NDAQ · Nasdaq, Inc.

Financial - Data & Stock Exchanges · mkt cap $49.7B · calls: Q1 FY2026 vs Q4 FY2025

69.0 conviction · conf-adj 69

conf 6/10 partial

enthusiasm:27.0 · trend:8 · quantifies:5 · impact:0 · under_radar:0 · credibility:12 · business_impact:8 · disruption:0 · commitment:6 · confirmation:3

Enthusiasm latest 9 / prev 7 (rising)

Nasdaq's AI thesis moved from broad product rollout in Q4 FY2025 to measured adoption, bookings support, enterprise cross-sells and a stated cost-efficiency target in Q1 FY2026. Credibility is strongest in Verafin, AxiomSL, surveillance and corporate solutions because management tied AI to actual client deployments, user adoption, bookings and renewals. The weakest point is that most revenue impact is still indirect rather than disclosed as standalone AI revenue.

GROUNDED NEXT-FY IMPACT vs CONSENSUS

Grounded on actual base — revenue $8.2B · net income $1.8B · net margin 21.8% · diluted EPS 3.09

These are next-fiscal-year annual uplift estimates, not next-quarter numbers.

Aggregate next-FY est. rev uplift: % · next-FY EPS uplift: 0.022079374% · vs analysts: inline · priced in: high · confidence: 6/10

Claim	Figure	Arithmetic	Next-FY Rev %	Next-FY EPS %
$100M expense efficiencies by end-2027 cost	$100 million	Cost saving, adopter-side, pure opex (topline ~0). Full run-rate: $100M(1-0.21 tax)=$79M after-tax = $79M/$1,789M NI = 4.42% EPS. Phasing: end-2025->end-2027 is a ~2yr ramp, assume ~linear so ~$50M realized next FY (2026); $50M0.79=$39.5M; $39.5M/$1,789M NI = 0.0221 (2.21%) EPS uplift.	0	0.022079374
>$9T client AUM adopted AI-ready data engagement · soft	over $9 trillion	$9T is CLIENT AUM, not Nasdaq revenue. No disclosed Nasdaq $ revenue base, fee rate, or conversion for the AI-ready data line -> cannot size. Unanchored.
29% YoY Q1 bookings increase (AI-helped) engagement · soft	29%	Growth rate on an undisclosed bookings $ base; bookings != revenue and only partly AI-attributable. No base obtainable from inputs -> soft.
74% of IR Insight users on AI engagement · soft	74%	Adoption rate with no disclosed IR Insight revenue base, user count, pricing, or take-rate uplift. Soft.
51% of Boardvantage users on AI engagement · soft	51%	Adoption rate with no disclosed Boardvantage revenue base or $ mapping. Soft.
Agentic-AI workforce at >500 clients engagement · soft	more than 500 clients	Client count with no disclosed ARPU/revenue-per-client or incremental attach. Soft.
Agentic-AI deployment up 40% since Investor Day engagement · soft	up 40%	Growth rate on an undisclosed base (implies ~357 prior, ~143 incremental) but no ARPU/revenue base -> cannot translate to revenue/EPS. Soft.

Assumptions: Tax rate = 21% (default). Incremental margin n/a — no anchored revenue claim (current net margin ~21.8% would apply if a revenue base existed). Phasing: $100M is an end-2027 run-rate target; from end-2025 that's a ~2yr ramp, assumed ~linear so ~$50M attributable to next FY (2026), giving 0.0221 EPS uplift, with the full 4.42% run-rate by 2027. All claims are adopter-side (AI improves Nasdaq's own products, client adoption, bookings, expenses — not selling AI infrastructure). EPS/rev uplift fields expressed as fractions per the formula (income/revenue ratios).

Top line: Unsizable from disclosure. The topline AI claims (>$9T client AUM, +29% Q1 bookings, 74% IR Insight and 51% Boardvantage AI adoption, 500+ agentic clients, +40% since Investor Day) are real engagement signals but each is a client-side metric or growth rate with no Nasdaq revenue dollar base disclosed in the inputs, so no defensible rev_uplift_pct can be computed -> est_rev_uplift_pct=null.

Bottom line: Driven entirely by the one anchored figure: $100M of expense efficiencies by end-2027. After-tax at 21% that is $79M = 4.42% of $1,789M net income at full run-rate; phasing ~half into next FY (2026) gives ~$39.5M after-tax = 0.0221 (2.21%) EPS uplift. Adopter-side, pure opex (topline ~0).

