Marketing agency questions answered

Navigating the New Frontier: An Agency’s Guide to AI Search and Conversational AI

The digital marketing landscape is once again being redrawn, this time by the transformative power of Artificial Intelligence.1 AI-powered search, exemplified by features like Google’s AI Overviews and the broader rise of conversational AI, is no longer a futuristic concept but a present-day reality.2 For digital marketing agencies, this evolution brings a cascade of urgent questions about how to maintain client visibility, demonstrate value, and adapt strategies in a world where search itself is changing fundamentally. This article delves into the top three concerns for agencies, offering clarity and actionable insights.

1. Adapting SEO and Content: Thriving in the Age of AI Answers

The Core Question: How do we adapt our SEO and content strategies to ensure client visibility and traffic in an era of AI-generated answers and “zero-click” searches?

The advent of AI search features that provide direct answers within search results is indeed challenging traditional SEO models, which have long prioritised driving clicks to websites.3 The concern that clients’ content might be used to inform AI summaries without a direct visit, or that traditional keyword rankings may lose their potency, is valid. So, how can agencies navigate this?

  • Embracing “Answer Engine Optimisation” (AEO): The focus must shift from solely optimising for search engines to optimising for answer engines.4 This means creating content that directly, comprehensively, and authoritatively answers the questions your clients’ target audiences are asking.
    • Being the Source: The goal is for your clients’ websites to become trusted sources that AI models cite or use to formulate their answers. This requires exceptionally high-quality, well-researched, and clearly presented information.
    • Structured Data is Non-Negotiable: Implementing robust schema markup is paramount.5 Detailed structured data (for products, articles, FAQs, events, etc.) provides AI with explicit, machine-readable information, making it easier to understand and feature your clients’ content accurately in AI summaries or rich results.6
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    • E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness): These principles are more critical than ever. Agencies must guide clients in demonstrating their first-hand experience, showcasing expertise, building authority in their niche, and ensuring their online presence radiates trustworthiness. This includes clear authorship, robust ‘About Us’ pages, customer testimonials, and secure website practices.

 

  • The Evolution of Keyword Strategy:

    • Beyond Keywords to Concepts and Entities: While keywords remain relevant, the emphasis is moving towards optimising for broader topics, concepts, and entities (people, places, things, and their relationships). AI’s understanding of context and semantics means it can connect queries to relevant content even without exact keyword matches.7
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    • Long-Tail Keywords and Conversational Queries: Long-tail keywords are not dead; they are evolving.8 AI excels at understanding natural, conversational language.9 Optimise content to answer the highly specific, often question-based queries that users type or speak. Think “how,” “why,” “what is the best way to,” etc. This often means creating more in-depth FAQ sections, how-to guides, and content that addresses the full user journey.

 

  • Content for Citation:

    • Clarity and Conciseness: Ensure content is well-organised with clear headings, bullet points, and concise language that AI can easily parse and extract for summaries.
    • Factual Accuracy and Freshness: Maintain up-to-date and accurate information, especially for rapidly changing data like prices, stock levels, or event details.10
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Agencies must educate clients that visibility within an AI answer, even if it doesn’t result in a direct click, is a new form of valuable exposure and brand reinforcement.

2. Evolving Agency Capabilities: New Skills, Tools, Services, and Value Demonstration

The Core Question: What new skills, tools, and service offerings do we need to develop to effectively serve clients in an AI-dominated search landscape, and how do we demonstrate ongoing value?

The shift to AI search necessitates an evolution in agency capabilities. Sticking to old methods will quickly lead to obsolescence.11

  • Developing New Analytical Skills:

    • Beyond Click Metrics: Traditional metrics like click-through rates and organic sessions, while still important, will not tell the whole story. Agencies need to develop skills in analysing brand mentions and sentiment within AI-generated results, tracking impressions or visibility in AI answers, and understanding how AI features influence the overall customer journey, potentially through assisted conversions.
    • Understanding AI Behaviour: This involves monitoring how AI models are sourcing information, which competitors are being featured, and why.

 

  • Investing in AI-Specific Tools:

    • Advanced Schema Tools: Tools for generating, validating, and managing complex schema markup.12
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    • AI Monitoring Platforms: Emerging tools that track how clients and their competitors appear in AI-generated search results.13
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    • Content Optimisation Tools with AI Integration: Platforms that use AI to help refine content for clarity, relevance, and E-E-A-T signals, or to identify content gaps based on conversational queries.14
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    • Enhanced Rank Trackers: Tools that not only track traditional rankings but also visibility within various AI-driven SERP features.

