2026 AI Search Brand Visibility Study — AEGIS Index Benchmarks Across 40 Korean Digital Brands

Executive Summary — 5 Key Findings

Direct AEGIS Insight diagnostics (Gemini 2.5 Flash + Google Search Grounding) on 40 Korean digital brands produced five headline findings.

1. GEO is the only differentiating factor. SEO (77.6 vs 81.7) and AEO (75.9 vs 76.3) are virtually identical between established brands and startups/SMBs. The 20.7-point gap occurs exclusively in GEO.
2. Three startup/SMB brands scored GEO 0 — despite SEO scores of 60+. They are effectively invisible in the AI search ecosystem.
3. 35% of startups/SMBs are classified S6_STEALTH — SEO and AEO above 60, but no GEO foundation for AI citation.
4. Retail & E-commerce leads all sectors — average AEGIS Index 77.0. Education is lowest at 67.1.
5. The GEO first-mover window is open. Even established brands average only 78.0. AI search ecosystem construction is still in progress across all tiers.

Research Design & Methodology

Data Collection

This report is based on direct measurements taken by the researcher using the AEGIS Insight diagnostic tool on 40 Korean digital brands.

• Collection date: June 29, 2026
• Diagnostic tool: AEGIS Insight — Gemini 2.5 Flash + Google Search Grounding
• Measurement items: 13 SEO items, 13 AEO items, 12 GEO items (38 total)
• Sample composition: 20 established brands (sector-leading digital natives) + 20 startups/SMBs (growth-stage companies in the same sectors)
• Sector coverage: IT/SaaS, Retail/E-commerce, Education, Finance/Fintech, Manufacturing/Services, Medical/Legal/Real Estate (6–8 brands per sector)

AEGIS Index Formula

AEGIS Index = SEO×0.25 + AEO×0.25 + GEO×0.50. GEO carries double weighting because generative AI search is the dominant future channel for brand visibility. A Critical Fail gate applies when SEO scores below 30.

Study Limitations

This is a small-scale pilot study of 40 brands. The sample skews toward digitally active companies and does not represent the full population of Korean brands. Figures should be treated as directional benchmarks, not definitive statistics.

Finding 1: Established Brands vs Startups/SMBs — Separated by GEO Alone

Comparing average scores between the two groups produces a counterintuitive result.

Metric	Established Brands (n=20)	Startups/SMBs (n=20)	Gap
Average SEO	77.6	81.7	−4.1 (startups lead)
Average AEO	75.9	76.3	≈ parity (0.4)
Average GEO	79.3	58.6	▼20.7 ← decisive gap
Average AEGIS Index	78.0	68.8	▼9.2

SEO and AEO are essentially equal — startups actually score 4.1 points higher on SEO. This signals that technical SEO knowledge is now broadly commoditized across the industry.

The decisive difference is GEO. Established brands averaged 79.3 vs startups/SMBs at 58.6 — a 20.7-point gap. GEO depends on accumulated external authority: Wikipedia and Namu Wiki listings, major media mentions, brand Entity construction. These require investment scale and brand age to develop — they cannot be replicated quickly.

SEO and AEO are already converging. The next battleground is GEO. Who AI chooses to cite is being decided right now — in the external ecosystem, not on your website.

Finding 2: Scenario Distribution by Group

Mapping both groups across AEGIS's eight diagnostic scenarios reveals a stark structural contrast.

Scenario	Established Brands	Startups/SMBs
S8_AEGIS (all dimensions 60+)	80% (16 brands)	60% (12 brands)
S7_TITAN (SEO+GEO 60+)	10% (2 brands)	5% (1 brand)
S6_STEALTH (SEO+AEO 60+, GEO below threshold)	5% (1 brand)	35% (7 brands)
S3_MIRAGE (GEO 60+, SEO below threshold)	5% (1 brand)	—

35% of startups/SMBs fall into S6_STEALTH — technically optimized on SEO and AEO, but with no GEO foundation for AI citation. This is the classic growth-stage brand pattern: product development investment concentrated on technical channels, while external authority infrastructure has not yet been started.

Finding 3: The GEO-Zero Brand Paradox

Three brands in the startup/SMB group recorded GEO 0. What makes these cases striking is that their SEO scores are exceptional.

