Understanding the Future of Search

What is AI in SEO?

Artificial Intelligence SEO (AI SEO) refers to both the use of artificial intelligence within SEO workflows and the way AI is transforming search itself.

While AI can help automate research, analyze data and improve efficiency, the biggest shift is happening within search engines and AI-powered search platforms.

Artificial intelligence has been shaping search for much longer than many people realize.

In 2019, Google introduced BERT (Bidirectional Encoder Representations from Transformers), helping Search better understand words within the context of an entire sentence rather than individual keywords. This marked a significant shift towards understanding natural language and search intent.

Google continued that evolution with MUM (Multitask Unified Model), a more advanced AI system capable of understanding information across multiple languages and content formats.

Today, generative AI experiences such as Google AI Overviews, Google AI Mode, ChatGPT, Gemini and Claude are changing search once again. Rather than simply returning webpages, these platforms generate answers by interpreting and synthesizing information from multiple sources before recommending content to users.

For SEO teams, this represents another major evolution rather than a completely new discipline. Traditional SEO remains essential, but success increasingly depends on creating content and digital experiences that AI systems can understand, trust and recommend.

How AI is changing search

For more than two decades, search followed a familiar pattern. A user entered a query, reviewed a list of results and clicked through to a website.

Today, that journey looks very different.

AI-powered search experiences increasingly answer questions directly, summarize information from multiple sources and help users refine decisions without repeatedly returning to traditional search results. Instead of a single query, users ask follow-up questions, compare options and explore topics through an ongoing conversation.

This shift doesn’t replace SEO. It expands it.

Traditional search remains fundamental, but brands must now consider how they’re discovered across conversational search experiences, AI-generated answers and recommendation engines.

As search evolves, SEO is becoming less about individual rankings and more about helping AI systems understand, trust and recommend content.

One of the biggest mindset shifts for enterprise SEO teams is moving beyond individual keywords or prompts. Search journeys now evolve through multiple conversational turns as users compare options, refine their thinking and build confidence before making a decision.

Rather than asking:

“What prompts should I be tracking?”
Organizations should increasingly ask:

“Which conversations influence decisions in my market?”

Understanding those conversations provides a richer understanding of customer intent and helps identify where brands appear, disappear and earn recommendations throughout the customer journey.

Tracking & measuring AI performance

Traditional SEO metrics such as rankings, traffic and conversions remain essential, but they no longer provide the complete picture.

AI-powered search introduces new ways for people to discover brands. Instead of clicking through to a webpage, users increasingly receive AI-generated answers that reference multiple sources before deciding where to go next.

As search continues to evolve, enterprise SEO teams need to understand more than where they rank.

They also need to measure:

Pi Datametrics’ AI Search Visibility Tool helps enterprise SEO teams measure performance across Google AI Mode, ChatGPT and other AI-powered search platforms. By tracking mentions, citations, sentiment and conversational performance, brands can understand how they’re represented, identify opportunities to improve visibility and benchmark performance against competitors.

The platform also includes the Conversation Presence Index (CPI), a metric developed by Pi Datametrics that evaluates how visible, influential and recommendable a brand is across AI-driven conversations. Rather than measuring performance for a single prompt, CPI provides a unified view of conversational performance across the topics and conversations that matter most to your business.

Preparing for the future of search

Search will continue to evolve, but the brands that succeed won’t be the ones chasing every new AI feature.

They’ll be the ones creating better content, building stronger digital foundations and making it easier for both people and AI systems to understand, trust and recommend their brand.

As AI continues to reshape search, these are the areas enterprise SEO teams should focus on.

1. Create FAST Content

As search becomes increasingly AI-driven, content needs to do more than rank. AI systems increasingly reward content that demonstrates depth, originality and expertise, helping brands earn citations, remain present in conversations and build trust across AI-powered search experiences.

At Pi Datametrics, we encourage brands to create FAST Content, following four core principles:

1. Fresh – Keep content current, accurate and regularly updated.
2. Authentic – Share genuine expertise, first-hand experience and original perspectives.
3. Structured – Organize content clearly using logical headings, schema and machine-readable formats.
4. Trusted – Reinforce authority through credible evidence, expert contributors and strong brand signals.

Whether content appears in traditional search results or AI-generated answers, these principles help improve discoverability, increase trust and create stronger opportunities to earn citations and recommendations.

2. Think Beyond Keywords

Keyword research remains fundamental, but understanding complete customer journeys is becoming increasingly important.

Look beyond individual searches and consider the questions people ask, the comparisons they make and the conversations they have before making a decision. This broader view helps uncover opportunities that traditional keyword research alone may never reveal.

Rather than asking:

“What keywords should I optimize?”

Enterprise SEO teams should increasingly ask:

“Which conversations influence decisions in my market?”

3. Prepare Your Brand for AI Interpretation

As Jon Earnshaw explains, brands are increasingly being interpreted by AI systems rather than simply experienced by people.

To explain this shift, Jon developed the Interpretation Stack, a framework that outlines the signals AI systems increasingly use to understand, compare and recommend brands.

The Interpretation Stack consists of five key elements:

Input – Creating original, experience-led content that provides genuine value.
Novelty – Publishing unique insights and perspectives that differentiate your brand.
Threads – Understanding complete conversations rather than optimizing for individual prompts or keywords.
Entities – Providing clear, structured information that helps AI understand your products, services and brand.
Reputation – Building trust through reviews, mentions and authoritative third-party sources across the wider digital ecosystem.

Together, these signals help determine whether your brand is understood, trusted and recommended across AI-powered search experiences.

4. Measure What Matters

Traditional SEO metrics such as rankings, traffic and conversions remain essential, but they no longer tell the complete story.

Enterprise SEO teams should also understand:

AI SEO is evolving

As AI search continues to evolve, new terms such as Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) have emerged to describe the strategies brands use to improve visibility across AI-powered search experiences.

These approaches don’t replace SEO. They build on it, combining strong technical SEO with deeper, more original content and the structured information AI systems need to understand and recommend brands.