The only hard AI figure is a publicly-guided cost tailwind: ~4.42% cumulative / ~2.21% next-FY EPS, small relative to and almost certainly embedded in the 11-12 analyst estimates. Consensus EPS rises into 2026 (~+12-15% on the higher current-EPS base, larger on a lower base — the two source EPS bases differ) and again into 2027, so a ~2.2% next-FY cost benefit is readily absorbed. Topline AI claims are unsizable (no disclosed Nasdaq revenue base) and so cannot be scored as upside vs consensus.

MODEL CONSENSUS (impact)

partial

Agree on verdicts (inline/high), claims, and the lone hard cost figure. Reconciled est_rev_uplift_pct to null and standardized EPS to fractional units.

Conflicts reconciled

est_rev_uplift_pct: X=0 vs Y=null -> used null because topline claims have no disclosed revenue base; 0 wrongly implies a measured no-impact rather than unsizable
eps units: X=fraction(0.0221) vs Y=percent(2.21) -> used fraction per the formula's income/revenue ratio definition
supplier_rev_uplift_pct: X=0 vs Y=null -> used 0 because there are zero supplier-side claims (genuinely none, not unsizable)
29% bookings type: X=revenue vs Y=engagement -> used engagement, more conservative for an unanchored growth rate

Field	Opus 4.8	GPT-5.5
Rev uplift %	–	0
EPS uplift %	2.21	0.022079374
Priced in	high	high
vs analysts	inline	inline
Confidence	6	6
Top line	Unsizable from disclosure. The topline AI claims (>$9T client AUM, 29% Q1 bookings growth, 74%/51% product adoption, 500+ agentic clients, +40% since Investor Day) are real engagement signals but every one is a client-side metric or growth rate with no Nasdaq revenue dollar attached — none disclose a revenue base in the inputs, so no defensible rev_uplift_pct can be computed. est_rev_uplift_pct=null.	No hard next-FY revenue uplift is calculable. The strongest topline datapoints are $9T+ AUM adoption, +29% Q1 bookings, 74% IR Insight AI use, 51% Boardvantage AI use, and 500+ Agentic-AI clients, but each lacks a disclosed revenue or bookings dollar base.
Bottom line	Driven entirely by the one anchored figure: $100M of expense efficiencies by end-2027. After-tax at 21% that is $79M, or 4.42% of $1,789M net income at full run-rate; phasing ~half into next FY (2026) gives ~$39.5M after-tax = 2.21% EPS uplift. Adopter-side, pure opex (topline ~0).	The hard bottom-line claim is $100M expense efficiencies by end-2027. With straight-line phasing, next-FY saving is $50M; after 21% tax, that is $39.5M, equal to 2.208% of current $1.789B net income.
Reasoning	Consensus EPS rises 3.43->3.94 (+14.7%) into 2026 and ->4.43 (+12.6%) into 2027. The only hard AI figure is a publicly-guided ~4.42% cumulative cost tailwind (2.21% next-FY) — small relative to, and almost certainly embedded in, the 11-12 analyst estimates. Topline AI claims are unsizable so cannot be scored as upside vs consensus.	The only hard adopter-side next-FY uplift is 0.0% revenue and 2.208% EPS. Consensus EPS rises from $3.09 current diluted EPS to $3.93624 for FY2026, a $0.84624 or 27.386% increase. The calculated AI cost uplift is about $39.5M / 576.5M shares = $0.0685 EPS, only 2.218% of current EPS and roughly 8.1% of the consensus EPS increase, so it appears readily absorbed in consensus. Consensus revenue comparisons are distorted because the provided FY2026 revenue estimate of $5.761B is below the stated current revenue base of $8.218B, but no hard AI revenue uplift exists to compare.

Rows highlighted where the two models disagreed.

QUANTIFICATIONS

expense efficiencies: $100 million (by the end of 2027, bottomline)
“we are striving to achieve $100 million of expense efficiencies by the end of 2027”

AI-ready data adopted by client AUM: over $9 trillion (Q1 FY2026, topline)
“The investment AI-ready data has been adopted by global asset managers, GPs and institutional investors representing over $9 trillion in assets under management. and helped drive a 29% year-over-year increase in Q1 bookings.”

bookings increase helped by AI-ready data: 29% (year-over-year in Q1, topline)
“The investment AI-ready data has been adopted by global asset managers, GPs and institutional investors representing over $9 trillion in assets under management. and helped drive a 29% year-over-year increase in Q1 bookings.”

