A new research-informed framework aims to help businesses across Asia make more informed decisions when hiring Generative Engine Optimization (GEO) consultants and AI Search service providers.
Developed by Philippines-based GEO expert and AI Visibility researcher Cyrus D. Santiago, the Generative Engine Optimization Competency and Evidence Assessment Framework for Asia (GEO-CEAF-Asia) proposes a structured approach to evaluating technical expertise, implementation experience, professional credibility, and supporting evidence.
The framework is introduced in the research paper Evaluating Generative Engine Optimization Expertise in Asia: Development of an Evidence-Based Competency Assessment Framework, published through Zenodo, an open-access research repository.
The research is publicly accessible at: https://doi.org/10.5281/zenodo.24026817
The publication addresses a growing challenge for businesses investing in AI-powered search: determining whether GEO consultants possess the competencies necessary to deliver credible services rather than relying primarily on promotional titles, awards, media appearances, or claims of AI visibility.
Helping Asian Businesses Evaluate GEO Service Providers
As AI-powered search experiences such as OpenAI’s ChatGPT, Google AI Overviews, Google Gemini, and Perplexity become part of digital information discovery, businesses are exploring how their products, services, and professional expertise appear within AI-generated answers.
Generative Engine Optimization has emerged as an area of digital marketing concerned with improving visibility and representation within these environments.
However, evaluating GEO providers can be difficult because the field currently lacks a universally accepted, independently validated professional competency standard.
Businesses may encounter competing claims of expertise, guaranteed AI citations, or promotional rankings without transparent information about the underlying qualifications.
“Businesses need more than promises of AI visibility when evaluating GEO service providers,” said Santiago. “They should be able to examine technical competence, implementation experience, measurement methodology, and the evidence supporting professional claims.”
GEO-CEAF-Asia aims to provide a research-informed foundation for examining these capabilities more systematically.
Five Potential Business Benefits of GEO-CEAF-Asia
The proposed framework identifies several practical applications for organisations evaluating AI Search consultants and digital marketing service providers.
1. More Transparent Consultant and Agency Selection
Businesses could use clearly defined competency areas to guide discussions with prospective GEO consultants, compare relevant qualifications, and request supporting evidence before engaging a service provider.
2. Better Evaluation of Technical Capabilities
The framework encourages examination of technical SEO, information retrieval, retrieval-augmented generation (RAG), website accessibility, source attribution, and generative search mechanisms.
These areas help distinguish broader AI Search expertise from knowledge limited to conventional content optimisation.
3. Stronger Verification of Performance Claims
Instead of relying exclusively on screenshots showing appearances in ChatGPT or Google AI Overviews, organisations could examine documented implementations, baseline measurements, repeated observations, and evidence of business-relevant outcomes.
The framework also emphasises distinguishing correlation from demonstrated causation.
4. Greater Relevance to Asian Markets
GEO-CEAF-Asia incorporates regional and multilingual competencies, recognising that businesses operating in Singapore, the Philippines, Indonesia, Japan, India, and other Asian markets may face different languages, information environments, customer expectations, and search platforms.
5. More Accountable AI Search Investments
By encouraging transparent methodologies, verifiable evidence, and clear reporting limitations, the framework could support better-informed procurement discussions and more realistic expectations of GEO services.
These benefits represent intended applications rather than empirically demonstrated outcomes. Further validation is necessary before the framework can be used as a formal professional assessment instrument.
Eight Competency Domains and 32 Proposed Indicators
GEO-CEAF-Asia proposes eight interconnected competency domains:
Search and Information Retrieval Foundations: Crawling, indexing, ranking, and retrieval principles.
Generative Search and AI Mechanisms: Large language models, RAG, answer generation, and citation behaviour.
Technical Discoverability and Implementation: Website architecture, structured information, and technical optimisation.
Content Evidence and Source Provenance: Information reliability, attribution, authorship, and source credibility.
