IBM Consulting AI Market Strategy Report - SIEM Software

Answer Capsule

IBM Consulting does not appear anywhere in the September 2026 LLM Authority Index SIEM Software benchmark, which tracked nine SIEM platform brands across six AI and search surface families. The benchmark's qualified observation set of 379 responses contains no mentions, no valid recommendations, and no rank placements for IBM Consulting. The clearest opportunity sits with its affiliated platform, IBM QRadar, which holds the second-highest valid recommendation coverage in the category at 14.5% but converts that presence into top-three placement only 4.8% of the time. The gap between QRadar's visibility and its recommendation conversion is the most actionable signal available for an IBM-affiliated services positioning play.

Who This Report Is For

This report is written for IBM Consulting's SIEM and security services leadership, category marketers, and alliance teams who need to understand how AI systems currently frame the SIEM software category and where an IBM-affiliated services brand is absent from the recommendation layer.

Report Card

Executive Summary

IBM Consulting is absent from the September 2026 SIEM Software benchmark. Across 379 qualified observations and six AI and search surface families, the dataset recorded zero mentions, zero valid recommendations, zero top-three placements, and zero rank-one placements for IBM Consulting. This is not a weak showing. It is a complete absence from the recommendation layer of the category.

The benchmark's tracked company universe consists of nine SIEM platform vendors, not services firms. IBM QRadar is the only IBM-affiliated brand in the set, and it carries the second-highest valid recommendation coverage in the category at 14.5%, behind only Splunk at 31.9%. IBM QRadar also holds a 52.0% raw mention presence rate, the second-highest in the benchmark, meaning AI systems surface the platform in more than half of all qualified responses.

The gap for IBM QRadar is not visibility. It is recommendation conversion. IBM QRadar's top-three rate sits at 4.8%, down from 10.4% in July 2026, a 5.6-point decline. Its rank-one rate is 0.0%, meaning no qualified observation placed IBM QRadar as the single first recommendation. The platform is mentioned frequently but rarely shortlisted at the top of the list.

The strongest cluster in the benchmark is Best SIEM Software Evaluation, which absorbed all 379 qualified observations. The SIEM Software Comparisons and SIEM Software Pricing and Cost clusters produced zero qualified observations in September 2026, so the benchmark cannot yet show how AI systems handle head-to-head comparisons or pricing and value questions in this category.

Splunk remains the category leader at 31.9% valid recommendation coverage, though it declined 10.1 points from 42.0% in August 2026. Elastic Security is the strongest challenger by coverage at 17.4%, and it holds the highest net sentiment score among the top three brands at 0.6803. IBM QRadar's net sentiment score is 0.4721, the lowest among the top five brands by coverage.

The clearest opportunity for an IBM-affiliated services positioning play is to close the gap between QRadar's high visibility and its low top-three conversion rate. That gap represents the difference between being named in an AI response and being named as a recommended option. For IBM Consulting, the strategic question is whether a services layer can be introduced into the recommendation set at all, given that the current benchmark tracks platforms rather than implementation partners.

What IBM Consulting Is Winning

IBM Consulting does not appear in the September 2026 SIEM Software benchmark. The dataset contains no mentions, no valid recommendations, no top-three placements, and no rank-one placements for IBM Consulting across any of the six tracked AI and search surface families.

There are no evidence-backed wins to report for IBM Consulting in this benchmark. The company is not part of the tracked company universe, and no prompt in the qualified observation set surfaced IBM Consulting as a brand, a recommendation, or a reference.

The closest adjacent signal belongs to IBM QRadar, which is a separate brand in the tracked set. IBM QRadar holds the second-highest valid recommendation coverage at 14.5% and the second-highest raw mention presence rate at 52.0%. Those are platform-level metrics, not services-level metrics, and they should not be attributed to IBM Consulting.

Where IBM Consulting Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why does IBM Consulting not appear in AI SIEM recommendations even though IBM QRadar does?
• What prompt types would need to exist for a services brand like IBM Consulting to surface in SIEM recommendations?

IBM Consulting has no AI visibility in the September 2026 SIEM Software benchmark. The gap is total absence, not underperformance. Across 379 qualified observations, the dataset recorded zero mentions of IBM Consulting on ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.

The benchmark's tracked company universe is composed entirely of SIEM platform vendors. IBM Consulting is a services firm, and the current prompt set does not appear to ask questions that would surface a services brand. All 379 qualified observations fell into the Best SIEM Software Evaluation cluster, which captures direct asks for the best or a recommended SIEM solution. None fell into comparison or pricing clusters, which are the prompt types most likely to surface implementation partners, managed security providers, or consulting firms.

