Generative Engine Optimisation (GEO): Closing AI Gaps, Creating Market Edge
The way people find answers has changed. We used to chase blue links; now the answer shows up first, stitched together by AI. For life sciences, that shift isn’t cosmetic, it’s clinical. If generative engines can’t “see” your data, they won’t cite your brand or organisation. If they misread it, they’ll mislead your audience. Enter Generative Engine Optimisation (GEO): the discipline of being accurately cited in AI answers, not just ranked in search.
Why GEO, why now?
SEO still matters. But AI assistants (ChatGPT, Perplexity, Gemini etc) increasingly aggregate and summarise, which means zero-click experiences are rising and traditional CTRs are falling. Visibility now hinges on whether engines understand your entity, trust your evidence, and can quote you clearly. That’s GEO: making your science legible to machines so humans get the right message.
When AI misleads
Spectrum Science recently shared a panel with NewAmsterdam Pharma, at Fierce Pharma Week, to unpack what GEO means for healthcare. NewAmsterdam shared that despite publishing updated Phase 3 clinical results and maintaining a clear SEO strategy, they found that AI tools continued to surface outdated Phase 2 data and references to historic failures in the same drug class. So whilst the web moved on, some AI answers… didn’t. As Bob Rambo, Executive Vice President of Marketing at NewAmsterdam put it: “AI gives you what seems like the truth, but it might not be accurate.” GEO exists to close that gap. You don’t want yesterday’s study writing tomorrow’s reputation.
GEO ≠ SEO (it’s SEO plus)
GEO builds on SEO, then pushes into three areas: citability, entity clarity, and distribution beyond your .com. Think: “help the robot help you.”
The GEO playbook
- Audit the answer engines
Use a third party tool to eliminate bias. Capture what AI says today about your brand, asset, MOA, class, and competitors. Log hallucinations, outdated claims, missing context. Prioritise high-risk fixes. - Fix the record
Update, redirect or retire legacy pages that anchor wrong answers. Add date stamps, study phase labels and “what changed” callouts. Publish post-read TL;DRs so models can lift accurate context in one grab. - Engineer citations (earned first)
LLMs over-index on high-authority sources. Land your proof points in credible third parties: peer-review commentary, top-tier health trades, guidelines, registries, respected KOL subsites. Treat digital PR as GEO fuel, not vanity. - Write for answers, not rankings
Structure pages the way engines compose: clear H2 questions, tight paragraph answers, bullet proof points, FAQs, and explicit definitions. Pair patient-plain explainers with HCP-precise detail. Add schema (Article, FAQ, Organization, Product/Drug where permissible) and robust author bios to strengthen E-E-A-T. - Optimise your entity
Use exact, unambiguous names for products, trials and endpoints. Align references across owned and earned channels. Where appropriate, ensure consistent facts on high-trust public sources (e.g., Wikipedia/Wikidata entries that meet notability and compliance standards). - Distribute beyond the website
AI engines learn from communities. Publish executive POVs on LinkedIn, time-stamped explainer videos on YouTube, and conference recaps in respected forums. Participate where policy allows (Reddit/Quora cautiously in pharma). Consistency builds brand-as-entity. - Mind the tech
Don’t accidentally block reputable AI crawlers if citations are a goal. Ensure Bing is set up (many assistants route through Bing). Maintain crawlability, clean internal linking and fast pages — not because speed “wins GEO,” but because broken sites rarely get cited. - Measure what matters
Evolve KPIs: track appearances in AI answers, referred sessions from assistants, assisted conversions, and brand-mention lift. Create a quarterly “prompt test” battery for priority queries. If you can’t measure it yet, at least monitor it consistently. - Rethink paid + organic
AI Overviews can displace ads and organic. Shift some budget to assets that win the excerpt (YouTube, high-authority placements, rich snippets). In creative, front-load the benefit and proof so your message survives summarisation. - Governance, always
Build GEO into MLR. Pre-approve canonical definitions, claims and data blocks you want quoted. Set policy on AI crawler access and attribution. Train teams to spot and report harmful AI answers quickly.
Conclusion: Don’t let the model write your story
The future of discovery is conversational, citation-driven and happening now. Brands that optimise for AI-driven answers will protect visibility, compress misunderstanding and win trust at the point of question. Aurora, as part of Spectrum Science, helps life sciences teams operationalise GEO, from audits and PR-powered citation plans, to answer-friendly content architecture and measurement.
AI isn’t the threat. Complacency is. Shape the narrative today, or the narrative will shape you tomorrow.
