This page explains what changed since 2024, what businesses should prioritise, and includes a AI Search Optimization Readiness Checklist plus an interactive scoring tool and downloadable PDF report.

1. What Changed in Search & Marketing After 2024?

1.1 AI Overviews and the rise of zero-click answers

In May 2024, Google rolled out AI Overviews (then called SGE) to users in the U.S., with a plan to reach over a billion people by the end of 2024. That rollout has since expanded, and by 2025 AI Overviews are reaching well over a billion users every month.

As AI answers sit above the classic blue links, the share of searches ending with no clicks has jumped. A Similarweb analysis showed that zero-click news-related searches climbed from around 56% to 69%, while organic visits to news sites dropped from over 2.3 billion in mid-2024 to under 1.7 billion by May 2025.

Implication: A growing share of your audience gets answers from AI layers without ever visiting your site – unless your content becomes the source those AI answers rely on.

1.2 AI becomes the default marketing co-pilot

Generative AI has moved from experiment to everyday workflow. In McKinsey’s 2024 State of AI survey, 65% of organisations reported regularly using generative AI, nearly double just ten months earlier.

In marketing specifically, multiple industry studies show that the vast majority of teams now use AI somewhere in their stack, from content ideation and copywriting to media planning and analytics.

Implication: The question is no longer whether to use AI in marketing, but how to become the trusted source that AI systems reference.

1.3 Generative AI reshapes traffic, ads & measurement

As more searches route through AI experiences, organic traffic becomes less predictable. At the same time, budgets are shifting: US advertisers are projected to spend nearly $26 billion on AI-powered search ads by 2029, up from just over $1 billion in 2025, representing about 13.6% of total search ad spend.

Meanwhile, a SAS & Coleman Parkes study reports that 93% of CMOs using GenAI see a clear return on investment from the technology.

Implication: AI is moving real budget and revenue. Only brands that connect AI initiatives to measurable outcomes (pipeline, revenue, cost savings) will sustain investment.

2. From SEO to AEO and GEO (AI SEO)

To win in generative search, it helps to clarify the three layers:

2.1 SEO – Search Engine Optimization

• Optimising content, technical setup, and authority so search engines can crawl, index and rank your pages.
• Focus areas: keywords, topical depth, backlinks, Core Web Vitals, structured data, UX.
• Primary outcome: visibility in classic blue links and rich results.

2.2 AEO – Answer Engine Optimization

• Optimising for direct answers, not just rankings.
• Focus on featured snippets, FAQs, how-to content and entity clarity so systems like Google, Bing, and voice assistants can answer questions with your content.
• Heavy use of structured content and schema markup (FAQ, HowTo, Article, Organization, Product, etc.).

2.3 GEO / Generative Engine Optimization (AI SEO)

• GEO focuses on making your brand and content easier for generative AI models (ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.) to discover, understand, and cite.
• Builds on SEO + AEO, but adds stronger emphasis on:
  • Entity-level optimisation for your brand, products, people and concepts.
  • Citations, statistics, expert quotes and clear attribution that AI can easily surface.
  • Multi-platform visibility: not just Google SERPs, but AI answers and chat experiences.

3. What Should Businesses Look For in the Age of AI Search?

3.1 Be discoverable and cite-worthy in AI answers

• Allow reputable AI crawlers (e.g., GPTBot, Google-Extended, ClaudeBot) where it aligns with your policy.
• Write in clear, structured language with headings, FAQs and concise summaries.
• Include data, references and expert commentary so your content stands out as a trusted source.

3.2 Build entity-based authority, not just page-level SEO

• Clarify who you are with strong About pages, Organization schema, and consistent NAP data.
• Explain what you do with focused product / service pages, use cases and case studies.
• Demonstrate why you’re credible using reviews, certifications, awards and original research.

3.3 Measure AI visibility, not only website sessions

• Track how often your brand or domain is mentioned inside AI answers (where tools allow).
• Monitor share of voice for key topics across AI search / assistants.
• Connect AI-influenced sessions to leads, opportunities and revenue with proper tagging and attribution.

3.4 Connect AI content to real business outcomes

• Define GEO goals in business terms (pipeline, revenue, LTV, CAC, cost savings, etc.).
• Set up Roadmap so AI-assisted content remains accurate, compliant and on-brand.
• Review AI outputs thoroughly, especially in regulated industries.

4. AI Search Optimization Readiness Checklist

Inspired by the GEO Readiness Checklist from Geoptie (paraphrased and adapted for this site).

4.1 Strategic foundation

• You have a documented GEO / AI search strategy aligned with your wider digital roadmap.
• There is a dedicated GEO budget and cross-functional task force (content, SEO, product, data, legal).
• Leadership understands the difference between SEO, AEO and GEO and actively sponsors the program.

4.2 Content and authority

• Content is conversational, intent-led, and organised into topic clusters with strong pillar pages.
• High-value assets include original research, proprietary data or unique frameworks.
• Author bios, case studies and stories highlight real-world experience and expertise.

4.3 Technical and data readiness

• Schema markup (FAQ, HowTo, Article, Organization, Product, LocalBusiness, etc.) is implemented and validated.
• Robots.txt intentionally manages AI crawlers according to your policy.
• Site is technically clean: fast on mobile, secure (HTTPS), with solid internal linking and XML sitemaps.

4.4 E-E-A-T: Experience, Expertise, Authority, Trust

• Content shows first-hand experience, process transparency and real outcomes.
• Team profiles highlight relevant credentials, certifications and speaking or publishing history.
• Reviews, testimonials, policies and Roadmap processes are easy to find and up-to-date.

4.5 Monitoring, analytics and competitive positioning

• You track AI visibility, citation rate and share of voice for your key topics.
• GEO-specific KPIs and dashboards are defined and reviewed regularly.
• Competitor mentions in AI answers are monitored to identify content gaps and opportunities.

4.6 Platform-specific optimisation

• Content is structured so assistants like ChatGPT, Gemini, Claude and Perplexity can easily quote and summarise it.
• For Google AI Overviews, you optimise for snippets, FAQs and structured data as well as classic SEO factors.
• You maintain platform-specific Action plan as AI search products evolve.