AI-powered search is rapidly reshaping how B2B buyers discover, evaluate, and engage with providers during the purchasing process and postsale experience. Today’s buyers ask questions that require more than simple keyword matches. They expect modern search environments — from generative AI-based answer engines to AI agents — to understand their intent and deliver responses that are contextually relevant, credible, and actionable to help guide them through complex decisions.

Recent Forrester data underscores the urgency: 95% of B2B buyers plan to use generative AI in at least one area of a future purchase, and over half say it led them to consider more or different vendors while saving them time in their purchase process. The implications for B2B marketing are profound: Success depends on creating and activating content that’s not only relevant and authoritative but also discoverable by both human and AI audiences, tailored to the deeper questions buyers are asking.

AI-powered search reaches well beyond inbound tactics to impact the entire B2B growth engine. As organic search click-through rates decline, the quality of post-click engagement is on the rise, so marketers must optimize not just for visibility but for meaningful interaction. It’s not just about being found — it’s about being understood and remembered.

How Will AI-Powered Search Experiences Impact B2B Marketing?

As modern search experiences result in more informed buyers — and more empowered marketers — B2B organizations must anticipate and optimize for AI-powered answer engines and zero-click search behavior in five key areas:

  • Establish content authority and trust. It’s not enough to rank for keywords; your content needs to answer the questions buyers are asking with credible, context-rich, intent-driven answers and show up in the sourcing and citations included for transparency. Leverage intent mapping, topic clusters, and structured data to help shape and reinforce AI model reasoning. Proactive community engagement and customer advocacy are critical: Third-party content helps shape AI model perception and summarization in zero-click search experiences, where decision-making space is condensed and answers are delivered directly rather than being ranked in a list of search results based on keyword matches.
  • Optimize B2B websites for visitors, both human and AI. Your website content is being consumed by AI systems as well as human users. Not only must websites be attractive to and readable by large language models (LLMs) and AI agents, but the onsite experience for humans who do click through — at any stage of the customer lifecycle — must account for the heightened expectations of search users for contextual, conversational experiences. Deliver a post-click experience that’s engaging, memorable, and differentiated from the information surfaced in the preceding search experience to encourage deeper buyer exploration and self-service. Balance content gating approaches with the need to provide open access to decision-driving information that influences AI model reasoning and persuades humans to stay on the page.
  • Enable frontline marketing. From knowledge management to automated search marketing workflows, generative AI is changing the work of frontline marketers. AI-powered enterprise search enables marketers to converse with enterprise content and uncover insights across disparate data using answer engines embedded into internal technologies and go-to-market workflows. Agentic search marketing workflows offer an automated, collaborative, and self-improving approach to search optimization and monitoring. Reskill frontline marketers to prioritize interaction quality over traditional metrics such as rankings and click volume, focusing instead on saturation, organic visibility, share of model, and brand equity within LLMs to assess authority and influence.
  • Align revenue processes with insights from AI-facilitated interactions. AI-powered search adds fuel to the revenue engine, as conversations across answer engines, websites, and databases offer a wealth of intent data and nuanced buying signals for revenue marketing stakeholders. Redefine conversion events to focus on buying group engagement, not individual leads. Adjust scoring models accordingly to prioritize pages visited from AI search and the higher value of that behavior. B2B companies must also prepare for the near future when commerce search assistants evolve into AI agents that negotiate, automate, and manage orders and transactions.
  • Advance content intelligence. As AI-powered search prioritizes semantic depth, relevance, and contextual alignment, content intelligence offers insights into how precisely content maps to buyer intent and influences the behavior of both human and AI users. Content must also persist in the memory of AI systems, so marketers need insights into content permanence, how that content is reinforcing signals for AI models, and how well that content influences AI — and human — reasoning over time. Keep the content intelligence feedback loop fresh by running experiments that align with how AI systems process, prioritize, and surface content.

A holistic approach across content, programs, digital experiences, and technologies is essential, as AI-powered search drives more informed buyers, empowers marketers, and integrates search agents into the buying network. Prioritize quality, uniqueness, and human connection in your content, and continuously audit your search presence to see how and where you show up.

Join us at Forrester’s B2B EMEA Summit to explore these five key areas of impact and opportunity for AI-powered search in B2B marketing and actionable next steps to not just survive but thrive in the new AI search ecosystem.