IR Insight AI adoption: 74% of IR Insight users (Q1 FY2026, topline)
“In Corporate Solutions, AI adoption is strong with 74% of IR Insight users and 51% of Boardvantage users leveraging our AI solutions.”

Boardvantage AI adoption: 51% of Boardvantage users (Q1 FY2026, topline)
“In Corporate Solutions, AI adoption is strong with 74% of IR Insight users and 51% of Boardvantage users leveraging our AI solutions.”

Agentic-AI workforce client deployment: more than 500 clients (Q1 FY2026, topline)
“Our Agentic-AI workforce is now deployed by more than 500 clients, up 40% since Investor Day.”

Agentic-AI workforce deployment growth: up 40% (since Investor Day, topline)
“Our Agentic-AI workforce is now deployed by more than 500 clients, up 40% since Investor Day.”

PAST (realized)

The investment AI-ready data has been adopted by global asset managers, GPs and institutional investors representing over $9 trillion in assets under management. and helped drive a 29% year-over-year increase in Q1 bookings.
In Q1, we completed a significant renewal and expansion of AxiomSL driven by our ability to deliver cloud and AI-enabled regulatory solutions.
We embedded AI across our business and have begun rolling out new AI-enabled products with strong client reception.
The first Agentic worker we introduced, our Agentic sanctions analyst, has strong early use among our clients.

CURRENT (now)

Within the banking sector, we're experiencing increasing demand for cloud-based mission-critical solutions that include AI features to support workflow automation.
In Corporate Solutions, AI adoption is strong with 74% of IR Insight users and 51% of Boardvantage users leveraging our AI solutions.
We continue to lead through advanced AI-driven innovation. Our Agentic-AI workforce is now deployed by more than 500 clients, up 40% since Investor Day.
We're also experiencing strong interest in our AI solutions within AxiomSL, including Reg-Copilot, REG Simplify, RegNavigator and REG Investigator, the products we detailed during Investor Day.

FORWARD (guidance)

we are striving to achieve $100 million of expense efficiencies by the end of 2027
Later this quarter, we will launch our new drug trafficking analytic, which embeds generative AI directly into our models and synthesizes open-source intelligence, social media, and third-party research to help clients more effectively detect potential drug trafficking activity.
In the second quarter, we will release our Gen AI platform extension, which connects news and market events to trade data.
We look forward to expanding this offering with additional Agentic workers planned for 2026.

TRACK RECORD — PROMISE vs DELIVERY

73/100 track record delivers 6 calls reviewed

Nasdaq's quantified AI commitments are mostly milestone-based product rollouts (Agentic workers, copilots) and an AI-enabled efficiency target rather than hard revenue guidance, and management consistently hit or exceeded the timelines set (EDD and sanctions analysts shipped on schedule; the $140M efficiency program beat its target). The track record is credible but the promises are relatively soft, lacking dated AI-specific revenue targets to fully stress-test.

Digital/Agentic Enhanced Due Diligence Analyst on track for release by end of 2025 — promised Q3 FY2025
delivered Launched the second Agentic worker (EDD analyst) into production in Q4 FY2025, on schedule

Digital Sanctions Analyst (Agentic AI, ~80%+ alert-review workload reduction) to move from beta to production in 2025 — promised Q2 FY2025
delivered Launched into production in Q3 FY2025 with strong early client adoption

Expanded AI-enabled efficiency program of $140M net expense reduction actioned by year-end 2025 — promised Q4 FY2024 / Q1 FY2025
delivered Overachieved with $160M+ in cost-reduction actions by end of 2025

Agentic AI workforce automating compliance workflows rolled out during 2025 — promised Q1 FY2025
delivered Launched in Q2 FY2025; deployed by 500+ clients by Q1 FY2026

GenAI entity-research Copilot adoption (1,200+ clients) with case-management copilot to follow in 2025 — promised Q1 FY2025
partial Continued expanding AI copilots through 2025-26, though specific follow-on milestones less clearly tracked

PRICED-IN (REFINED)

HIGH (already in)

Est. revisions rising · Fwd P/E 25.6 · EV/Sales 7.1x

AI claim maps to Market Technology, Capital Access Platforms, Market Services

Analyst ratings have migrated modestly upward since early 2026 and price targets remain above the last-year average, while consensus already embeds solid forward revenue and EPS growth. The valuation is rich for a mature exchange/data business, with a 25.6x forward P/E and about 7.1x EV/Sales. AI upside would most plausibly flow through Market Technology, Capital Access Platforms, and some Market Services efficiency, and the combination of rising estimates plus a premium multiple indicates the AI thesis is already largely priced in.

