Strategy & Finance

S&P Global: AI, data and the customer interface

Topic
Customer Strategy, Platform Strategy, Growth Strategy
Industry
Financial Exchanges & Data
Internal ID
S&F-STR-488
Source
Strategy & Finance
Publication date
Pages
5
License
Not specified

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Strategy case for MBA students and working professionals
Information cutoff: October 3, 2026

The investor’s question

S&P Global had entered a new chapter. On July 1, 2026, it separated its Mobility division into Mobility Global, leaving Ratings, Indices, Energy and Market Intelligence as its four operating segments. At the same time, the company was investing in artificial intelligence, adding AI features to Capital IQ Pro, and opening new ways for customers to access its data through cloud and large-language-model partners.

For an outside investor, the strategic question is how to interpret those moves. Could AI make S&P Global’s data and specialized workflows more useful—and support continued paid use of its products? Could the same technology make information collection and analysis cheaper for competitors and customers, shifting the customer interface to third-party platforms? Both forces could operate at once.

Consider two lenses for assessing the strategy. A platform-centered approach would emphasize differentiated S&P products that combine its data, research and analytics with AI tools. A broader-distribution approach would emphasize feeds, APIs, cloud partnerships and access through external AI platforms. These are investor lenses, not options that management has said it is choosing between. S&P has publicly pursued elements of both.

Your task is to assess what the evidence supports about the durability of S&P Global’s post-Mobility growth strategy. Which evidence would strengthen or weaken your confidence? What should investors monitor to distinguish product activity from commercial results?

A company built around information and workflows

S&P Global supplies credit ratings, market indices, commodity prices, company and financial data, analytics and software. Its products serve financial-market participants and corporate, government and academic users. Market Intelligence combines data and analysis with products such as Capital IQ Pro, feed and API delivery, valuation services, enterprise software and ratings-related information.

The company reports three revenue categories in Market Intelligence. Subscription revenue includes access to data, analytics, research, ratings-related information, software and hosted products. Recurring variable revenue depends on contract measures such as trades processed, assets under management or positions valued. Non-subscription revenue includes advisory, events and analytical services. These categories describe how revenue is contracted and earned; they do not identify which products use AI or whether AI caused growth.

In 2025, S&P said it had invested more than $1 billion in AI, including its earlier Kensho acquisition. It said it formed partnerships in cloud and large-language-model ecosystems and had received a “very positive response” to Automated Data Ingestion on iLevel and Document Intelligence on Capital IQ. In March 2026, it announced more content and AI capabilities for Capital IQ Pro, integrating ProntoNLP sentiment analysis and acquiring Drift AI with a planned integration. The company’s second-quarter release described continued rapid adoption and expansion of AI solutions.

Those statements show investment and product activity. The materials do not disclose AI-specific revenue, paid adoption, usage, price realization, renewal or churn, customer productivity, or the return on AI investment. “Positive response” and “rapid adoption” are not defined with customer or revenue measures.

Reading the second-quarter results

Mobility’s separation creates a reporting break. S&P’s second-quarter Form 10-Q includes Mobility through June 30. Its July earnings release reported consolidated GAAP Q2 revenue of $4.146 billion, up 10%, including Mobility. It separately presented $3.678 billion of Q2 Article 11 pro forma revenue excluding Mobility, up 11%. The pro forma presentation is unaudited and illustrative; it uses management estimates and updated segment composition and cost-allocation methods. It is not interchangeable with reported GAAP results or proof that the same results would have occurred historically.

Segment / company measure Q2 2026 evidence What it does and does not show
Market Intelligence revenue $1.290bn, +6% Subscription revenue was $1.076bn (+6%), 83% of the segment; recurring variable revenue was $173m (+9%); non-subscription revenue was $41m (−1%).
Ratings revenue $1.339bn, +17% Transaction revenue was $746m (+25%); non-transaction revenue was $593m (+8%). Billed issuance grew 25%.
Indices revenue $568m, +2% Subscription revenue grew 4%; sales usage-based royalties fell 9%. Asset-linked fees in the consolidated revenue table rose 22%, reflecting fees primarily tied to client fund assets.
Consolidated reported GAAP revenue $4.146bn, +10% Includes Mobility through June 30.
Consolidated Article 11 pro forma revenue, excluding Mobility $3.678bn, +11% Unaudited and illustrative; reflects changed allocations and business composition.
Consolidated Article 11 pro forma operating profit $1.757bn, +21% Excludes Mobility; this is not the sum of segment operating profit.
Consolidated pro forma non-GAAP adjusted operating profit $1.998bn, +15% Adjusted for the company’s specified items; not GAAP operating profit.

