Why SERPs by no means stand nonetheless

Twenty years in the past, Google’s search outcomes had been famously easy: ten blue hyperlinks, a handful of advertisements, and little else. Right this moment, a single question can floor AI-generated summaries, maps, photographs, movies, buying outcomes, and discussion board discussions – typically earlier than a person clicks something.

For CMOs, this shift can really feel unsettling. But it surely shouldn’t be shocking. Search has all the time developed in response to how people search info. AI Overviews aren’t a rupture – they’re the most recent chapter in a protracted story of search changing into sooner, richer, and extra environment friendly.

This text traces the evolution of SERPs over the past 20 years, locations AI Search in its historic context, and descriptions what leaders ought to give attention to subsequent.

A screenshot of the Google search interface from the early 2000s, displaying a simple list of

Search earlier than Search Engines: a human fixed

Lengthy earlier than Google, people relied on oral data, libraries, encyclopaedias, and trusted consultants. Every technological leap – the printing press, indexing programs, the web – lowered friction between a query and its reply.

Engines like google didn’t change why we search. They modified how shortly we are able to fulfill curiosity. From that perspective, AI-generated solutions aren’t radical. 

They’re a continuation of the identical trajectory: compressing effort, time, and cognitive load.

A timeline graphic titled

2005–2009: the period of 10 blue hyperlinks

Within the mid-2000s, SERPs had been linear and predictable. Natural rankings had been largely decided by hyperlinks and key phrase relevance, whereas paid advertisements appeared above or beside outcomes.

Key developments:

  • 2005: Introduction of sitelinks for navigational queries
  • 2007: Universal Search blends information, photographs, video, and maps into natural outcomes

Common Search marked the primary main break from uniform outcomes, forcing manufacturers to assume past webpages and optimise for a number of content material varieties.

2010–2013: richer outcomes and the data graph

As broadband improved and person expectations rose, Google accelerated SERP innovation.

Key milestones:

  • 2010–2011: Autocomplete begins shaping person intent. Google’s predictive search options began influencing how individuals phrased queries, subtly guiding demand and shortening the trail to solutions.
  • 2012: Launch of the Knowledge Graph – “issues, not strings”, representing a major shift in the direction of optimising for Entities.

Information Panels allowed Google to reply factual queries straight, decreasing dependency on clicks whereas growing belief in search as an authority.

This shift laid the muse for entity-based website positioning, explored additional in Hallam’s information to entities in SEO.

A Google Knowledge Panel for Thomas Jefferson, displaying a biographical summary, key facts, and image carousel, illustrating the shift toward entity-based search results introduced in 2012.

2014–2015: featured snippets, native packs and mobile-first actuality

The mid-2010s launched the idea of zero-click search.

Key developments:

  • 2014: Featured snippets (“Place Zero”) seem above natural outcomes
  • 2015: Mobilegeddon (or “Cell-first”) prioritises mobile-friendly pages in SERPs
  • 2015: Google lowered the variety of native companies proven in search outcomes, concentrating visibility on fewer, extra outstanding listings – a transfer pushed by cell utilization and person behaviour.

Featured snippets rewarded structured, authoritative content material, and previewed a future the place Google more and more solutions questions itself.

A Google search result for

2015–2019: AI enters the algorithm

Whereas SERP layouts stabilised, Google’s understanding of queries improved dramatically.

Key milestones:

  • 2015–2016: RankBrain applies machine studying to rating programs, permitting increased high quality and relevancy in search outcomes
  • 2016: “Folks Additionally Ask” introduces expandable, question-led search journeys. Google started surfacing follow-up questions straight within the outcomes, encouraging customers to discover subjects with out reformulating searches or clicking by means of a number of pages.
  • 2019: BERT allows contextual understanding of pure language

These updates bolstered a essential reality: optimisation was now not about matching key phrases, however about satisfying intent.

For manufacturers, this meant investing in depth, readability, and credibility – not shortcuts.

A side-by-side comparison of mobile search results for

2020–2022: SERPs develop into experiences

The early 2020s noticed Google reshape SERPs into immersive experiences:

  • Steady scroll replaces pagination
  • Video and visible search acquire prominence
  • MUM expands multi-modal understanding

On the similar time, person behaviour fragmented. Discovery more and more occurred throughout YouTube, TikTok, Reddit, and marketplaces – not simply Google.

This era bolstered the necessity for a Whole Search mindset, explored additional in our article on navigating the era of AI-powered search.

A modern search result page for

2023–2025: AI Overviews and generative search

The launch of AI Overviews represents probably the most seen SERP shift in a decade.

AI Overviews:

  • Generate authentic summaries from a number of sources
  • Prioritise synthesis over itemizing
  • Scale back clicks for informational queries

Early knowledge suggests elevated zero-click behaviour (60% of Google Searches now don’t result in a click), but in addition new alternatives for citation-level visibility.

Importantly, Google has been clear: AI Overviews nonetheless depend on conventional rating programs and high-quality sources, and we don’t have to reinvent the wheel by calling it “GEO”.

A 2024 Google search result in dark mode showing an

What this implies for CMOs

AI Overviews really feel disruptive as a result of they’re seen. However strategically, they reward the identical behaviours which have pushed sustainable website positioning for years.

John Mueller has repeatedly bolstered that there is no such thing as a separate optimisation playbook for generative search – robust website positioning foundations stay the prerequisite.

In different phrases: good GEO is sweet website positioning. 

Actionable priorities for AI Search readiness

1. Put money into authority, not quantity

AI programs preferentially cite trusted sources. Digital PR, expert-led content material, and model mentions matter greater than ever – as explored in Hallam’s perspective on Digital PR in 2026.

2. Optimise for entities and understanding

Entity readability helps AI contextualise your model. This implies:

  • Clear topical possession
  • Structured knowledge
  • Constant messaging throughout channels

3. Construction content material for solutions

Nicely-structured pages: clear headings, concise explanations, supporting proof, usually tend to be surfaced in AI summaries.

4. Keep away from chasing “GEO hacks”

There is no such thing as a shortcut. Manufacturers chasing AI-specific methods threat undermining long-term efficiency. As an alternative, give attention to:

  • Technical excellence
  • Person-first content material
  • Credibility indicators

Adaptation is the benefit

From encyclopaedias to AI summaries, the story of search is the story of human adaptation. Every evolution has lowered friction, and every has rewarded manufacturers that prioritise usefulness, belief, and readability.

AI Overviews aren’t the tip of website positioning. They’re a reminder of what website positioning has all the time been about.

For CMOs, the mandate is evident: spend money on fundamentals, embrace change calmly, and construct manufacturers that need to be cited – by people and machines alike.

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