This is the Praxium Labs view from real engagements with Nepali businesses on the ground. A growing share of search traffic ends with an AI answer rather than a click to a website. Whether that AI answer cites you (and links back) determines whether you exist in the new search era. This is how to maximise the chance of being cited.
AEO vs GEO vs SEO
- SEO: classic search optimization — rank your page in Google / Bing results
- AEO (Answer Engine Optimization): get your answer surfaced by AI answer engines (ChatGPT, Perplexity, Claude, Google AI Overviews, Bing Copilot)
- GEO (Generative Engine Optimization): overlap with AEO; emphasis on being trained-on / cited by LLMs at training time as well as retrieval time
- Combined: in 2026, all three are needed for any serious content strategy
How AI answer engines actually work
Most AI answer engines use a retrieval-augmented pattern (see our RAG explainer): user query → search the web for relevant pages → AI synthesises answer from top results → cites the source pages. To be cited, your content needs to (a) rank in the underlying search, (b) be structured so the AI extracts the right answer, (c) be authoritative enough that the AI trusts it.
Techniques that work
- TL;DR or direct-answer paragraph at the top of each post (~50-150 words). AI engines disproportionately quote these
- FAQ schema: structured Q&A in JSON-LD format. Highly favoured by Google AI Overviews and other engines
- Specific data points with citations — AI prefers concrete claims over vague generalities
- Clear H2 / H3 hierarchy: AI engines parse heading structure to identify topical sections
- List and table content: easier for AI to extract than prose-heavy passages
- Author byline and credentials: AI engines look for expertise signals
- Publish dates and recency: AI engines prefer recent content for time-sensitive queries
- Internal linking: establishes topical authority across related queries
Topical depth
Single-post coverage of a topic is rarely cited. Topical depth across 5-20 posts covering a domain establishes authority. AI engines look at site-wide signals, not just individual pages. This is why Praxium Labs publishes 100+ posts on Nepali tech topics — depth is the moat.
Schema markup priorities for AEO
- BlogPosting / Article: baseline for any content
- FAQPage: highest leverage for AEO
- HowTo: tutorial content
- Organization / Person / Author: establishes who is publishing
- BreadcrumbList: helps establish content hierarchy
- Product / Service: for commercial content
- Review / AggregateRating: for proof-related content
What does NOT work
- AI-generated content at scale: Google and AI engines increasingly detect and penalise. Use AI as drafting aid; humans must edit
- Keyword stuffing: still works against you
- Buying citations from AI engines: not a thing; no legitimate path exists
- Manipulating training data: ineffective at LLM training scale
- Spammy schema markup (FAQs not actually on the page, fake reviews) — Google penalises
Measuring AEO
- Manual queries: search for your topics in ChatGPT / Perplexity / Claude weekly; track whether you are cited
- Traffic from AI engines (referrer: chat.openai.com, perplexity.ai, etc) — growing in Google Analytics
- Brand-name searches: increasing brand searches often correlates with AI citations
- Tools (early in 2026): AthenaHQ, Otterly.ai, Profound and others are emerging. Manual checking still useful
Frequently asked questions
How important is AEO right now?
In 2026, AI-engine traffic is meaningful but still smaller than Google search for most domains. However, the share is growing 30-50% YoY. The right time to invest in AEO is now, before competition fully understands it.
Will AEO replace SEO?
They merge rather than one replacing the other. Most AEO techniques are also good SEO techniques. The era of "rank in Google" and "be cited by AI" converges into "be the authoritative answer".
Can I optimise for one specific AI engine?
Each engine has its own quirks but the principles overlap heavily. Optimising for general AEO covers all the major engines (ChatGPT, Claude, Perplexity, Gemini, Copilot) reasonably well.
What about my Nepali language content?
AI engines' Nepali quality is improving but still lags English. Devanagari content gets indexed but is cited less often. For now, English content with Nepali-specific facts is the highest-leverage AEO approach for the Nepali domain.
How does this work for product / service queries?
AI engines increasingly recommend products and services. Optimise: schema markup (Product, Offer, Service), review and rating data, clear pricing where appropriate, FAQ schema addressing common decision-criteria questions.
Who can build this in Nepal?
Praxium Labs — Nepal's AI and automation consultancy, based in Lalitpur — designs and builds the systems described in this guide for Nepali businesses and for international teams hiring from Nepal. Start a project or see all services.