How AI Search Is Recommending Information Technology and Digital Transformation Services: Monthly Trends

Executive Summary

The benchmark's coverage leader in September 2026 remained Accenture, with valid recommendation coverage of 41.3%, but the gap to the next brand narrowed substantially. IBM Consulting held second place at 37.4%, a spread of just 3.9 points, down from an 8.0-point gap between Accenture and Deloitte, then in second place, in July 2026. This month's movement is significant because all three major consultancies at the top declined from their July baseline, yet no brand rose to challenge them.

Accenture continues to lead despite a significant decline of 6.7 points from its July baseline of 48.0%. Its September 2026 coverage of 41.3% remains the strongest in the vertical, supported by 242 valid recommendations across 586 observations and a top-three rate of 38.2%. The two-month downward streak signals that its previously dominant position in AI-generated recommendation sets is being redistributed across the category.

The sharpest notable movement came from Cognizant, which fell 8.2 points from 32.3% in July to 24.1% in September, a significant decline driven almost entirely by an 8.0-point drop in August. Deloitte also declined significantly, down 5.7 points from 40.0% to 34.3%, while IBM Consulting remained effectively stable at 37.4%, down just 0.7 points from its July level of 38.1%.

Against the prior month, September 2026 showed no individual brand exceeding normal month-to-month variation, yet the cumulative baseline-to-current movement is significant for Accenture, Cognizant, and Deloitte. What the category demonstrates is not a single dominant shift but a broad repositioning in which three leading consultancies saw AI systems recommend them less often while IBM Consulting held its ground.

Each monthly run begins with 800 prompt-surface observations (560 unique questions in September, 584 in August, 525 in July across the July baseline) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor; 626 were relevant and 174 were irrelevant in September (615 and 185 in August, 551 and 249 in July). The public metrics use the 586 qualified observations in September (576 in August, 527 in July) that survive both qualification stages.

Key Findings

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

The benchmark universe held steady at 800 source prompts in both July and September, while the share of prompts surviving qualification rose from 527 to 586 as relevance improved. August 2026 sat between the two at 576 qualified observations, meaning the qualified set has grown for three consecutive months even as the raw collection size stayed constant.

Benchmark-Level Metrics

The valid recommendation shortlist share fell from 48.6% in July to 41.3% in September, a contraction of 7.3 points. That decline is the backdrop to the brand-level movements: AI systems produced proportionally fewer valid recommendation shortlists in the current month, meaning the consultancies competed within a smaller recommendation pool.

AI Recommendation Trend

Three significant declines within a stable two-tier structure

The commercial situation is a narrowing at the top. Accenture remains the category leader at 41.3% but is no longer separated from the field by a wide margin, and the three significant decliners in the vertical are all among the top consultancies.

The observed category-level change came from the combination of several smaller to moderate movements rather than one dominant shift. Accenture, Deloitte, and Cognizant each showed significant baseline-to-current declines, while IBM Consulting, Capgemini, CDW UK, and the three brands with no coverage moved within normal variation.

What Changed This Month

Accenture: Leader declines significantly but retains first place

Accenture's valid recommendation coverage fell from 48.0% in July to 41.3% in September, a drop of 6.7 points that stands out against the vertical's typical month-to-month movement. The decline has been steady across two months, down 3.0 points in August and a further 3.7 points in September.

The erosion shows in placement quality. Accenture's top-three rate fell 8.3 points from 46.5% to 38.2%, and its rank-one rate dropped 7.1 points from 40.6% to 33.5% over the same period. Despite that, Accenture still produced 196 rank-one recommendations in September, far more than any other brand in the vertical; the next closest, IBM Consulting, recorded 9.

Accenture was mentioned in 99.2% of qualified observations in both July and September. The brand remains nearly universally present in AI answers, but the rate at which those mentions convert into top recommendations has weakened across the three-month series.

Highest-priority diagnostic: Which specific high-intent prompts shifted Accenture out of the top recommendation slot, and which brand is capturing those positions when Accenture loses?