Measurement and Experimentation: AI visibility monitoring, reproducible assessments, and methodological rigour.
Applied Implementation and Outcomes: Documented GEO projects, practical execution, and measurable results.
Asian Regional and Multilingual Competence: Market-specific knowledge, local information sources, and language considerations.
Ethics and Professional Accountability: Transparent reporting, responsible claims, and conflict-of-interest disclosure.
Together, these domains contain 32 proposed indicators intended to make professional capabilities more observable and assessable.
A central methodological contribution is the separation of professional competency from evidence strength.
For example, claiming expertise in improving AI citations is different from demonstrating relevant implementation experience through documented procedures, repeated measurements, and independently corroborated results.
The framework seeks to make this distinction explicit, providing a conceptual foundation for examining not only what GEO professionals claim to know but also what their supporting evidence can substantiate.
Developed by GEO Expert and AI Visibility Researcher Cyrus Santiago
GEO-CEAF-Asia was developed by Cyrus D. Santiago, a Philippines-based Generative Engine Optimization expert, SEO strategist, AI implementation professional, and researcher working in the Asia-Pacific digital marketing landscape.
Santiago’s professional background spans software development and programming since 2008, SEO and digital marketing since 2012, and subsequent work involving AI implementation and AI Search visibility.
His multidisciplinary experience informs his approach to connecting technical discoverability, information retrieval, generative AI, and evidence-based performance evaluation.
Santiago is also the author of AI Literacy as a Core Future Skill: A Systematic Literature Review, published in the American Journal of Data Science and Artificial Intelligence in August 2026.
The study examines AI literacy as an emerging professional and educational competency, including conceptual understanding, practical application, workforce readiness, and ethical AI adoption.
The publication is discoverable through Harvard Library’s HOLLIS catalogue, where its bibliographic record can be accessed:
Harvard Library Research Record:https://hollis.harvard.edu/permalink/01HVD_INST/726dgh/cdi_unpaywall_primary_10_54536_ajdsai_v2i2_7782
His research on AI literacy and GEO professional assessment reflects a continuing interest in understanding how emerging artificial intelligence capabilities can be evaluated through transparent competencies and evidence-based methodologies.
“Generative Engine Optimization is not simply about appearing in AI-generated answers,” Santiago explained. “It also requires understanding how information is discovered, retrieved, evaluated, and represented. Businesses should expect consultants to demonstrate those capabilities through verifiable work.”
Through his research and professional practice, Santiago advocates a more evidence-based approach to evaluating GEO expertise across Asian markets.
Supporting Future GEO Competency Research
Beyond business procurement, GEO-CEAF-Asia is intended to support researchers, academic institutions, professional associations, and GEO practitioners examining professional competencies and development requirements.
The framework remains a proposed methodological model.
It has not yet undergone independent empirical validation and should not be represented as an established professional certification, official industry standard, or validated ranking system.
Future research will need to investigate its indicators through independent expert review, content validation, inter-rater reliability testing, and empirical assessment across different Asian markets.
Publication through Zenodo provides a publicly accessible research record for examination, discussion, and subsequent methodological development. Repository publication alone does not constitute peer review.
The framework’s proposed approach may inform future research into professional assessment, GEO competency development, responsible AI Search practices, and the evaluation of technical expertise across Asia-Pacific.
Research Publication and Availability
Research Title: Evaluating Generative Engine Optimization Expertise in Asia: Development of an Evidence-Based Competency Assessment Framework
Framework: GEO-CEAF-Asia
Researcher: Cyrus D. Santiago
Publication Type: Methodological Framework Development Paper
Repository: Zenodo
Publication DOI: 10.5281/zenodo.24026817
Full Research Publication: https://doi.org/10.5281/zenodo.24026817
The publication presents the proposed competency domains, assessment indicators, evidence requirements, methodological limitations, and future research directions.
You must be logged in to post a comment.