The clearest displacement signal in the benchmark belongs to IBM QRadar, which lost 5.6 points of top-three rate between July 2026 and September 2026 while gaining 6.4 points of raw mention presence. IBM QRadar is being mentioned more often but recommended in the top three far less often. Splunk, Elastic Security, and Google Chronicle all hold higher top-three rates than IBM QRadar despite lower or comparable presence rates. Splunk converts 92.6% presence into a 24.5% top-three rate. IBM QRadar converts 52.0% presence into a 4.8% top-three rate.

For IBM Consulting, the gap is structural. The benchmark does not currently measure services-layer recommendations in the SIEM category. That means the absence is not evidence that AI systems would refuse to recommend IBM Consulting if asked. It is evidence that the current prompt set does not ask.

Biggest Opportunity

Questions This Section Answers

• Which uncovered prompt clusters could open a services-layer presence for IBM Consulting in SIEM recommendations?
• Could closing IBM QRadar's recommendation conversion gap help IBM Consulting enter the same AI answers?

The single biggest opportunity for IBM Consulting is to establish a services-layer presence in the SIEM recommendation set by targeting the prompt types that the current benchmark does not yet cover. The benchmark's Pricing and Value and Multi-Brand Comparison clusters produced zero qualified observations in September 2026, which means AI systems are not yet being asked to compare SIEM options head-to-head or to evaluate pricing and value in this category at scale.

Those are the prompt types where a services brand becomes relevant. A buyer asking which SIEM platform offers the best value, or which vendor is easiest to implement, or which SIEM deployment partner is most recommended, is asking a question that a platform-only benchmark cannot answer. IBM Consulting's opportunity is to build the owned answer layer and citation architecture that makes it retrievable when those questions start appearing in AI responses.

The adjacent opportunity is to support IBM QRadar's recommendation conversion. IBM QRadar holds 14.5% valid recommendation coverage but only 4.8% top-three rate and 0.0% rank-one rate. If IBM Consulting can produce the implementation guides, deployment comparisons, and managed services content that AI systems retrieve when framing QRadar recommendations, the services brand and the platform brand can reinforce each other in the same answer.

Competitive Landscape

Questions This Section Answers

• Where does IBM QRadar rank against Splunk, Elastic Security, and Google Chronicle in top-three placement and sentiment?
• How does IBM QRadar's 0.0% rank-one rate compare with competitors like Splunk and Exabeam?

Splunk holds dominant recommendation-stage strength in the SIEM Software category at 31.9% valid recommendation coverage, though its lead narrowed significantly in September 2026. Elastic Security is the strongest challenger by coverage at 17.4%, and IBM QRadar sits third at 14.5%. IBM Consulting does not appear in the tracked set.

Average recommended rank covers rank-eligible recommendations only.

IBM QRadar ranks third by top-three rate but holds the lowest net sentiment score among the top five brands by coverage. Its rank-one rate is 0.0%, meaning no qualified observation placed it as the single first recommendation. The platform is visible and frequently mentioned, but it is not being chosen at the top of the list.

Prompt Evidence

ChatGPT / Best SIEM Software Evaluation Prompt: "best cloud siem" Result: IBM QRadar appeared in the response but was not placed in the top three recommended options.

Google AI Overviews / Best SIEM Software Evaluation Prompt: "siem tools" Result: IBM QRadar was mentioned with positive framing but did not convert into a top-three recommendation placement.

Google AI Mode / Best SIEM Software Evaluation Prompt: "What are the big 5 cybersecurity companies?" Result: IBM QRadar appeared as a reference in the response, contributing to its 52.0% raw mention presence rate without a corresponding top-three placement.

Perplexity / Best SIEM Software Evaluation Prompt: "siem company" Result: IBM QRadar received a valid recommendation but no rank-one placement, consistent with its 0.0% rank-one rate across the benchmark.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map the full prompt surface for SIEM software and adjacent security services queries to identify where IBM Consulting and IBM QRadar appear, where they are absent, and which competitors capture the recommendation when an IBM-affiliated brand is mentioned but not chosen.

Phase 2: Recommendation Readiness Plan Define the specific prompt clusters, answer formats, and evidence types that would move IBM QRadar from a mention into a top-three recommendation, and identify the services-layer prompts where IBM Consulting could enter the recommendation set.

Phase 3: Owned Answer Layer Buildout Build the deployment guides, implementation comparisons, managed services explainers, and evaluation frameworks that AI systems can retrieve when framing SIEM recommendations and services-layer answers.

