← back to rankingICE · Intercontinental Exchange, Inc.
Financial - Data & Stock Exchanges · mkt cap $80.5B · calls: Q1 FY2026 vs Q4 FY2025
46.0 conviction · conf-adj 46
conf 3/10 partial
enthusiasm:27.0 · trend:8 · quantifies:0 · impact:0 · under_radar:0 · credibility:0 · business_impact:8 · disruption:0 · commitment:0 · confirmation:3
Enthusiasm latest 9 / prev 8 (rising)
ICE's AI thesis is that proprietary financial data, owned data-center infrastructure, and regulated workflow systems make it a supplier of trusted inputs and embedded automation rather than a software vendor exposed to generic model substitution. The latest call is more enthusiastic because management moved from describing AI-enabled products and pilots to saying AI is in production, embedded in systems of record, and supported by MCP server infrastructure. Quantification is present but still mostly indirect: usage, CapEx, and revenue growth partly attributed to AI demand rather than discrete AI revenue.
GROUNDED NEXT-FY IMPACT vs CONSENSUS
Grounded on actual base — revenue $12.6B · net income $3.3B · net margin 26.1% · diluted EPS 5.77
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: high · confidence: 3/10
| Claim | Figure | Arithmetic | Next-FY Rev % | Next-FY EPS % |
|---|
Data & Network Technology revenue +11% in Q1, 'partly' AI-driven capacity demand
engagement · soft | 11% (segment growth, only partly AI) | 11% is TOTAL Data & Network Technology segment growth, attributed only 'partly' to AI. Management discloses neither the segment's dollar base nor the AI-specific share, so the AI portion cannot be isolated. Even if the segment were ~10% of the $12.638B base, '11% partly AI' yields no clean AI dollar figure. Pcts null per the vague/unanchored rule. | | |
Servicing processed ~4B API/web-service calls in March, up ~20% YoY, driven by AI/BI tools
engagement · soft | ~4 billion calls; +20% YoY | This is a USAGE/engagement signal (call volume), not a revenue figure. No price-per-call or incremental revenue is disclosed; ICE frames it as embeddedness, not a new revenue line. No way to map 4B calls to incremental dollars without a take-rate ICE did not provide. Pcts null, soft. | | |
2026 CapEx $740M–$790M including AI infrastructure (GPUs, storage, network)
other · soft | $740M–$790M total 2026 capex (AI infra a subset, unsized) | Midpoint capex = ($740M+$790M)/2 = $765M; $765M/$12.638B rev = 6.05% and $765M/$3.304B NI = 23.15%. But this is capital spend on AI infra to serve ICE's own workloads — capitalized and depreciated, not a near-term EPS event; any P&L effect is future depreciation drag, not a quantified return. AI-specific portion not broken out; no ROI given. No rev or EPS uplift computable. Pcts null, soft. | | |
Assumptions: Defaults: incremental net margin = company net margin 26.1% (would apply to any incremental data/services revenue if a figure existed); tax rate 21% for opex savings (none claimed); phasing = next FY (2026). No hard AI dollar figure was disclosed in ANY claim, so no flow-through arithmetic could be executed. Side mapping: all three are ADOPTER — AI lifts demand for ICE's own network/data/servicing products and drives ICE's own capex; ICE is not selling AI compute/chips into the buildout (not supplier). Segment mapping: Claim 1→Data & Network Technology; Claim 2→Mortgage Technology/Servicing; Claim 3→balance-sheet capex, not a P&L line. CapEx sized at midpoint only.
Top line: No isolatable AI revenue. The only topline figures are an 11% segment growth rate attributed merely 'partly' to AI (no AI dollar share, no segment base disclosed) and a 4-billion-call/+20% usage statistic with no take-rate — neither yields a computable revenue uplift. AI here is a qualitative tailwind embedded in existing segment momentum, not a sized incremental revenue stream.
Bottom line: No quantified savings or earnings benefit. The one bottom-line item, $740–790M of 2026 capex (midpoint $765M = 6.05% of revenue, 23.15% of net income, including unsized AI infra), is investment that gets capitalized and depreciated — a future cost item, not an EPS uplift. After-tax math is moot because no return figure was given.
[impact n/m (all claims soft/unanchored)] Consensus already embeds ~11.3% revenue growth (2025E $9.896B → 2026E $11.017B) and EPS growth $6.92 → $8.10 (+17%). ICE's AI commentary describes tailwinds to ALREADY-growing lines (Data & Network Technology +11%, Servicing usage +20%) plus ordinary capex — all consistent with, and absorbed by, the existing consensus trajectory. No disclosed AI figure points ABOVE that path, so there is no quantifiable upside gap; the AI narrative is priced in.
