IBM · AI Citation Intelligence Dashboard
IBM in AI Answers
How AI platforms position IBM when enterprises evaluate AI solutions
Executive Summary
IBM achieves 60.5% organic discovery—appearing in 121 of 200 unbranded tests when enterprises research AI platforms. IBM ranks #4 in featured recommendations among hyperscalers (16.5% vs. Microsoft 20.5%, AWS 19.5%, Google 17%)—but #1 among non-hyperscaler advisors, beating McKinsey (7.5%) and Accenture (2.5%) by wide margins. Strongest categories: Hybrid Cloud (80%), AI Governance (78%), and Enterprise Platform (67%). Key opportunity area: Developer/Technical queries (34%) where AWS and Google dominate. watsonx penetration remains low—appearing in only 1.5% of unbranded responses despite 56% in branded queries, indicating the platform brand has not achieved organic recall.
Organic Discovery
60.5%
Unbranded query performance
IBM appeared in 121 of 200 unbranded tests across all platforms. This measures organic visibility when enterprises search without naming IBM specifically.
Featured Company Rank
#4 / #1
Hyperscalers / Non-hyperscalers
IBM is the featured (primary recommendation) company in 33 of 200 unbranded responses (16.5%). Ranks #4 among hyperscalers but #1 among non-hyperscaler advisors—2× ahead of McKinsey, 6× ahead of Accenture.
Brand Accuracy
100%
Branded query performance
When users explicitly search for "IBM" or "IBM watsonx," AI platforms correctly provide information 50 of 50 times across all platforms.
watsonx Penetration
1.5%
In unbranded queries (3/200)
48%
In branded queries (24/50)
Query Performance by Category
Where IBM appears (and doesn't) in AI responses
Based on 40 unbranded queries across 5 strategic categories reflecting enterprise buyer research patterns.
Category 01
Hybrid Cloud
80%
"Best hybrid cloud architectures for enterprise AI workloads"
Category 02
AI Governance & Trust
78%
"Best AI governance platforms for enterprises managing model risk"
Category 03
Enterprise Platform
67%
"What are the best enterprise AI platforms for large companies?"
Category 04
Emerging / Agentic AI
52%
"Best platforms for building enterprise-ready AI agents"
Category 05
Developer & Technical
34%
"Which cloud platform is best for enterprise machine learning development?"
Category 06
Branded Validation
94%
"What is IBM's role in the enterprise AI market today?"
Strategic Insight
IBM's strongest positioning aligns with its differentiated messaging: hybrid cloud infrastructure and AI governance/trust. The developer/technical gap (34%) reflects AWS and Google's traditional developer mindshare—this is a known competitive reality rather than a new finding. The question for IBM: is developer visibility a priority, or is enterprise buyer capture sufficient?
Source Intelligence
Which sources correlate with IBM wins?
Outcome-based analysis: when each source is cited, who gets featured as the primary recommendation? Baseline: IBM is featured in 16.5% of unbranded queries overall.
AR Targeting Intelligence
When analyst firms are cited, IBM outperforms baseline at Gartner (27%) and Forrester (29%). IDC represents an opportunity gap—IBM wins only 15% vs. AWS/Google at 23% each.
Source
Responses
IBM Wins
Top Competitor
vs. 16.5%
forrester.com
24
29%
Google 25%
+12.5pp
gartner.com
48
27%
Google 19%
+10.5pp
idc.com
13
15%
AWS 23%
−1.5pp
AR Strategy Implication
IBM's Gartner and Forrester relationships are driving favorable AI platform outcomes—these analyst citations correlate with IBM being featured 27-29% of the time, well above the 16.5% baseline. IDC is the primary opportunity: high citation volume (13 responses) but IBM wins at only 15% vs. AWS/Google at 23%. Consider whether IDC briefing cadence or content emphasis differs from Gartner/Forrester approach.
Partnership & Thought Leadership
Consulting firm citations show mixed IBM outcomes. Accenture (21% IBM wins) reflects the partnership relationship. BCG is a significant gap—Microsoft wins 38% when BCG is cited, IBM wins 0%.
Source
Responses
IBM Wins
Top Competitor
vs. 16.5%
kpmg.com
2
50%
—
+33.5pp
accenture.com
14
21%
Others <5%
+4.5pp
mckinsey.com
28
14%
MSFT 11%
−2.5pp
deloitte.com
17
6%
MSFT/AWS 12%
−10.5pp
pwc.com
5
0%
MSFT 20%
−16.5pp
bcg.com
8
0%
MSFT 38%
−16.5pp
Consulting Landscape
Accenture partnership value is visible—IBM wins 21% when Accenture is cited, with no competitor above 5%. In contrast, BCG citations correlate with Microsoft wins (38%) while IBM wins 0%. This may reflect BCG's AI practice positioning or case study portfolio. Deloitte and PwC also show Microsoft advantage. Consider whether joint thought leadership with these firms could shift citation outcomes.