Deloitte: Significant decline in top placement despite rising presence

Deloitte's valid recommendation coverage fell 5.7 points from 40.0% in July to 34.3% in September, a significant decline. The drop concentrated in the most recent month, with coverage falling from 38.9% in August to 34.3% in September, a move of 4.6 points within that single month.

The placement story is sharper than the headline coverage figure. Deloitte's top-three rate dropped 6.7 points from 32.3% to 25.6%, while its rank-one rate fell 2.9 points from 3.8% to 0.9%.

Notably, Deloitte's raw mention presence rose from 77.8% to 81.9% over the same period. The brand is being surfaced and described more often, but AI systems are recommending it in top positions substantially less.

Highest-priority diagnostic: Which evidence sources or prompt contexts keep Deloitte visible and positively described but push it out of the top recommendation position?

Cognizant: The largest baseline decline, concentrated in August

Cognizant entered the series at 32.3% valid recommendation coverage in July and exited September at 24.1%, a decline of 8.2 points, the largest in the vertical over this period. The movement was not gradual: coverage fell 8.0 points between July and August, then held nearly flat with a further 0.2-point decline in September.

Unlike Deloitte, Cognizant's loss was not primarily a placement problem. Its top-three rate fell only 0.5 points from 6.5% to 6.0%, and its rank-one rate actually improved from 0.2% to 0.5%. The decline came from a reduction in the total number of valid recommendations, which fell from 170 in July to 141 in September.

The gap between CDW UK and Cognizant narrowed from 32.1 points in July to 23.8 points in September, a narrowing driven by Cognizant's decline rather than any rise in CDW UK's coverage, which stood at just 0.3% in September.

Highest-priority diagnostic: Which prompt categories stopped producing Cognizant recommendations between July and August, and do those prompts represent a shift in how AI systems frame the vendor landscape?

IBM Consulting: The stable counterweight

IBM Consulting is the only member of the top tier that did not decline significantly, with coverage of 37.4% in September versus 38.1% in July, a movement of just 0.7 points that sits well within normal variation. IBM Consulting's presence rose strongly from 66.2% to 76.4% over the series, a 10.2-point increase.

The result is a repositioning at the top: IBM Consulting began the series nearly 10 points behind Accenture and ended it just 3.9 points back, while passing Deloitte to claim the second position. IBM Consulting's top-three rate of 27.3% and rank-one rate of 1.5% both improved modestly from July.

IBM Consulting's stability is distinct from Accenture's, Deloitte's, and Cognizant's declines in that its gains in raw presence did not translate into a coverage increase, but they also did not come with a coverage penalty as seen elsewhere.

Highest-priority diagnostic: Which surfaces or prompt types account for IBM Consulting's large increase in presence without an equivalent rise in top recommendations?

Buyer-Intent Interpretation

The qualified observations for this vertical all fell into the Brand Recommendation class in the current month. The public benchmark could not answer price, value, or head-to-head comparison questions because no observations survived into the Pricing & Value or Multi-Brand Comparison classes. Buyers asking AI systems to compare or price information technology and digital transformation providers are operating outside what the public metrics can currently characterize.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Market Discovery research program.

• AI Industry Market Discovery
• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• Small-count movement: CDW UK's 0.1-point rise reflects just 2 valid recommendations in September, within normal variation. Brands with zero coverage across the series should be read as absent, not unsuccessful.
• Qualified denominator vs raw collection: Brand percentages are calculated against 586 qualified observations, not the 800 prompts collected.
• Directional analysis: Baseline-to-current movement identifies changes worth investigating, not their causes.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

Beneath the aggregate percentages sit the questions that define competitive position: which high-intent prompts is Accenture still winning, which competitor takes the recommendation when Deloitte or Cognizant loses, what attributes does the AI associate with IBM Consulting's rising presence, and which external sources are shaping those answers. The public benchmark cannot answer those questions from aggregate coverage alone.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It isolates the specific contexts where a brand gains or loses AI recommendation authority.

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