← back to rankingIT · Gartner, Inc.
Consulting Services · mkt cap $11.4B · calls: Q1 FY2026 vs Q4 FY2025
27.0 conviction · conf-adj 27
conf 2/10 1-model
enthusiasm:21.0 · trend:-5 · quantifies:0 · impact:0 · under_radar:14 · credibility:0 · business_impact:8 · disruption:-14 · commitment:0 · confirmation:3
Enthusiasm latest 7 / prev 8 (falling)
Gartner's AI thesis runs on two rails simultaneously: demand-side (AI is the single highest-requested client topic, driving subscription volumes, inquiry activity, and conference attendance) and supply-side (AI is deployed internally via neural-network topic modeling, AskGartner's personalization engine, content-production automation, and sales role-play tools to produce more insights faster and raise salesperson effectiveness). The clearest financial signal is AskGartner's 'substantially higher renewal rates' among users—a direct topline retention indicator—and the 75% cut in Magic Quadrant creation time—a direct bottomline productivity signal—but neither is given a dollar or basis-point magnitude, which limits investment-grade credibility. Management's explicit rejection of third-party LLM content distribution, combined with its defensive posture on AI substitution risk, reflects a coherent but not yet financially proven bet that bespoke proactive advisory is durable against generative AI commoditization.
GROUNDED NEXT-FY IMPACT vs CONSENSUS
Grounded on actual base — revenue $6.5B · net income $0.7B · net margin 11.2% · diluted EPS 9.65
These are next-fiscal-year annual uplift estimates, not next-quarter numbers.
Aggregate next-FY est. rev uplift: % · next-FY EPS uplift: % · vs analysts: unclear · priced in: low (model's call-read: medium; verdict above is the hard-data one used for ranking) · confidence: 2/10
| Claim | Figure | Arithmetic | Next-FY Rev % | Next-FY EPS % |
|---|
AskGartner answered >500k AI questions (FY25)
engagement · soft | >500,000 questions | Usage count only; no revenue-per-query or attach-rate disclosed. No base obtainable from inputs -> cannot dollarize. | | |
>200k in-depth AI client conversations (FY25)
engagement · soft | >200,000 | Activity count; not tied to a revenue line or pricing. No base obtainable. | | |
>6,000 AI documents in library (end-25)
other · soft | >6,000 docs | Content inventory stat; no revenue/cost base. | | |
>1,000 unique AI use cases documented
other · soft | >1,000 | Inventory stat; no monetizable base. | | |
75% cut in avg insight-creation time (Magic Quadrants), from Jul-25
productivity · soft | 75% | Real productivity gain, but NO insight-production cost/labor base disclosed anywhere in the claims. 75% of an unknown base = unknowable $ saving. Frees analyst capacity (capacity reinvested per mgmt, not banked) -> can't size after-tax saving. Anchored % with no obtainable base => soft. | | |
Active Insights library grew ~50%
other · soft | ~50% | Content-volume growth, not unit price or revenue; no mapping to a revenue line. | | |
AskGartner users had substantially higher renewal vs non-users
engagement · soft | substantially higher (magnitude not disclosed) | Most economically meaningful (retention drives CV/Research revenue), but mgmt gave NO bps. Cannot size retention->revenue with no number. Genuinely unanchored. | | |
Same-day event-driven docs more than doubled (Q1 FY26)
productivity · soft | >2x | Throughput/timeliness count; no revenue or cost base. | | |
High-impact documents +22% (Q1 FY26)
productivity · soft | 22% | Output-volume %; no $ base for the document-production line. | | |
Total insights library docs +19% (Q1 FY26)
productivity · soft | 19% | Output-volume %; no $ base; volume != revenue (Gartner sells seats/subscriptions, not per-document). | | |
Assumptions: EPS basis = consensus adjusted (FY25 adj NI $920.5M, adj EPS $12.78, adj margin 14.2%); GAAP NI $729.2M/11.2% noted but not used for EPS%. Tax 21%, incremental margin would be 14.2% (adj) if any revenue claim existed. Phasing: all figures are FY25 actuals or Q1-FY26 YoY volume comps — no forward $ AI guide given. Gartner is a research/advisory ADOPTER of AI (improves its own content production, engagement, retention); it sells no AI compute/silicon/capacity, so there is zero supplier-side revenue.