Phase 4: Citation / Authority Layer Development Develop the public evidence layer, including analyst references, customer proof points, technical documentation, and third-party validation, that supports retrievability and framing quality across ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track IBM Consulting and IBM QRadar recommendation coverage, top-three rate, rank-one rate, and sentiment month over month against the LLM Authority Index benchmark to measure whether the services-layer and platform-layer strategies are converting visibility into recommendation placement.

Why This Matters

Questions This Section Answers

• What is the difference between being mentioned in AI SIEM responses and being shortlisted in the top three?
• How does IBM QRadar's mention-to-shortlist conversion compare with Splunk's?

AI systems are forming buyer shortlists before a buyer ever visits a vendor page. In the September 2026 SIEM Software benchmark, Splunk was mentioned in 92.6% of qualified responses and recommended in the top three in 24.5% of them. IBM QRadar was mentioned in 52.0% of responses but recommended in the top three in only 4.8%. The difference between those two conversion rates is the difference between being part of the conversation and being part of the shortlist.

For IBM Consulting, the stakes are structural. The current benchmark does not measure services-layer recommendations in the SIEM category, which means the absence is a measurement gap as much as a visibility gap. But measurement gaps close. As buyers begin asking AI systems which SIEM partner to work with, which deployment approach is most reliable, or which managed security provider is most recommended, the brands with an established owned answer layer and citation architecture will be the ones that appear. Building that layer now is the difference between shaping the recommendation set and reacting to it.

Core Metrics

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

IBM Consulting has no mentions in the September 2026 SIEM Software benchmark, so no sentiment score can be calculated. The absence of a score is not the same as a neutral score. A neutral score would mean the brand was mentioned without positive or negative framing. No score means the brand was not mentioned at all.

This distinction matters because unclassified mention counts are misleading. A brand that appears in 50 responses as a neutral reference and a brand that appears in 50 responses as a top recommendation are not in the same position. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal. Counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, and for IBM Consulting, there is no visibility to classify in this benchmark.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of the September 2026 LLM Authority Index AI Market Discovery Index for SIEM Software, interpreted for IBM Consulting.
2. The reporting window is September 2026, with comparison data from July 2026 and August 2026 where available.
3. Six AI and search surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.
4. The September 2026 run began with 793 prompt-surface observations and 603 unique questions, producing 379 qualified benchmark observations after qualification.
5. The tracked company universe consists of nine SIEM platform vendors: Splunk, Elastic Security, IBM QRadar, Rapid7 InsightIDR, Securonix, Exabeam, Google Chronicle, Sumo Logic, and Microsoft SharePoint. IBM Consulting is not part of the tracked universe.
6. All 379 qualified observations fell into the Best SIEM Software Evaluation cluster. The SIEM Software Comparisons and SIEM Software Pricing and Cost clusters produced zero qualified observations in September 2026.
7. Stage 0 extraction retained the query, AI or search surface, answer, brand outcome, recommendation placement, sentiment, and citations where exposed.
8. A mention is counted when a tracked brand appears anywhere in a qualified AI response, regardless of framing or placement.
9. A valid recommendation is counted when a tracked brand receives a clear, actionable recommendation in a qualified response. Mentions that are neutral, cautionary, or listed only are not counted as valid recommendations.
10. Top-three rate is the share of qualified observations in which a brand appears among the top three recommended options. Rank-one rate is the share in which a brand is the single first recommendation.
11. Average recommended rank covers rank-eligible recommendations only. A brand with no rank-eligible recommendations receives N/A.
12. The public benchmark does not measure market share, attributable sales, every possible AI response, organic search ranking, social mention volume, or private and sponsored channels. A metric movement alone does not establish causality.
13. IBM Consulting does not appear in the September 2026 benchmark. All IBM Consulting metrics in this report are zero or N/A. IBM QRadar metrics are reported separately and should not be attributed to IBM Consulting.
14. Microsoft Sentinel appeared in the August 2026 brand set at 35.6% valid recommendation coverage but was not tracked in the September 2026 set. This is a roster change, not a like-for-like comparison.

See Where Your Brand Stands in AI Recommendations

The LLM Authority Index benchmark shows where the SIEM Software category stands. A company-level AI visibility audit shows where IBM Consulting and IBM QRadar appear in AI-generated recommendations, which prompts they win, which competitors capture the recommendation when they are mentioned but not chosen, and which public sources shape the answers. That is the difference between knowing the category and knowing your position in it.