MODEL CONSENSUS (impact)
partial
Both reached identical null uplifts, priced_in high, confidence 3; only claim-1 classification differed, resolved to Y's better-justified adopter mapping.
Conflicts reconciled
- math[0].side: X=supplier vs Y=adopter -> used adopter because ICE sells its own network/data capacity (demand partly lifted by AI), not AI compute/chips into the buildout
- math[0].type: X=revenue vs Y=engagement -> used engagement because the 11% is a partly-AI growth rate with no AI dollar share
- ai_revenue_side: X=both vs Y=adopter -> used adopter, consistent with reclassifying claim 1 as adopter
| Field | Opus 4.8 | GPT-5.5 |
|---|
| Rev uplift % | – | – |
| EPS uplift % | – | – |
| Priced in | high | high |
| vs analysts | unclear | unclear |
| Confidence | 3 | 3 |
| Top line | No isolatable AI revenue. The only topline figures are an 11% segment growth rate attributed merely 'partly' to AI (no AI dollar share, no segment base disclosed) and a 4-billion-call/+20% usage statistic with no take-rate — neither yields a computable revenue uplift. AI here is a qualitative tailwind embedded in existing segment momentum, not an incremental, sized revenue stream. | No hard adopter-side revenue uplift can be calculated. The 4B calls/up nearly 20% claim is engagement without pricing, while the 11% D&NT growth claim is supplier-side and lacks segment revenue and AI attribution. |
| Bottom line | No quantified savings or earnings benefit. The one bottom-line item, $740–790M of 2026 capex (including unsized AI infra: GPUs/storage/network), is investment that gets capitalized and depreciated — a future cost item, not an EPS uplift. After-tax math is moot because no return figure was given. Net EPS effect from disclosed AI claims is effectively unquantifiable and, on the capex line, slightly negative over time. | The only quantified bottom-line item is 2026 capex of $740M-$790M; midpoint $765M equals 6.05% of current revenue and 23.15% of current net income, but it is investment rather than an EPS uplift and the AI portion is not disclosed. |
| Reasoning | Consensus already embeds ~11.3% revenue growth (2025E $9.896B → 2026E $11.017B) and EPS growth $6.92 → $8.10 (+17%). ICE's AI commentary describes tailwinds to ALREADY-growing lines (Data & Network Technology +11%, Servicing usage +20%) plus ordinary capex — all consistent with, and absorbed by, the existing consensus trajectory. No disclosed AI figure points ABOVE that path, so there is no quantifiable upside gap; the AI narrative is priced in. | Consensus already implies 2026 revenue of $11.017B versus 2025 consensus revenue of $9.897B, a $1.121B increase or 11.33%, and EPS of $8.10261 versus $6.91643, up 17.15%. Versus the provided actual base, 2026 consensus EPS is up 40.43% from $5.77, while consensus revenue is not comparable because it is below the provided $12.638B base. The quantified AI claims do not produce a measurable adopter-side uplift above those expectations. |
Rows highlighted where the two models disagreed.
QUANTIFICATIONS
Data & Network Technology revenue growth tied partly to AI-driven capacity demand: 11% (first quarter, topline)
“Data & Network Technology revenues increased 11% in the first quarter, reflecting strong demand for our ICE global network, consolidated feeds and desktop solutions. Private global data center network connecting over 750 data sources and 150 trading venues across 24 countries is a physical infrastructure asset that cannot be replicated quickly or cheaply, and it continues to benefit from secular demand trends, including higher messaging activity and AI-driven demand for capacity.”
Servicing API and web services calls driven by AI and Business Intelligence tools: approximately 4 billion; up nearly 20% year-over-year (March, topline)
“In March alone, our Servicing business processed approximately 4 billion API and web services calls up nearly 20% year-over-year driven by increased use of our AI and Business Intelligence tools, a signal that our infrastructure is becoming more embedded in client operations, not less.”
2026 CapEx including AI infrastructure: $740 million to $790 million (2026, bottomline)
“Regarding capital expenditures, we expect 2026 investments to be between $740 million and $790 million. This includes installing AI infrastructure, such as GPUs, storage, and network equipment designed to handle AI and data-intensive workloads.”
PAST (realized)
- In March alone, our Servicing business processed approximately 4 billion API and web services calls up nearly 20% year-over-year driven by increased use of our AI and Business Intelligence tools, a signal that our infrastructure is becoming more embedded in client operations, not less.
- We did that last year through the launch of call prediction capabilities, call summarization, automated call routing to help take costs out of the process there.