Top line: Unquantifiable from disclosure. Every AI metric is a usage/inventory/volume statistic (500k questions, 6,000 docs, +50%/+22%/+19% volume) with no revenue, price, or attach-rate attached. Gartner monetizes via subscription seats/CV, not per-document or per-query, so doc-count growth does not translate mechanically to revenue. The one item with real top-line leverage — AskGartner users renewing 'substantially higher' — was given with NO magnitude, so it cannot be sized. Consensus carries revenue essentially flat (FY26 -0.7% to $6.45B, FY27 +4.6% to $6.75B), implying analysts assume NO AI-driven top-line acceleration.
Bottom line: The 75% reduction in insight-creation time is a genuine cost/capacity gain, but Gartner discloses no production-cost or analyst-labor base anywhere in the quoted claims, so the dollar saving cannot be computed (75% of an unknown). Mgmt explicitly says freed capacity is REINVESTED into analysts and sellers, not dropped to the bottom line. Indirectly, consensus already shows the efficiency dividend: adj EPS grows +7.2% (FY26) and +12.5% (FY27) on flat revenue — that gap IS embedded margin expansion. No incremental, unpriced EPS uplift can be defensibly added.
[impact n/m (all claims soft/unanchored)] Consensus revenue flat (-0.7% FY26, +4.6% FY27) yet adj EPS +7.2%/+12.5% => analysts already model ~7-12% margin-driven earnings growth on a flat top line, which is precisely the 'AI frees resources / long-term margin expansion' thesis. The bottom-line AI benefit is therefore largely in the numbers. The top line is the open question: no analyst is modeling AI revenue acceleration, but Gartner also disclosed no number to prove they should — there is no quantified gap to exploit in either direction.
MODEL CONSENSUS (impact)
1-model degraded to opus only
other model unavailable: cursor: ```json
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"math": [
{
"claim": "500k+ AskGartner AI questions (FY25)",
"type": "engagement",
"side": "adopter",
"figure": ">500,000",
"basis": "Activity only; no in
QUANTIFICATIONS
AI-related questions answered via AskGartner: more than 500,000 (full year 2025, topline)
“we answered more than 500,000 AI-related questions through AskGartner”
In-depth client conversations on AI: more than 200,000 (full year 2025, topline)
“In 2025, we conducted more than 200,000 in-depth client conversations on AI”
AI-related documents in insights library: more than 6,000 (as of end of 2025, topline)
“We have more than 6,000 AI-related documents in our library”
Unique AI use cases documented: more than 1,000 (by end of 2025, topline)
“We've documented more than 1,000 unique use cases”
Reduction in average insight creation time (AI automation + process restructuring): 75% (versus 2024 baseline; effective from July 2025, bottomline)
“for insight types that are highly valued by our clients, such as Magic Quadrants, we reduced our average insight creation time by 75% compared to 2024”
Growth in Active Insights library (AI-enabled automation): approximately 50% (by end of 2025 versus prior period, topline)
“our Active Insights library has grown by approximately 50%”
AskGartner users renewal rate premium versus non-users (no precise bps given): substantially higher (magnitude not disclosed) (2025 renewal cohort, topline)
“Licensed users who use AskGartner had substantially higher renewal rates than those who did not even with the same levels of engagement”
Same-day event-driven insight documents (AI-enabled timeliness initiative): more than doubled (Q1 FY2026 versus prior year, topline)
“The number of these documents has more than doubled”
High-impact documents count increase (AI-assisted production): 22% (Q1 FY2026 versus prior year, topline)
“We've increased the number of high-impact documents by 22%”
Total insights library document count increase (AI-assisted production): 19% (Q1 FY2026 versus prior year, topline)
“The number of documents in our insights library is up 19%”
PAST (realized)
- In 2025, answered more than 500,000 AI-related questions through AskGartner and conducted more than 200,000 in-depth client conversations on AI (Q4 FY2025, Hall)
- Expanded AI insights library to more than 6,000 AI-related documents and documented more than 1,000 unique AI use cases by end of 2025 (Q4 FY2025, Hall)
- Developed and deployed a neural network AI model to identify trending client topics in real time and route relevant data assets to analysts (Q4 FY2025, Hall)
- Completed AskGartner rollout to all licensed users in October 2025; users who used it had substantially higher renewal rates than non-users even at equal engagement levels (Q4 FY2025, Hall)