PR Targeting Intelligence
Earned media shows limited citation volume but meaningful outcome variation. CRN and Forbes are strengths where IBM outperforms baseline. AI Magazine and Towards Data Science are gaps where competitors dominate.
Strengths (above 16.5% baseline)
Source
Responses
IBM Wins
Top Competitor
vs. 16.5%
zdnet.com
2
100%
—
+83.5pp
crn.com
5
40%
MSFT 40%
+23.5pp
techcrunch.com
3
33%
MSFT/Goog 33%
+16.5pp
forbes.com
11
18%
MSFT 9%
+1.5pp
Opportunities (at or below 16.5% baseline)
Source
Responses
IBM Wins
Top Competitor
vs. 16.5%
hbr.org
7
14%
MSFT/AWS 14%
−2.5pp
technologyreview.com
2
0%
Spread
−16.5pp
aimagazine.com
6
0%
MSFT 33%
−16.5pp
towardsdatascience.com
4
0%
AWS 50%
−16.5pp
PR Priority Targets
Forbes (11 responses, 18% IBM wins) is the highest-volume strength—double Microsoft's rate. AI Magazine and Towards Data Science are gaps where competitors dominate. Note the developer publication pattern: Towards Data Science shows AWS at 50%, IBM at 0%—consistent with IBM's developer category gap. For earned media ROI, prioritize outlets where IBM already shows favorable outcomes while building presence in gap publications.
Government & Standards Engagement
Policy and standards citations show IBM strength in government sources (NIST 33%, ai.gov 50%). World Economic Forum is the largest gap—9 responses but only 11% IBM wins.
Strengths (above 16.5% baseline)
Source
Responses
IBM Wins
Top Competitor
vs. 16.5%
ai.gov
2
50%
—
+33.5pp
nist.gov
6
33%
Others 0%
+16.5pp
oecd.org
6
33%
MSFT 17%
+16.5pp
partnershiponai.org
3
33%
Others 0%
+16.5pp
brookings.edu
6
17%
MSFT 17%
+0.5pp
Opportunities (at or below 16.5% baseline)
Source
Responses
IBM Wins
Top Competitor
vs. 16.5%
weforum.org
9
11%
Spread low
−5.5pp
ieee.org
2
0%
MSFT 50%
−16.5pp
Policy Engagement ROI
Government sources (NIST, OECD, ai.gov) show strong IBM outcomes—when these sources are cited, IBM wins 33-50% of the time, well above baseline. This validates IBM's AI governance and responsible AI positioning. WEF is the primary opportunity: highest citation volume (9 responses) in this category but only 11% IBM wins. Given IBM's WEF membership and AI governance leadership, this gap may reflect content contribution strategy rather than relationship.
Methodology: Outcome-Based Source Analysis
This analysis measures who wins when each source is cited—not co-occurrence. "Responses" = number of AI responses (out of 250 total) that cited this source. "IBM Wins" = percentage of those responses where IBM was the featured/primary recommendation. Baseline: IBM is featured in 16.5% of all unbranded queries. Green = above baseline (strength); Yellow = below baseline (opportunity). Data from 250 tests across 5 AI platforms, December 2025.
Competitive Intelligence
How IBM compares to enterprise AI competitors
Based on unbranded queries only—measuring organic competitive positioning when no specific vendor is named.
Featured Company Rankings (Primary Recommendations)
Consolidated to brand level; excludes pure-play ML tools (H2O.ai, DataRobot, Databricks)
Microsoft Hyperscaler
41
AWS Hyperscaler
39
Google Hyperscaler
34
IBM SUBJECT
33
McKinsey Consultant
15
OpenAI AI Lab
8
Accenture Consultant
5
Mention Frequency (Appearing in Response)
All mentions in unbranded queries; excludes pure-play ML tools
Microsoft Hyperscaler
165
Google Hyperscaler
155
AWS Hyperscaler
129
IBM SUBJECT
121
McKinsey Consultant
26
OpenAI AI Lab
22
Accenture Consultant
16
Key Competitive Insight
IBM occupies a unique position—competitive with hyperscalers (#4 at 16.5% featured vs. 17-20.5%) while decisively leading non-hyperscaler advisors (33 featured vs. McKinsey's 15 and Accenture's 5). This reflects IBM's dual identity as both a technology platform vendor and enterprise transformation partner. When AI platforms recommend "who should help with AI strategy," IBM is chosen 2× more often than McKinsey and 6× more often than Accenture.