COVERAGE — ENTHUSIASM TRAJECTORY + CATALYSTS

2Q4 FY20244Q1 FY20254Q2 FY20255Q3 FY20259Q4 FY20259Q1 FY2026

AI enthusiasm across 6 calls — trend ↗ rising

AI moved from scattered feature mentions to concrete agentic products, adoption metrics, client traction, and data-led revenue support.

RECENT AI CATALYSTS & NEWS

BUSINESS IMPACT - QUALITATIVE MATERIALITY

8/10 qualitative impact material medium-term · mixed evidence

Where AI matters: financial crime, regtech, data analytics and internal efficiency

Nasdaq has moved beyond generic AI talk: Verafin, AxiomSL, surveillance, AI-ready data and corporate-solutions products show client deployments, high feature adoption, bookings support and a targeted $100M efficiency program by end-2027. The upside is material for important software/data lines, but still not clearly transformational because Nasdaq has not disclosed standalone AI revenue or pricing uplift.

Caveats: AI revenue contribution is mostly inferred from adoption/bookings rather than disclosed dollars; Expense-efficiency target may already be embedded in consensus and depends on execution through 2027; AI features could become table stakes, limiting pricing power; Regulatory, model-risk and data-governance constraints may slow deployment in mission-critical financial workflows

AI DISRUPTION / CANNIBALIZATION RISK tailwind · 2/10

AI does not plausibly automate away Nasdaq's core exchange, regulated infrastructure, proprietary data, compliance workflow and market-technology franchises; it mostly raises the value of those assets. Some basic analytics or interface layers could be commoditized, but the durable pieces are trust, data rights, workflow embedding and regulatory criticality.

OPTIONS / MARKET STRUCTURE

option liquidity: good

ATM IV

—

TYPICAL BID-ASK

—

OPEN INTEREST

—

proxy inputs — dollar-ADV $285M · beta 0.99 · px $87.91

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 8/10 committed.

INSIDERS selling 12 open-market sell(s) vs 2 buy(s) — net distribution

INSTITUTIONS (13F) adding as of 2026-03-31: 136 new / 150 closed positions; 536 increased / 400 reduced; institutional ownership -2.19pp; -10 net 13F holders

MGMT LANGUAGE 8/10 committed Management uses concrete adoption, deployment, bookings, and launch language, with only limited softer interest-based phrasing.

commit “AI adoption is strong with 74% of IR Insight users and 51% of Boardvantage users leveraging our AI solutions.”

commit “Our Agentic-AI workforce is now deployed by more than 500 clients, up 40% since Investor Day.”

commit “Later this quarter, we will launch our new drug trafficking analytic, which embeds generative AI directly into our models”

VERBATIM AI QUOTES

“Within the banking sector, we're experiencing increasing demand for cloud-based mission-critical solutions that include AI features to support workflow automation.”
— Adena Friedman, Q1 FY2026

“Across analytics, we're leveraging our gold standard data assets to support our clients' AI strategy.”
— Adena Friedman, Q1 FY2026

“The investment AI-ready data has been adopted by global asset managers, GPs and institutional investors representing over $9 trillion in assets under management. and helped drive a 29% year-over-year increase in Q1 bookings.”
— Adena Friedman, Q1 FY2026

“In Corporate Solutions, AI adoption is strong with 74% of IR Insight users and 51% of Boardvantage users leveraging our AI solutions.”
— Adena Friedman, Q1 FY2026

“In Q1, we completed a significant renewal and expansion of AxiomSL driven by our ability to deliver cloud and AI-enabled regulatory solutions.”
— Adena Friedman, Q1 FY2026

“Early in the second quarter, we expanded the relationship further with a cross-sell for Nasdaq Verafin, our cloud-based AI native financial crime management solution.”
— Adena Friedman, Q1 FY2026

“We continue to lead through advanced AI-driven innovation. Our Agentic-AI workforce is now deployed by more than 500 clients, up 40% since Investor Day.”
— Adena Friedman, Q1 FY2026

“Later this quarter, we will launch our new drug trafficking analytic, which embeds generative AI directly into our models and synthesizes open-source intelligence, social media, and third-party research to help clients more effectively detect potential drug trafficking activity.”
— Adena Friedman, Q1 FY2026

“We're also experiencing strong interest in our AI solutions within AxiomSL, including Reg-Copilot, REG Simplify, RegNavigator and REG Investigator, the products we detailed during Investor Day.”
— Adena Friedman, Q1 FY2026