- Beginning July 2025, reduced average insight creation time for high-value types (e.g., Magic Quadrants) by 75% versus 2024 via new content types, process restructuring, and AI automation (Q4 FY2025, Hall)
- Grew Active Insights library by approximately 50% by end of 2025, enabled by AI-driven automation and streamlined processes (Q4 FY2025, Hall)
- Deployed AI-based sales role-play tools enabling salespeople to practice C-level client conversations; described as exponentially better than prior role-play methods (Q4 FY2025, Hall)
- AI named as an explicit capital allocation investment priority alongside expert talent, customer experience, and frontline sellers (Q4 FY2025, Safian)
CURRENT (now)
- AskGartner receives a new release every 2 weeks combining feature enhancements and incremental proprietary data integration; client usage and repeat usage are increasing (Q1 FY2026, Hall/Safian)
- AskGartner now supports queries in 25 languages and enables downloadable PowerPoint creation directly within the tool (Q1 FY2026, Hall)
- High-impact documents up 22%, total insights library up 19%, same-day event-driven documents more than doubled—all driven by AI-enabled BTI transformation (Q1 FY2026, Hall)
- Gartner leverages AI to quickly identify and summarize high-value insights, personalized by role, function, mission-critical priorities, and viewership history (Q4 FY2025, Hall)
- Neural network system running in real time to identify trending topics and route relevant assets to analysts; weekly AI-identified 'must-read' content routed to salespeople by role (Q4 FY2025, Hall)
- AI automation is now standard in insight production workflow since July 2025; production restructuring (including headcount in non-creative roles) completed (Q4 FY2025, Hall)
FORWARD (guidance)
- AskGartner improvements will continue as foundational models improve and clients provide feedback (Q1 FY2026, Safian)
- AI-driven operational efficiencies expected to free up resources for reinvestment in analysts and frontline sellers, supporting CV growth acceleration and long-term margin expansion (Q1 FY2026, Safian)
- Continued BTI transformation including AI components expected to drive step-change improvement in client value, engagement, and retention over the next several years (Q4 FY2025, Hall)
- Gartner explicitly positions itself as the best-placed guide for clients on AI journeys, expecting AI to remain the single highest-demand advisory topic (Q1 FY2026, Hall)
- Gartner will not distribute proprietary content via third-party LLMs; proactive human advisory and 'seeing around corners' is the strategic moat against AI disintermediation (Q1 FY2026, Hall)
TRACK RECORD — PROMISE vs DELIVERY
—/100 (no quantified promises) no-quantified-promises 6 calls reviewed
Across Q4 FY2024–Q1 FY2026, Gartner cites many AI metrics (AskGartner rollout, 75% faster insight production, ~50% library growth, 6k+ AI documents) but almost always as retrospective results, pilot anecdotes, or ongoing cadence—not as earlier earnings-call commitments with both a number and a deadline. No prior quantified AI target in this set is judgeable for delivery vs miss.
PRICED-IN (REFINED)
LOW (room left)Est. revisions flat · Fwd P/E 13.3 · EV/Sales 2.0x
AI claim maps to Research Segment, Consulting, Events
Analyst sentiment is not migrating up: buy counts slipped from four to three while holds rose to ten, consensus is Hold with more sells, and forward revenue dips in FY2026 before modest recovery—EPS growth is mid-single digits, not an AI-driven step-up. Price targets show a short-term lift (last month above last quarter) but remain far below the year-ago average, so revisions are mixed, not clearly rising. At ~13.3x forward P/E and ~2.0x EV/Sales, valuation is reasonable for a mature research/consulting model, not rich enough to imply AI upside is already capitalized; AI claims would most plausibly flow through Research Segment and Consulting, where estimates still look subdued.
COVERAGE — ENTHUSIASM TRAJECTORY + CATALYSTS
5Q4 FY20246Q1 FY20258Q2 FY20259Q3 FY20259Q4 FY20258Q1 FY2026
AI enthusiasm across 6 calls — trend ↗ rising
AI shifted from client-demand advisory to AskGartner, quantified internal productivity, and retention-linked insights transformation.
RECENT AI CATALYSTS & NEWS
BUSINESS IMPACT - QUALITATIVE MATERIALITY
7/10 qualitative impact material near-term · mixed evidence
Where AI matters: Research subscriptions (AskGartner retention/engagement) and insight-production cost
Deployed AskGartner, 75% faster high-value insight production, and rising usage are real drivers of retention and capacity in the core Research line, but mgmt gives no $/bps on renewal lift and reinvests savings rather than banking margin while consensus revenue stays flat.
