/li>
  • Developing GEO governance frameworks that scale across agencies and markets.<\/li>
  • Building the AI-native design systems and data architecture that make a brand easy for AI systems to understand, integrate with, and act on.<\/li>
  • Developing Assistants & Agents for distributed channels, with the robust AI guardrails to match<\/li><\/ul>\n\nThe brands taking these steps now are the ones actively treating AI as a second audience. The ones that understand B2A as the next chapter of their marketing strategies. And the ones that will get selected, recommended, and chosen in a world that’s already taking shape.<\/p>\n<\/div>\n\t\n\t<\/div>\n\n
    \n\tOn our mind<\/span><\/h2>\n\t\n\t\t\n\t\t\t
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