“For example, we recently introduced our calibration copilot, an AI-powered tool that's enabling clients to optimize workflows, reduce false positives and increase accuracy of detection.”
— Adena Friedman, Q1 FY2026

“In the second quarter, we will release our Gen AI platform extension, which connects news and market events to trade data.”
— Adena Friedman, Q1 FY2026

“The revenue increase was driven primarily by analytics, mainly investment and Datalink, with both businesses benefiting from strong sales momentum, client engagement to the platform's AI capabilities and demand for data to power AI.”
— Sarah Youngwood, Q1 FY2026

“we are striving to achieve $100 million of expense efficiencies by the end of 2027”
— Adena Friedman, Q1 FY2026

“Our financial crime management technology business pioneered innovative approaches to fight crime and introduced our new Agentic AI workforce, a suite of Agentic workers that automate key client workflows.”
— Adena Friedman, Q4 FY2025

“We embedded AI across our business and have begun rolling out new AI-enabled products with strong client reception.”
— Adena Friedman, Q4 FY2025

“The first Agentic worker we introduced, our Agentic sanctions analyst, has strong early use among our clients.”
— Adena Friedman, Q4 FY2025

“Continuing the momentum this month, we launched our second worker, the Agentic enhanced due diligence analyst.”
— Adena Friedman, Q4 FY2025

“In Corporate Solutions, investments in AI-powered features and tools as well as deep client engagement supported new sales efforts in our governance and Nasdaq Lens solutions.”
— Adena Friedman, Q4 FY2025

“as well as a strong level of investments in growth and innovation, including AI, both in our products and on our business, which we'll discuss in more details at Investor Day.”
— Sarah Youngwood, Q4 FY2025

ANALYST QUESTIONS ON AI

Q (Q1 FY2026, William Katz): So at the Investor Day, I thought you guys did a great job of just sort of debunking some of the concerns around Agentic AI and it seems like there's some really good stats here this morning as well to that score. So maybe a 2-part question. Number one, can you maybe step back and help us frame out the Agentic AI capabilities for the Nasdaq platform itself? And then secondly, can you unpack some of the growth that you saw in the first quarter from clients just in terms of where you see the greatest uptake around Agentic-AI adoption?
A: we do have an internal program to drive AI adoption within the operations of Nasdaq, and we say that's AI on the business. And we are focused in some key areas, and we have a program in place where we are striving to achieve $100 million of expense efficiencies by the end of 2027

Q (Q1 FY2026, William Katz): So at the Investor Day, I thought you guys did a great job of just sort of debunking some of the concerns around Agentic AI and it seems like there's some really good stats here this morning as well to that score. So maybe a 2-part question. Number one, can you maybe step back and help us frame out the Agentic AI capabilities for the Nasdaq platform itself? And then secondly, can you unpack some of the growth that you saw in the first quarter from clients just in terms of where you see the greatest uptake around Agentic-AI adoption?
A: In terms of the areas where our clients are seeing the most benefit from our AI capabilities, anti-fincrime is a key area because we have so many ways to automate workflows associated with financial crime management

Q (Q1 FY2026, Alexander Blostein): I was hoping we can double-click on trends you're seeing in fintech, in particular, in Capital Market stack. Sarah, you highlighted to a couple of drivers this quarter. But given the really strong momentum in ARR even sequentially, I was hoping you can give us a little more detail on where you're seeing the incremental uptake, particularly within cap markets as well as your view for the rest of the year within that segment.
A: we launched an intelligence suite, which we kind of allow our clients, we have it internally. But basically, a modern way for them to manage all their data within their infrastructure. And that's been a really great, I would say, add-on sale to our clients as they're thinking about how they leverage AI they're leveraging us to kind of help them modernize their data management infrastructure.

Q (Q1 FY2026, Elias Abboud): Anthropic's new Mythos model is expected to post significant cybersecurity risks for financial institutions. So as one of the largest bank software vendors, I was wondering if you previewed Mythos and if you can speak to the extent to which the release poses risks or creates liability for Nasdaq. And then separately, does it create any new opportunities? Is bank cybersecurity an interesting adjacency for you? Or is that too far afield from your current business?
A: We're very careful in how we bring new models into Nasdaq. We do leverage Bedrock, which is AWS' AI platform infrastructure to support a lot of our AI infrastructure here at Nasdaq as well as we work with Microsoft and like Azure.