- These are the result of initiatives that we had this year, and solutions that we brought to market both across Encompass as well as in servicing.
CURRENT (now)
- Internally, we're already deploying AI in production across our organization.
- The application of AI with our agents that automate multistep manual workflows is driving our engagement with our clients across price mortgage technology.
- As customers integrate artificial intelligence into their workflows and require ever-increasing volumes of high-quality data, we are uniquely positioned as a critical technology provider.
FORWARD (guidance)
- As AI is incorporated into these workflows, that pricing model remains durable and stands to benefit us.
- We are in the process of rolling out the following ICE Aurora AI-enabled agents for our IMT business in the first half of this year.
- Among several other initiatives, these investments include expanding our data center footprint to meet growing customer demand and developing new artificial intelligence tools that will drive future productivity and innovation.
TRACK RECORD — PROMISE vs DELIVERY
—/100 (no quantified promises) no-quantified-promises 6 calls reviewed
ICE began discussing AI in substance only from Q3 FY2025 (the 'ICE Aurora' platform), framing it almost entirely as current-state reporting (e.g. >95% reference-data extraction accuracy, ~40,000 documents/month processed) rather than forward-looking quantified AI targets. The revenue/CapEx figures management did guide to were general Data and Network Technology and recurring-revenue guidance that merely cite AI as one demand driver, not standalone quantified AI promises with a number and date — so there is no AI delivery track record to score.
PRICED-IN (REFINED)
HIGH (already in)Est. revisions rising · Fwd P/E 20.6 · EV/Sales 7.6x
AI claim maps to Fixed Income And Data Services Segment, Mortgage Technology Segment, Exchanges Segment
Estimate revisions are rising: analyst ratings migrated toward more strongBuy/buy and fewer holds, and price targets increased from last-year to last-quarter to last-month averages. The stock also trades at a rich mature-company valuation, with a 20.6x forward P/E and 7.6x EV/sales. AI upside would most plausibly flow through Fixed Income And Data Services, Mortgage Technology, and exchange workflow/data operations, so rising estimates plus rich valuation indicate the market is already paying for much of that upside.
COVERAGE — ENTHUSIASM TRAJECTORY + CATALYSTS
2Q4 FY20242Q1 FY20252Q2 FY20258Q3 FY20256Q4 FY20255Q1 FY2026
AI enthusiasm across 6 calls — trend ↗ rising
AI moved from absent to an explicit ICE Aurora initiative, then settled into data-network demand and customer workflow positioning.
RECENT AI CATALYSTS & NEWS
BUSINESS IMPACT - QUALITATIVE MATERIALITY
7/10 qualitative impact material near-term · mixed evidence
Where AI matters: financial data, mortgage workflow automation, internal productivity
AI is already embedded in ICE systems of record, mortgage servicing agents, pricing/index workflows, and data/network demand, with usage signals like 4B servicing API/web calls in March and Data & Network Technology growth partly tied to AI capacity needs. The upside is meaningful for FIDS and Mortgage Technology, but ICE has not isolated AI revenue, margins, or EPS, so this is not yet company-transforming.
Caveats: No disclosed AI-specific revenue or EPS contribution; AI infrastructure capex could outrun monetization; Generic AI interfaces may reduce differentiation in some desktop or analytics products; Regulatory and audit requirements could slow customer deployment
AI DISRUPTION / CANNIBALIZATION RISK tailwind · 2/10
ICE's core assets are proprietary regulated data, exchange/clearing infrastructure, networks, and workflow systems that AI users need rather than easily replace. Generic AI could pressure some analytics interfaces, but it is unlikely to commoditize ICE's trusted data, connectivity, governance, or regulated systems of record.
OPTIONS / MARKET STRUCTURE
option liquidity: good
proxy inputs — dollar-ADV $475M · beta 0.964 · px $142.38
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
Mixed — insiders selling, institutions adding, management language 4/10 measured.
INSIDERS selling 26 open-market sell(s) vs 0 buy(s) — net distribution
INSTITUTIONS (13F) adding as of 2026-03-31: 150 new / 176 closed positions; 843 increased / 623 reduced; institutional ownership -10.92pp; -36 net 13F holders
MGMT LANGUAGE 4/10 measured AI is barely discussed; language is declarative but broad, with no AI-specific targets, timelines, or quantified revenue impact.
commit “including higher messaging activity and AI-driven demand for capacity”
commit “the growing reliance on proprietary and institutional-grade data by AI systems and human decision-makers alike”
hedge “the forward opportunity set remains as large as it has ever been”
VERBATIM AI QUOTES
“Data & Network Technology revenues increased 11% in the first quarter, reflecting strong demand for our ICE global network, consolidated feeds and desktop solutions. Private global data center network connecting over 750 data sources and 150 trading venues across 24 countries is a physical infrastructure asset that cannot be replicated quickly or cheaply, and it continues to benefit from secular demand trends, including higher messaging activity and AI-driven demand for capacity.”