Brand (anonymized)	SEO	AEO	GEO	AEGIS Index	Scenario
HR SaaS A	81	88	0	42.3	S6_STEALTH
Athleisure Commerce B	98	80	0	44.5	S6_STEALTH
Coding Education C	91	74	0	41.3	S6_STEALTH

Despite strong technical SEO foundations (81–98 points), GEO registers zero. The shared root cause: no Wikipedia or Namu Wiki listing, no significant media coverage, no AI-facing content. When GEO = 0, the GEO weight (×0.50) in the AEGIS Index formula vanishes entirely — final scores collapse into the low 40s regardless of technical excellence.

These brands do not appear as cited sources when users search related keywords on ChatGPT or Perplexity. Owning page-one Google rankings and building AI search citation authority are now two separate fights.

Finding 4: AEGIS Index by Industry Sector

Comparing overall averages (n=40) and within-group gaps across six sectors.

Sector	Overall Average	Established Brands	Startups/SMBs	Within-group Gap
Retail & E-commerce	77.0	85.4	68.5	16.9
Medical / Legal / Real Estate	76.6	79.8	73.4	6.4
Finance & Fintech	75.5	74.3	76.6	−2.3 (startups lead)
Manufacturing & Services	75.0	77.5	72.5	5.0
IT & SaaS	69.5	75.0	63.9	11.1
Education	67.1	74.7	59.5	15.2

Finance & Fintech is the only sector where startups/SMBs outperform established brands (by 2.3 points). Fintech startups like Finda and Sam3.3 were forced early into heavy content marketing and media exposure due to regulatory environments — building stronger GEO foundations than their larger sector peers as a result.

The Education gap (15.2 points) is the second-largest. Education startups concentrated investment on product development, leaving GEO infrastructure construction significantly delayed compared to other sectors.

Finding 5: SEO & AEO Converging, GEO Diverging

The most important implication of this study is that SEO and AEO have entered a convergence phase among digitally active Korean brands.

Across brands with strong digital activity, SEO (77–82) and AEO (75–76) show virtually no inter-group difference. Technical SEO knowledge and structured data implementation are now sufficiently commoditized across the industry.

GEO, by contrast, shows the largest inter-group gap (20.7 points) and extreme intra-group variance among startups/SMBs — ranging from 0 to 89 points (standard deviation ~28). GEO depends on accumulated media assets and external ecosystem authority, making short-term reversal difficult.

This is precisely why GEO investment is urgent today. Brands that build external citation foundations before competition migrates to GEO will create an AI-search moat that competitors cannot close quickly.

Recommendations — Execution Strategy by Tier

GEO First-Mover Roadmap for Startups & SMBs

• Immediate (within 1 week): Allow GPTBot and Google-Extended in robots.txt; publish one definitional brand blog post (AI-facing, FAQ-structured)
• Short-term (1 month): Contribute 2–3 pieces to industry media or blogs; launch a branded YouTube channel; pursue Namu Wiki listing
• Medium-term (3 months): Publish original data or a survey report to attract inbound citations; build a series of definitional content around brand name + category keywords

S8_AEGIS Maintenance Strategy for Established Brands

80% of established brands have achieved S8_AEGIS, but the average of 78.0 leaves headroom before the ceiling. Additional GEO points are available in two high-value items: original data/research publication (×1.5 weight) and citation-optimized reference documents (×1.5 weight).

Conclusion — GEO Is the Moat of the AI Search Era

The central message from 40 brand diagnostics is unambiguous. SEO and AEO entry barriers have lowered. GEO is emerging as the final arena of differentiation.

Brands building GEO foundations today are creating a moat in the AI search ecosystem that competitors will find difficult to cross. Wikipedia listings, media citations, and brand Entity are compounding assets. A brand that starts today holds a decisive advantage six months from now when AI search becomes the dominant discovery channel.

What is your brand's GEO score? Run a free diagnostic on AEGIS Insight to find out.

This study is a small-scale pilot covering 40 brands. The sample skews toward digitally active companies and is not representative of the full population of Korean businesses. AEGIS Index scores are AI-estimated diagnostics based on Gemini 2.5 Flash + Google Search Grounding, current as of the collection date (June 29, 2026). Individual brand data has been anonymized for research purposes.