Information Technology & Services: AI Visibility Market Discovery Index

Benchmark Summary

Questions This Section Answers

• Who leads the Information Technology & Services category in AI recommendation coverage?
• Did any brand move beyond normal month-to-month variation in October 2026?

Accenture leads the category in October 2026 with valid recommendation coverage of 58.0%, ahead of IBM Consulting at 46.5%, a gap of 11.5 percentage points. No brand moved beyond normal month-to-month variation, with the largest decline Accenture's, down 1.9 points, and the largest increase Vention's, up 3.2 points. The benchmark began with 800 prompt-surface observations in each month and produced 601 qualified observations in September 2026 and 574 in October 2026 after qualification.

Current Benchmark at a Glance

Qualified surface breadth is the number of canonical AI surface families with at least one qualified observation in the month. The six canonical families are ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. Both months reached the full breadth of six families.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Information Technology & Services

Research Scope and Qualification

Questions This Section Answers

• Why is the published benchmark denominator smaller than the raw prompt-surface collection?

The public benchmark is narrower than the raw collection universe by design. The table below shows how observations move from raw collection to the published denominator.

Brand-level percentages use the qualified observations as the public denominator, not the raw collection. For formulas and denominator rules, see AI Visibility Market Discovery Methodology.

Current Brand Standings

Questions This Section Answers

• How do the eight tracked brands separate on valid recommendation coverage and placement metrics?
• Why is Taazaa Inc last on every recommendation metric in this benchmark?

How to Read the Standings

• Presence rate: the share of qualified observations in which the brand appeared at all, whether or not it was recommended.
• Valid recommendation coverage: the share of qualified observations in which the brand received a valid recommendation. This is the primary metric for the index.
• Top-three rate: the share of qualified observations in which the brand was recommended in the top three positions.
• Rank-one rate: the share of qualified observations in which the brand was the first recommendation.
• Net sentiment: the balance of positive against negative mentions, where 1.0 indicates no negative mentions were recorded.

For formulas and denominator rules, see AI Visibility Market Discovery Metric Definitions.

Taazaa Inc: Company Position

Taazaa Inc recorded a presence rate of 0.4% in October 2026, with valid recommendation coverage of 0.4%, a top-three rate of 0.0%, a rank-one rate of 0.0%, and net sentiment of 1.0. These figures place Taazaa Inc last among the eight tracked brands on every recommendation metric in this benchmark, with coverage up only 0.4 points from the September 2026 baseline of 0.0%.

Accenture records 58.0% on valid recommendation coverage, while Taazaa Inc stands at 0.4%. At a 0.4% presence rate, Taazaa Inc is essentially absent from the qualified observations that make up this benchmark, so there is almost no recommendation visibility to build from, let alone convert into top-three or rank-one placement. The net sentiment of 1.0 reflects the small number of observations in which Taazaa Inc appeared at all, not a demonstrated strength, and it does not offset the scale of the coverage gap. Left unaddressed, this is a material gap that leaves Taazaa Inc effectively outside the category's AI-driven recommendation conversations that Accenture and IBM Consulting already dominate.

Highest-priority diagnostic: Why does Taazaa Inc appear in only 0.4% of qualified observations in this category, and what would be required to move presence and valid recommendation coverage into a measurable range before placement or rank-one performance can be meaningfully assessed?

Recommendation Coverage Movement

Questions This Section Answers

• Which brands gained or lost recommendation coverage since the September 2026 baseline?
• Did any coverage change this month signal a real shift or just normal variation?

Movement is measured from the baseline month of September 2026 to October 2026.

The current month was quiet. No brand moved beyond normal month-to-month variation, and the largest single-month change across the category was Vention's 3.2-point increase, which remained inside its normal variation range. There are no significant risers or decliners to report this month. The gap between Accenture and Vention widened from 45.9 points in September 2026 to 40.8 points in October 2026.

Category Leader: Accenture

Accenture remains the category leader with valid recommendation coverage of 58.0% in October 2026, down from 59.9% in September 2026. Its presence rate was 78.4% in October 2026, its top-three rate was 50.7%, and its rank-one rate was 43.4%. The leadership position is stable and the movement this month falls within normal variation.

Recommendation Placement Snapshot

Questions This Section Answers

• How differently do top-three and rank-one rates distribute across the leading brands?
• Why can similar top-three rates hide large differences in first-position recommendations?

Coverage shows whether a brand was recommended, while placement shows how prominently. Accenture led on both top-three and rank-one rates in October 2026, with a top-three rate of 50.7% and a rank-one rate of 43.4%. IBM Consulting and ScienceSoft followed on top-three rate at 35.5% and 20.9% respectively, but their rank-one rates were notably different at 2.8% and 8.5%.

Close coverage can still hide very different first-position rates, as IBM Consulting and ScienceSoft show near-identical top-three rates but rank-one rates that differ by several points.

Buyer-Intent Distribution

Questions This Section Answers

• Which buyer-intent classes are represented in the qualified observations?
• Why do pricing and multi-brand comparison questions contribute zero qualified observations?

All qualified observations in October 2026 fell into the brand recommendation class, continuing the pattern from September 2026. The current public series measures that class of discovery and does not yet contain qualified observations in the other classes.

This single-class concentration reflects the current prompt set's design rather than any measured shift in buyer-intent coverage.

Historical Measurement Record

Evidence and Source Layer

The benchmark is built from prompt-level observations that retain the query, the AI or search surface, the answer, the brand outcome, the recommendation placement, the sentiment, and where exposed, citations or attributable evidence sources. Source presence is evidence about the information environment. It is not automatically proof that the source caused the recommendation.

Scope Boundaries

• This benchmark does not measure market share, revenue, or any commercial outcome.
• It does not measure attributable sales or conversions from AI recommendations.
• It does not capture every possible AI response, only the qualified observations described above.
• It does not measure organic-search ranking, social mention volume, or private or sponsored channels.
• It does not establish causality from any metric movement on its own.

Top 10 Cited Domains

Questions This Section Answers

• Which domains are cited most often across AI platform responses?
• How concentrated is citation volume across the top ten domains?
• Did any tracked brand's own domain appear among the most-cited sources?

Across all AI platform responses in this measurement period, 6,052 citations were observed across 1,947 unique domains. The table below lists the ten most-cited domains.

Citations are broadly distributed: the top ten domains together account for only 16.6% of all citations, and the remaining 1,937 unique domains carry the rest. One tracked brand's own domain appears in the top ten: simform.com at rank nine with 62 citations. Review and directory sites and professional platforms feature prominently in the top three, with clutch.co and linkedin.com leading citation volume.

About This Benchmark

The LLM Authority Index AI Visibility Market Discovery Index measures how brands appear and are recommended across the major AI and search surfaces. It tracks prompt-level observations across six canonical surface families and reports presence, recommendation coverage, placement, and sentiment as distinct signals.

• AI Visibility Market Discovery Methodology
• AI Visibility Market Discovery Metric Definitions
• AI Visibility Market Discovery Research Standards
• Modeled AI Visibility Authority Value

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