— Warren Gardiner, Q1 FY2026
“Because this is a highly regulated market that requires a deep understanding of risk, audit and governance before deployment, we embed AI directly into the systems of record, reinforcing ICE's role as a neutral trusted platform that does not compete with its customers.”
— Benjamin Jackson, Q1 FY2026
“In March alone, our Servicing business processed approximately 4 billion API and web services calls up nearly 20% year-over-year driven by increased use of our AI and Business Intelligence tools, a signal that our infrastructure is becoming more embedded in client operations, not less.”
— Benjamin Jackson, Q1 FY2026
“At our ICE Experience Conference in March, we unveiled AI-powered Voice and Chat Agents for Mortgage Servicing to handle routine borrower inquiries, execute common loan management actions and help servicers manage fluctuating call volumes.”
— Benjamin Jackson, Q1 FY2026
“Artificial intelligence fits squarely within that strategy. It accelerates the way regulated workflows are processed by embedding intelligence directly into our systems of record, preserving governance and audibility and while improving speed and insight.”
— Jeffrey Sprecher, Q1 FY2026
“Internally, we're already deploying AI in production across our organization. Teams are using it to undertake code writing, enhanced pricing workflows, accelerate index calculations, support client interaction and earlier identified loan servicing issues. These are not experiments.”
— Jeffrey Sprecher, Q1 FY2026
“ICE now offers an AI model control protocol server, or MCP server located in our data center and available on the ICE proprietary Cloud to ease access to ICE's nonproprietary data.”
— Jeffrey Sprecher, Q1 FY2026
“As customers integrate artificial intelligence into their workflows and require ever-increasing volumes of high-quality data, we are uniquely positioned as a critical technology provider.”
— Warren Gardiner, Q4 FY2025
“More broadly, the growth of AI continues to be an enabler. Our ICE Aurora platform, paired with our high-quality proprietary data with controlled secure distribution into customer workflows, is where ICE differentiates.”
— Benjamin Jackson, Q4 FY2025
“The application of AI with our agents that automate multistep manual workflows is driving our engagement with our clients across price mortgage technology.”
— Benjamin Jackson, Q4 FY2025
“Applying our ICE Aurora platform and agents to workflow automation remains the most effective lever, moving manual steer and compare tasks to exception-based workflows where people focus only on what needs human judgment.”
— Benjamin Jackson, Q4 FY2025
ANALYST QUESTIONS ON AI
Q (Q1 FY2026, Brian Bedell): Maybe switching over to fixed income data and data and tech. Just noticing the really straight-line improvement in growth here, FIDS overall recurring revenue going up 5%, 6%, 7%, 8% and now 9% on a year-over-year basis the last 5 quarters. And it looks like the contribution is coming both from FIDS and data and network technology with data and tech obviously now in the double digits. So can you just talk about what have been the 2 or 3 or so biggest drivers organically for that and outlook throughout 2026. I assume the Polymarket initiative is going to be included in this area. And then I guess, just overall, I guess the punchline is, does the mid-single-digit revenue growth guidance in FIDS recurring revenue seem conservative given the really strong momentum here?
A: Certainly, the appetite for data across the entire segment with some of the comments that Jeff made around AI and things that we're doing that, there are 3 real components that we have in the portfolio, a very large segment of proprietary data, that is very well versed in the regulatory community.
Q (Q4 FY2025, Craig Siegenthaler): And just as a follow-up on the tech side, can you update us on the opportunities to modernize your mortgage technology tech stack, whether it's through blockchain-enabled capabilities at MERS or even AI tools that could improve efficiency at Encompass or MSP?
A: And we have been accelerating bringing to market different solutions in and around those tech stacks. I went through a bunch of the agents and AgenTek AI initiatives that we have coming into this year.
Q (Q4 FY2025, Benjamin Budish): I wanted to ask about the FIDS business. One of the themes that reemerged quickly this week has been this AI disruptive fear across all things software. Just for you guys, I think the question that we get the most is, you know, on the data and analytics businesses, you know, where is their potential risk?
A: One, we generate a lot of proprietary mission-critical content on all of our activities that we have within the exchange and clearing space that goes into drive models around there. And we license that data effectively to the client base around there.