Caveats: Renewal premium and productivity gains are unquantified; flat FY26 revenue consensus implies limited modeled top-line lift; Efficiency gains are reinvested into analysts/sellers, not near-term EPS upside; AskGartner may train clients to self-serve more and compress inquiry/conference pull over time; Third-party LLM distribution refusal limits reach but may not stop client-side substitution
AI DISRUPTION / CANNIBALIZATION RISK two-sided · 6/10
GenAI commoditizes reactive Q&A and generic summaries—the layer many clients could substitute for seats—while Gartner’s moat (proactive guidance, unpublished analyst knowledge, human advisory) is coherent but not immune as clients internalize AskGartner-style tools.
OPTIONS / MARKET STRUCTURE
option liquidity: good
proxy inputs — dollar-ADV $277M · beta 0.909 · px $170.62
source: proxy (no options chain on FMP)
FMP /stable/ exposes no options-chain endpoint on this key, so ATM IV, bid-ask spread and open interest are unavailable. Liquidity below is a PROXY from dollar-ADV, beta and price level (a stand-in for option depth), not measured option-market data.
CONFIRMATION — INSIDERS · 13F · LANGUAGE
Confirming — insiders neutral, institutions adding, management language 4/10 measured.
INSIDERS neutral no open-market buys/sells in last 6mo (routine: 26 awards, 9 tax-withholding)
INSTITUTIONS (13F) adding as of 2026-03-31: 99 new / 198 closed positions; 377 increased / 237 reduced; institutional ownership +1.37pp; -100 net 13F holders
MGMT LANGUAGE 4/10 measured AI is thin on the call: client-demand and positioning, one internal-use claim, no AI-specific business metrics.
commit “AI continues to be one of the most requested topics across all the roles we serve.”
commit “And we are world-class users of AI internally.”
commit “we've added the ability to create downloadable PowerPoint presentations directly from within AskGartner.”
VERBATIM AI QUOTES
“AI continues to be one of the most requested topics across all the roles we serve. Gartner sits at the nexus of CIOs and IT organizations, business leaders and AI technology providers. This gives us a full proprietary perspective that includes all the major players.”
— Eugene Hall, Q1 FY2026
“We also have comprehensive independent and objective guidance on all aspects of AI, strategy, ROI, ethics and governance, workforce readiness and more. We cover the full range of issues leaders need to address to be successful with AI. And we are world-class users of AI internally. No one is more capable or better positioned to guide leaders along their AI journeys than Gartner.”
— Eugene Hall, Q1 FY2026
“Gartner is the best source for clients looking to achieve success on their AI journeys.”
— Eugene Hall, Q1 FY2026
“The client usage continues to increase and the amount of repeat client usage continues to increase. And so we're seeing increasing engagement with AskGartner. We do a new release every 2 weeks.”
— Eugene Hall, Q1 FY2026
“we've added sort of support for 25 languages. You can now create PowerPoints directly from the from with AskGartner, and there's all series of other kinds of upgrades.”
— Eugene Hall, Q1 FY2026
“Those upgrades are a combination of feature enhancements and incremental proprietary data that the tool is going from as well. And so we are very quickly rolling out new features, as Gene mentioned, every 2 weeks, and we'll continue to do that as there's demand for it, as the models improve and as our clients give us feedback on what they want from the tool.”
— Craig Safian, Q1 FY2026
“we can leverage AI for some of that. We can leverage other technologies for other things. We can improve processes as well, and we will continue to do that.”
— Craig Safian, Q1 FY2026
“that doesn't really fit well with feeding into an LLM that is really answering questions, which is we have as Gartner. That's not the majority of what we do”
— Eugene Hall, Q1 FY2026
“AI continues to be one of the most requested topics across all the roles we serve. During 2025, we expanded our AI insights. We have more than 6,000 AI-related documents in our library. We've documented more than 1,000 unique use cases. In 2025, we conducted more than 200,000 in-depth client conversations on AI, and we answered more than 500,000 AI-related questions through AskGartner.”
— Eugene Hall, Q4 FY2025
“We developed a neural network AI model to quickly and systematically determine the topics our clients care about most.”
— Eugene Hall, Q4 FY2025
“As Gartner leverages AI to quickly identify and summarize the right high-value insights across our vast library. It leverages role, function, mission-critical priorities, insight viewership histories and more to make user responses even more relevant to each license user.”
— Eugene Hall, Q4 FY2025
“Licensed users who use AskGartner had substantially higher renewal rates than those who did not even with the same levels of engagement.”
