Editors’ note: Today’s post is by Stephanie Lovegrove Hansen and Kristina Henrikson. Kristina is the Director of Marketing and Communications at Canadian Science Publishing and has more than a decade of experience in scholarly publishing.

Search Engine Optimization (SEO) isn’t new. It’s been a cornerstone of website strategy for decades, helping brands compete for visibility online. At its core, SEO is about improving how your content ranks on search engines so it appears among the top results. As the search and user behavior landscapes undergo dramatic evolutions, however, marketers and others are left to wonder what SEO (and all the other -EOs) means for publishers now and how we can ensure that our content is still discoverable in the internet of the future.

What is SEO?

For years, SEO was a race to the top, driven by tactics like metadata optimization, structured in-page content, and keyword research. The focus shifted to writing high-quality content that incorporated keywords naturally, alongside strong link-building strategies, thereby earning backlinks from reputable websites and establishing credibility. Over time, SEO has expanded to include technical factors like page speed, mobile optimization, and user experience, as well as the practice of regularly updating content so that search algorithms index pages more frequently. Ensuring that websites remain authoritative and relevant for both search engines and users reinforced the idea that content is king.

As user behavior changed, so did SEO strategies. The concept of “Search Everywhere (not Engine) Optimization” emerged, reflecting the need to think beyond your website. Today, people discover content across multiple platforms: social media, YouTube, blogs, and other channels. Paid search and algorithmic changes also reshaped visibility, making it more important to maintain a flexible, multi-channel content strategy that keeps your brand visible wherever people search. In this world, discoverability means thinking beyond keywords. It’s about building interconnected content ecosystems, where website, social, and video content all reinforce each other and help audiences find you wherever they are searching.

In scholarly publishing, this approach extends to Academic Search Engine Optimization (ASEO). Research content lives not only on journal websites but also in discovery platforms, such as Google Scholar, PubMed, and institutional repositories. ASEO focuses on increasing the visibility of academic work across these systems through clear metadata, structured abstracts, and accessible titles and keywords. For publishers and editors, this means ensuring research outputs are easy to find, cite, and use, supporting both discoverability and impact within the scholarly record.

As AI systems like ChatGPT and other generative tools begin indexing and summarizing research, the same ASEO principles (clarity, structure, and accessibility) become critical for discoverability if and when content is made available to these systems. Even when access is restricted, well-structured content supports human discoverability, interoperability, and potential future AI indexing.

The latest evolution in search is Generative Engine Optimization (GEO), which focuses on optimizing content so it can be effectively understood and surfaced by AI systems. Being discoverable in this AI-driven landscape is becoming as important as ranking highly on Google and requires an evolving strategy to ensure that content is discoverable to both human and AI audiences.

The Changing Landscape

As we are all painfully aware, traditional search engines have evolved and are now complemented (and in some cases replaced) by AI. User behavior has shifted significantly as people increasingly start their journeys through plain-language search or AI prompts, reflecting a move toward more intuitive, conversational ways of finding information. And with AI-generated summaries appearing alongside traditional search results, publishers have the opportunity for content to reach audiences in new ways, though those opportunities require adapted strategies.

As GEO continues to evolve, it’s clear that this isn’t SEO versus GEO — it’s a combination of the two. We’re not changing our focus, but expanding our strategy to consider how users will discover our content. Today, we need to think like both the AI tools (the engine generating answers) and the user (the human seeking information) — essentially, two audiences at once. GEO isn’t yet as formally established as SEO, so it will be important to remain flexible and informed as best practices arise.

We’ve seen similar challenges before. In the early days, SEO strategy was like the wild west: keyword stuffing and hidden tags crowded out credible content until search engines learned to reward quality and relevance. Paid advertising added another layer, drawing attention to paid placements rather than the most trustworthy sources.

The difference today is that AI doesn’t just rank information, it interprets it, reshaping how authority and accuracy are perceived. This introduces a new kind of risk. Generative tools can surface content that appears authoritative but may be incomplete, misleading, or inaccurate, drawing from the vast pool of information online. The underlying challenge remains the same: ensuring trustworthy, accurate content rises above the noise.

How SEO Serves Public Trust in Science

The dip in public trust in science over the last few years makes this topic all the more urgent. Search visibility determines which sources people encounter first when seeking information about health, climate, technology, or any domain where evidence matters. So SEO and discoverability have a direct relationship to building public trust.

As we know, the pandemic accelerated this challenge as misinformation, misunderstanding of early-stage research, and desperation to find answers collided, putting the research ecosystem under intense scrutiny. If peer-reviewed research sits buried, while predatory journals, preprint servers without peer review flags, or opinion masked as fact rank higher, we fail our fundamental mission as stewards of the scholarly record.

