Are AIO and LLMO just SEO relabelled?

My opinion? I must admit, I had my own scepticism about AIO (Artificial Intelligence Optimisation) and LLMO (Large Language Model Optimisation) as standalone concepts at least. New marketing opportunities have always excited me though and cannot deny the potential benefits of being cited in the new era of AI search. I decided to dig deeper, build my own knowledge, and share my thoughts on the subject. If nothing else, this article will settle the debate in my own head once and for all.

What even is AIO and LLMO I hear you ask?

Fair point. Before diving in, here’s what AIO and LLMO mean.

AIO

AIO or artificial intelligence optimisation is the broadest term when it comes to optimising for all things AI. We’re not talking about Google’s AI Overview which also gets abbreviated to AIO. Confusing, I know! AIO goes beyond language models like ChatGPT and Perplexity. It focuses on optimising any digital asset or process for AI systems. Its real-life applications differ more than LLMO or SEO as it can be used for things like:

• Writing product descriptions
• Automatically adjusting search results
• Product recommendations

Saying this, maybe because the discipline of AI optimisation is new, a lot of people talk about AIO as optimising content for chat based large language models like ChatGPT and Perplexity. They’re wrong. That’s LLMO.

LLMO

LLMO or large language model optimisation is a discipline falling under the umbrella of AIO that concentrates on optimising content for large language models like ChatGPT, Perplexity, or even Google’s own AI Overview feature powered by Gemini. Unlike AIO, that  has a goal of leveraging AI to improve outcomes, the goal of LLMO is to increase visibility inside AI chatbots.

The core similarities: Why your (and my own) scepticism makes sense

Many fundamental strategies remain identical when comparing AIO, LLMO and SEO. The emphasis on answering questions, formatting content for readability, and creating clear, structured information has been central to good SEO for years. Google has been evolving into an "answer engine" since at least 2018 with the introduction of featured snippets and People Also Ask boxes. This is good news for many SEO professionals who have been doing things ‘properly’ and the brands who trust them to deliver results. You don’t need to change much if LLMO is something you think could work for your brand.

Traditional SEO practices that directly translate to AIO include

• Creating well-structured content with clear headings
• Using schema markup and structured data
• Writing content that directly answers user questions
• Optimising for user intent rather than just keywords
• Building topical authority and expertise (E-A-T)

The Marketing Buzzword Problem

My instinct and initial scepticism makes even more sense when you start searching for so-called AIO or LLMO solutions. So many products are explicitly described as using AI but when you dig a bit deeper, they’re rebranded existing products with AI terminology thrown in for the sake of it. People seem obsessed with rebranding apps with confusing AI jargon. It's just another way to overhype something that is in fact simple.

The Real Differences: Where AIO and LLMO diverge from SEO

There are some meaningful distinctions that go beyond rebranding I think is worth mentioning. Scepticism over, LLMO is a thing.

1. Shift from Rankings to Citations

Traditional SEO focuses on ranking positions in search engine result pages (SERPs), while LLMO emphasises being cited or referenced in AI-generated responses. This represents a fundamental shift from ‘getting traffic’ to ‘being the source of answers.’ Something we’re going to have to learn to embrace and I think very few experts would disagree. Website traffic and browsing behaviour is changing quick.

2. Different Content Processing

AI models process content differently than search engines. They use vector embeddings and semantic understanding rather than primarily keyword matching. This means content needs to be optimised for how AI models parse and synthesise information, not just how search crawlers index it.

3. Real-Time Synthesis vs. Static Ranking

While SEO operates on relatively static ranking algorithms, AI systems dynamically generate responses by synthesising information from multiple sources in real-time. This creates different optimisation requirements around content structure and authority signals. It’s not about a single page/URL having the most authority to rank so there’s less emphasis on building links to a page and more emphasis on AI systems understanding your content. Perhaps the saying ‘content is king’ will survive another ten years -  we can wish, right!

 4. Conversational vs. Keyword-Based Queries

AI tools are designed for natural language conversations rather than keyword-based searches. This requires optimising for different query types and user interaction patterns. Worth thinking about, but for those of us who thought voice search was going to be the future, it’s not a big change. Longer tail phrases, natural language, and answering questions in a way people (and bots) understand. It’s the SEO of 2023!

The Technical Reality

The underlying technical infrastructure does differ though, big time. Traditional search engines use lexical matching and backlink analysis, while AI systems rely on large language models that understand context and relationships between concepts. This creates genuinely different optimisation requirements around:

• Token efficiency and how content is embedded in AI training data
• Contextual authority rather than just domain and page authority
• Semantic relevance over keyword density and traditional on-page techniques
• Advanced multi-modal content understanding (text, images, structured data)

My verdict: Be kind, it’s just my opinion in a quick-changing landscape

My skepticism is largely justified. Much of what's being marketed as revolutionary AI optimisation is indeed SEO best practices relabelled. The core principles of creating high-quality, authoritative, well-structured content that answers user questions remain unchanged. If you’re doing SEO well, the chances are you’re doing LLMO well too.

The distribution and discovery mechanisms are genuinely evolving though. Your audience might be using Google today, but they might switch to Perplexity tomorrow. And finally, if anyone has a Perplexity Comet invite handy, throw it my way please! Perplexity Comet is a new browser that might just be the catalyst of change when it comes to how we use the internet. Bold statement, but I think it might just be another blow to Google’s armour.

AI-powered search systems are real, they’re growing, and undeniably they are the future of search. Embrace it, optimise for it, and keep pushing to get your brand remembered in a world that is changing fast. If you want to explore how Bigger Picture can help with your SEO, LLMO or AIO efforts, or you just want to shout at me because you think the future looks different, we’re here to listen.