Market Intelligence’s second-quarter revenue growth was aided by less than one percentage point from the net effect of recent acquisitions and a disposition. Management attributed the remaining growth primarily to subscriptions in Data, Analytics & Insights, Lending Solutions and RatingsXpress, as well as higher recurring-variable volumes. The With Intelligence and ORBCOMM AIS acquisitions supported reported revenue; the January sale of Enterprise Data Management and thinkFolio reduced it. The segment’s reported operating profit also includes acquisition amortization, severance, disposition-related items and a required labor-law accrual adjustment.

Ratings’ transaction business depends in part on debt issuance. The company attributed Q2 investment-grade issuance growth partly to AI-related financing and M&A, and high-yield growth partly to M&A. This market issuance is not growth from selling S&P’s own AI products. Indices revenue also has exposure to client fund assets, derivatives activity, subscriptions and usage-based royalties. These drivers can move independently of Market Intelligence adoption.

Segment operating profit is the company’s measure before Corporate Unallocated expense and equity in income on unconsolidated subsidiaries. It differs from consolidated operating profit. The company’s adjusted measures exclude specified items and are non-GAAP. Margin comparisons can also reflect allocation changes around the Mobility spin. An investor therefore needs to separate the segment trend, the consolidated reported result, the Article 11 pro forma view and management’s adjusted measures.

Competition and the broader AI environment

S&P’s annual report identifies competitive risk from both traditional providers and nontraditional companies, including some customers that are adding data and analytics to their own products. It also says that AI could let competitors collect and process information at low or no cost, and that off-the-shelf models could make it easier to build competing applications. S&P notes that its AI-enabled products may rely on third-party data, software and AI providers. New products may not achieve expected customer acceptance or profitability.

Competitors are also combining data, analytics and AI. Moody’s announced OneView, an AI-enabled platform combining data, analytics and research, and described integrations with major AI and cloud providers. FactSet announced a Google Cloud partnership to embed Google Search and Gemini capabilities into Workstation. These are company announcements, not independent or comparable evidence of customer adoption, price, performance or return.

Academic evidence

Research suggests that information firms can create value by checking, standardizing and distributing information—not only by owning raw data. Nic Schaub studied more than 100,000 First Call earnings announcements from 1995–2011. In the paper’s main specifications, earnings news disseminated with delay had a 20.7% weaker two-day abnormal announcement response and 61.0% stronger post-announcement drift than immediately disseminated news. A timing-based test found part of the later reaction clustered around dissemination. The study concerns an earlier earnings-news service and market reactions; it does not measure customer willingness to pay, S&P product retention or AI returns. Its estimates should not be applied to S&P Global.

An, Benetton and Song studied U.S. equity ETF index licensing. Their structural analysis estimated that about 60% of index license fees were markups and that a perfect-competition counterfactual could reduce ETF management fees by about 30%. Those are model-based estimates from an ETF market, with selective voluntary fee disclosure; they are not estimates of S&P’s total Indices economics or current customer pricing. Together, these studies point to possible value from trusted information and brands, while leaving open how much of that value is captured, how durable it is, and how technology changes the economics.

Questions for discussion

  1. Which investor lens—platform-centered differentiation or broader distribution—best explains S&P Global’s disclosed strategy? Can both reinforce one another, or could they create tensions?
  2. How much confidence should an investor place in the company’s AI adoption claims given what it does and does not disclose?
  3. Which parts of Q2 2026 growth appear recurring, cyclical, asset-linked, acquisition-related or affected by the Mobility reporting break?
  4. What evidence would distinguish AI-driven customer value from general subscription growth, issuance recovery, AUM growth, FX or portfolio changes?
  5. What indicators should investors monitor over the next several reporting periods to test whether AI improves retention and pricing or weakens S&P’s control of the customer relationship?

Sources

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