Platform Performance
IBM visibility across AI platforms
Unbranded query mention rates by platform. Significant variation (20%-85%) suggests platform-specific optimization opportunities.
Meta Llama
85%
34 of 40 tests
Strong
ChatGPT
73%
29 of 40 tests
Strong
Claude
68%
27 of 40 tests
Strong
Gemini
58%
23 of 40 tests
Moderate
Search-Native
Perplexity
20%
8 of 40 tests
Opportunity
Search-Native
Platform Variation Analysis
The 65-point gap between Meta Llama (85%) and Perplexity (20%) is substantial. Perplexity's search-native architecture prioritizes real-time web results over training data associations—IBM's lower visibility there may reflect indexing patterns or content freshness rather than brand perception. The consistently strong performance on ChatGPT, Claude, and Meta Llama (68-85%) suggests IBM has solid representation in model training data.
Product Brand Analysis
watsonx penetration in AI responses
When IBM is mentioned, how often is watsonx specifically cited? This reveals whether IBM's flagship AI platform brand has achieved organic recall.
watsonx Mention Rates
Branded Queries
48%
24 of 50 tests
Unbranded Queries
1.5%
3 of 200 tests
Gap
46.5pp
Percentage point difference
watsonx by Category (All Tests)
| Category | watsonx Rate | Tests |
|---|---|---|
| Branded Validation | 56.0% | 28/50 |
| AI Governance & Trust | 2.5% | 1/40 |
| Developer & Technical | 2.0% | 1/50 |
| Enterprise Platform | 1.7% | 1/60 |
| Hybrid Cloud | 0% | 0/25 |
| Emerging / Agentic | 0% | 0/25 |
watsonx Brand Transition Challenge
watsonx has not achieved organic recall. While AI platforms correctly reference watsonx when users explicitly ask about IBM (48% branded rate), the platform brand virtually disappears in competitive contexts (1.5% unbranded rate). This suggests AI models still associate "enterprise AI" with legacy IBM or general IBM capabilities rather than the watsonx platform specifically. As Jonathan Adashek has noted, IBM faces ongoing perception challenges—this data confirms the brand transition work remains incomplete in AI-mediated discovery.
Query Appendix
Complete test results
All 250 tests with filtering and search. Click column headers to sort.
Showing 250 of 250
| Query | Type | Category | Platform | IBM | watsonx | Featured |
|---|
Methodology
Study parameters & limitations
Study Parameters
- 50 unique queries × 5 platforms = 250 tests
- 10 branded queries (20%) for quality validation
- 40 unbranded queries (80%) for competitive testing
- 5 AI platforms: ChatGPT, Claude, Perplexity, Gemini, Meta Llama
- Analysis date: December 5, 2025
- Total citations analyzed: 2,116 across 568 unique domains
Query Design Philosophy
Queries are persona-modeled to reflect how actual enterprise buyers phrase decision research:
- CIO/CTO evaluating multi-year platform investments
- ML Engineers and Data Scientists selecting tooling
- CISO/Compliance Officers managing AI risk
- Enterprise Architects designing hybrid infrastructure
The query set deliberately tests beyond IBM's positioning strengths to reveal honest competitive gaps—not to validate existing messaging.
Limitations
- Single snapshot in time (December 2025)—AI responses change
- Sample size appropriate for directional insights, not statistical certainty
- Query phrasing influences results—different wording may yield different outcomes
- Platform algorithms are opaque and evolving
- Citation extraction varies by platform (Perplexity/Gemini provide structured citations; others require parsing)
- "Featured company" is interpretive—based on prominence in response
- watsonx detection may miss variant spellings or partial references
- Does not capture visual/image-based AI responses
- Enterprise buyers may use different terminology than tested queries
Recommended Follow-Up
- Industry-specific deep dives: Financial Services, Healthcare, Government—where IBM has vertical strength
- Competitor head-to-head: IBM vs. Microsoft Azure AI, IBM vs. AWS specifically
- Temporal tracking: Repeat quarterly to measure trend
- Content gap analysis: What content would need to exist to improve Developer/Technical category?
- watsonx brand lift: Test whether specific watsonx campaigns improve organic recall
- Perplexity optimization: Investigate why search-native platform shows significantly lower IBM visibility