Of course, the role of AI in discovery has further muddied this endeavor. When AI crawlers are blocked from quality research, it amplifies the “garbage in, garbage out” problem, muddying the credibility of results. After all, poor SEO practices don’t just hide research from human readers — they exclude it from the training data and knowledge bases of systems that increasingly mediate access to information.

Indeed, data lies at the heart of many of today’s challenges and solutions. Well-structured data that follows industry best practices and standards helps search engines understand not just that content exists, but what it represents. Robust data flowing from editorial and marketing teams and being displayed properly by platforms will continue to serve the needs around SEO / GEO as it evolves, and reinforces the fact that discoverability is everyone’s responsibility.

Possible SEO Futures

Where the SEO conversation will be in five years is anyone’s guess, which makes it even harder for organizations to prepare. Search could continue to fragment, with researchers beginning their searches within specialized databases, ChatGPT, and similar tools. Publishers need to optimize for multiple discovery paths simultaneously, which means moving beyond traditional search engine optimization toward broader content accessibility strategies.

AI-mediated discovery could look like a user asking an AI tool about recent findings in a research area and receiving an answer synthesized from sources in its training data, via a RAG model, or retrieved through real-time search. These solutions already exist (see OUP’s Law Pro).

Perhaps there will be no publisher sites at all, and research data will be fed directly into LLMs and AI tools in the format most easily ingested, leaving things like user experience to the likes of Claude, ChatGPT, and other tools.

Licensing and training data rights may also impact how publishers approach their discoverability strategy. We’re already seeing glimpses of a future where publishers actively negotiate their content’s role in AI training rather than passively optimizing for algorithmic visibility.

Finally, the relationship between SEO and content strategy will likely tighten. Rather than optimizing existing content for search, publishers may increasingly create content designed from inception for specific discovery paths — whether that’s FAQ-style content that appears in voice search results, video abstracts optimized for YouTube discovery, or graphical abstracts designed for visual search engines. Content strategies will need to be more inclusive, thinking beyond just human audiences to include AI systems and the broader digital ecosystem.

Actions Marketing Teams Can Take to Futureproof SEO

So, yes — SEO is a complicated, fragmented, and ever-shifting hydra. But all is not lost! There are things Marketing teams can do that solidify their SEO approach, no matter which direction it goes.

• Audit the way your content currently appears across different discovery channels. This means going beyond traditional Google searches to test how content surfaces in ChatGPT, Perplexity, AI Overviews, and specialized academic search tools. Understanding current visibility provides baseline data for measuring improvement and reveals gaps where valuable research remains hidden.
• Don’t forget your data. The audit should extend to structured data implementation, consistently populated metadata, and high-value abstracts, keywords, and author information. This technical-sounding work actually requires editorial judgment about which terms matter most, how to describe research for broader audiences, and what contextual information helps position an article within its field.
• Develop a content strategy for discoverability. This includes developing plain-language abstracts optimized for general search alongside technical abstracts for specialist audiences, creating FAQ content that addresses common questions about research findings, and producing supplementary materials designed specifically for AI systems to parse and cite.
• Strengthen the relationship between content and creators. Many SEO opportunities get lost because researchers and editors don’t understand how their choices affect discoverability. Creating guidelines for authors about effective titles, keyword selection, and abstract writing serves both traditional academic purposes and search optimization.
• Monitor performance over time. Use analytics and AI grader tools to benchmark how your content appears across search engines and AI systems. This includes both journal content and supporting pages, since the full website ecosystem contributes to visibility and credibility. Consider GEO principles, ensuring content structure and schema markup support AI-driven discoverability. Track outcomes such as downloads, newsletter signups, and webinar registrations in addition to search visibility to measure engagement and impact. Monitoring performance helps you understand shifts in user behaviour and spot emerging trends.

The landscape of content discovery will continue to evolve rapidly. SEO and GEO remain foundational to ensuring content is visible, trustworthy, and accessible across both human and AI-driven channels. Publisher websites are shifting from being the primary “home” for content to serving as vehicles that establish credibility, authority, and trust, while content is increasingly discovered across multiple platforms. In this environment, integrating SEO and GEO strategies, maintaining clarity and reliability, and meeting audiences where they engage are essential for success.

Our responsibility is to communicate science clearly, collaborate with credible voices, and ensure that both human readers and AI systems can access accurate, authoritative information. By prioritizing authenticity alongside optimization, we protect visibility, trust, and the integrity of research in an increasingly complex information landscape. Staying vigilant, adaptable, and audience-focused will ensure that research content remains discoverable and relevant as content and technology continue to evolve.