— Eugene Hall, Q4 FY2025
“for insight types that are highly valued by our clients, such as Magic Quadrants, we reduced our average insight creation time by 75% compared to 2024.”
— Eugene Hall, Q4 FY2025
“between those 3 factors, different content types restructure the process and what is jobs are and then provide a lot of automation, including AI, allowed us to shrink the production time, which, again, in today's world is really, really important.”
— Eugene Hall, Q4 FY2025
“use AI-based role play tools so that we can put a sales person situation with these AI tools or they are talking to a prospect or a client about things like what's the value, how -- what questions they might have...adding AI-based tools has allowed us to exponentially explain those better role place. And the sales teams love these tools because it makes it so much more proficient.”
— Eugene Hall, Q4 FY2025
“we do not hear frequently is that they're thinking about using AI and some way the substitute for Gartner...Q4 is less of an issue or less confirmed than even before. But we try to track it very carefully.”
— Eugene Hall, Q4 FY2025
“We continue to balance disciplined cost management, while ensuring we can invest in key areas such as expert talent, AI, the customer experience and frontline sellers.”
— Craig Safian, Q4 FY2025
“As of the end of 2025, our Active Insights library has grown by approximately 50%.”
— Eugene Hall, Q4 FY2025
ANALYST QUESTIONS ON AI
Q (Q1 FY2026, Jeff Meuler (Baird)): Just anything you can give us on the evolution of AskGartner, either usage statistics or any meaningful changes in, I guess, user experience, either from something new with the foundational models that underpin it or any adjustments that you've been making to it?
A: Hall: AskGartner is important and will be made competitive; client usage and repeat usage are increasing; new releases every 2 weeks; added 25-language support and PowerPoint creation. Safian: Upgrades combine feature enhancements and incremental proprietary data; cadence will continue as models improve and clients give feedback.
Q (Q1 FY2026, Toni Kaplan (Morgan Stanley)): A number of the other info services firms have been starting to use large LLM providers as like an additional distribution channel... is there a sort of broader data distribution that you would consider? Or do you think that, that dilutes your value proposition too much?
A: Hall: Gartner's core value is proactive guidance—telling clients what they don't know, not answering reactive questions—plus deep human advisory via analysts and executive partners. Published content is only ~5% of what analysts know; the rest is accessed through inquiries and conferences. Feeding content into a third-party LLM is 'not our plan' and 'doesn't really fit well' with this value proposition.
Q (Q1 FY2026, Surinder Thind (Jefferies)): Any update where maybe there's a bit more benefits from even if it's AI or just other things that are going on and the opportunity for any potential structural change in the outlook for margins at this point?
A: Safian: Continuously driving operational efficiencies including through AI, but those savings are reinvested in growth-driving areas (analysts, frontline sellers, AskGartner) rather than dropped to margin; the OpEx model is being tuned to align run rates with CV growth expectations while protecting long-term investments.
Q (Q4 FY2025, Toni Kaplan (Morgan Stanley)): Wanted to get a sense of in the fourth quarter if AI sort of entered the renewal conversations a little bit more in terms of client decision-making around adding or removing seats... And is the environment getting maybe a little bit better?
A: Hall: AI-as-substitute is tracked via a dedicated help desk and salesperson documentation system used by roughly half the sales force annually; it is 'not heard frequently' and was even less prevalent in Q4 than before. Real headwinds are tariffs, budget pressure, and federal government cuts—not AI displacement risk.
Q (Q4 FY2025, Jason Haas (Wells Fargo)): Are there any changes to try to institutionalize some of the process that your analysts go through to collect proprietary insights from your customers? Because our understanding is there's a treasure trove of data that your analysts are collecting.
A: Hall: A neural-network-based system ingests hundreds of thousands of annual client conversations, vendor briefings, peer interactions, and proprietary surveys, identifies trending topics on a real-time basis, and routes the most relevant data assets to the analysts covering those specific topics. This replaced informal analyst information-sharing and is a core part of the BTI transformation.
Q (Q4 FY2025, Brendan Popson (Barclays, for Manav Patnaik)): You talked about some of the rapid change internally. And I also noted you mentioned this 75% time reduction for insights. So I guess just any clarity on what exactly that means?
A: Hall: Beginning July 2025, three levers cut production time: (1) new content types such as 'First Take' for same-day events; (2) streamlining the back-end editing process including headcount reduction in non-creative roles; and (3) AI-powered automation across production steps. Together these reduced average creation time for high-value insight types (e.g., Magic Quadrants) by 75% versus 2024.