 

  • Evolving Service Offerings:

    • AI Search Readiness Audits: Assessing a client’s current state of optimisation for AI search and providing a roadmap.
    • Advanced Structured Data Implementation & Management: Offering specialised services to create and maintain comprehensive schema.
    • Conversational Content Strategy: Developing content specifically designed to answer questions and engage in a more conversational manner.
    • E-E-A-T Consulting: Guiding clients on building and showcasing their experience, expertise, authority, and trust.
    • Product Feed Optimisation for AI Shopping: Ensuring product data is perfectly structured and detailed for AI-driven e-commerce experiences.15
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  • Demonstrating ROI and Value:

    • Focus on Influence and Authority: Highlight how the agency’s efforts are positioning the client as an authoritative source for AI, leading to brand mentions and shaping the narrative within AI answers.
    • Qualitative Metrics: Supplement quantitative data with qualitative insights, such as the quality of leads generated or the sentiment of brand mentions in AI outputs.16
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    • Educate Clients on New KPIs: Work with clients to establish and understand new Key Performance Indicators relevant to the AI search era. This includes visibility shares within AI results, attributed influence on conversions, and growth in brand authority signals.
    • Long-Term Strategic Partnership: Emphasise the agency’s role in navigating ongoing changes and future-proofing the client’s digital presence.

3. The Shifting Sands of Paid Advertising: Budgets, Strategies, and the Marketing Mix

The Core Question: How will AI search impact paid advertising strategies, client budgets, and the overall marketing mix we recommend?

AI’s influence extends significantly into the realm of paid search, prompting agencies to re-evaluate traditional approaches.17

  • Potential for Cannibalisation and Coexistence:

    • Visibility Shifts: There’s a real possibility that prominent AI answers could reduce clicks on traditional paid search ads if users find what they need directly in the AI summary.
    • New Ad Placements: However, search engines like Google are actively testing and rolling out ad formats within or alongside AI Overviews.18 This could present new opportunities for visibility. Agencies need to stay abreast of these evolving ad placements and learn how to leverage them effectively.
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  • Emerging Ad Formats and AI-Driven Campaigns:

    • Integrated Ads: Expect to see more sponsored content or product listings seamlessly integrated into AI-generated results.19
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    • Conversational Advertising: Opportunities for ads to appear within conversational AI interfaces could emerge.
    • AI-Powered Campaign Management: Tools like Google’s Performance Max are already central, using AI to automate ad creation, targeting, and bidding across multiple channels.20 Agencies must master these platforms, focusing on providing strong strategic inputs (e.g., audience signals, creative assets, conversion goals) rather than granular manual adjustments.
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  • Advising on Budget Allocation:

    • Holistic Investment: The lines between ‘organic’ and ‘paid’ preparation are blurring.21 Investment in high-quality content and comprehensive structured data, traditionally seen as ‘SEO,’ is now also foundational for appearing effectively in AI-generated answers and potentially influencing how products are featured in AI-driven ad formats.22
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    • Strategic Testing: Advise clients to allocate a portion of their budget to experimenting with new AI-related ad placements and campaign types as they become available.
    • Data-Driven Decisions: Continuously monitor the performance of traditional paid campaigns alongside new AI-driven formats. Be prepared to shift budgets flexibly based on ROI and achieving specific client objectives.
    • Content as a Core Pillar: Emphasise that robust, informative content benefits both organic AI visibility and provides better assets for AI-powered ad campaigns.23
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  • The Agency’s Role in an AI-Driven Paid Landscape:

    • Strategic Oversight: While AI automates many tactical aspects, human strategic oversight is crucial.24 This includes defining target audiences, setting clear objectives, ensuring brand safety, and interpreting complex performance data.
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    • Creative Excellence: Providing high-quality ad creatives (text, images, video) that resonate with target audiences remains a key human-driven element, even in automated campaigns.
    • Data Integration and Analysis: Ensuring that first-party data is effectively utilised by AI ad platforms and performing sophisticated analysis to uncover insights and opportunities.

Summary: Adapt Proactively, or Face Obsolescence

The integration of AI into search is not merely an incremental update; it is a paradigm shift. For digital marketing agencies, the questions around adapting SEO, evolving service offerings, and recalibrating paid advertising strategies are not just academic – they are critical to survival and continued relevance.

Businesses, in turn, must recognise that the ways customers discover and interact with them online are fundamentally changing. Those who fail to embrace modern search optimisation techniques, who neglect to structure their data for AI consumption, or who ignore the nuances of conversational queries, risk becoming invisible.25 Their traffic will dwindle, their sales will suffer, and their very business could fail in this new AI-driven landscape.

Proactive adaptation, continuous learning, and a willingness to innovate are no longer optional. They are the essential ingredients for agencies and their clients to not just weather this transformation, but to emerge stronger and more successful in the era of AI search.

References for Further Reading:

  • Google Search Central Blog (formerly Google Webmaster Central Blog): For official announcements, guidance, and best practices directly from Google regarding search and AI.
  • The Keyword (Google’s official blog): For broader announcements about Google products, including AI developments.26
    • blog.google
  • Schema.org: The official website for understanding and implementing structured data.