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WireSift Research · AI Adoption Tracker · Q1 2026

SPGIS&P Global Inc.

AI adoption · Q1 2026 earnings call

FinancialsMonetizing
AI mentions
28
extracted from this call
Max specificity
5 / 5
financialized — dollar / segment level
AI revenue
Not disclosed
no breakout in this call
AI was a central theme of the call, with management presenting S&P Global as actively monetizing AI through both embedded product features and new distribution channels including MCP integrations, AI-ready APIs, and partnerships with frontier model providers like Anthropic (Claude). Management provided several concrete data points on AI adoption and early revenue impact, including API call volume growth of 5x quarter-over-quarter, ACV growth among AI customers running 30-100% above non-AI customers, and specific customer examples of 20-45% price premiums for AI-enabled data access. Internally, AI is being deployed across Ratings analytics, research workflows, and data operations, with management noting margin benefits are 'just beginning' with more significant impact expected in 2027-2028.
Public Company AI Adoption Index
Hybrid
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Composite
85/ 100
#1 non-tech · #17 overall · #1 in Financials
Depth · 40%
100
stage: monetizing · max spec: 5
Disclosure · 40%
70
rev: qualitative_only · 10 quant outcomes
Breadth · 20%
85
3 scopes
Adoption scopes:product_embeddedinternal_useproduct_standalone
Every claim, sourced

28 AI mentions from this call.

Extracted verbatim from the SPGI Q1 2026 earnings call transcript. Speaker, section, and specificity tier surfaced for each mention.

  • T5Q&A· CEO· Product-embedded AI
    Analyst questionparaphrased· Morgan Stanley· Toni Kaplan
    I was hoping that you could expand on how you're thinking about the partnership strategy with the large AI players? Are you building SMP, MCP apps on the platforms? Or you just plan to continue to provide the data through the MCP integrations and the APIs? And maybe if you could just talk about the monetization model and directional economics between the different distribution channels.
    one of our buy-side clients working with Kensho was looking at our financial data via at AI-ready API and Kensho helped them to understand how to use the plug-in to perform tasks like creating tearsheets or creating earnings calls previews. And as a result, the clients liked it so much that they actually canceled their existing provider and went with our data and plug-in even though it was about 20% more expensive.
    Martina Cheung, SPGI earnings call
    ProductsKensho, S&P Global plug-in
  • T5Prepared remarks· CEO· Product-embedded AI
    ACV growth among customers who use our AI solutions is outpacing growth from other customers by a wide margin. Growth in Market Intelligence is 30% higher among AI customers compared to others and growth among AI customers and Energy is double the growth rate among other customers.
    Martina Cheung, SPGI earnings call
  • T5Q&A· CFO· Product-embedded AI
    Analyst questionparaphrased· Evercore· David Motemaden
    Are you seeing any meaningful differences in usage patterns or engagement with your data across those two broad channels today? And I guess I'm wondering, as adoption scales, where do you see the balance between direct delivery through your own solutions and third-party large language models ultimately settling out?
    In the clients that have been using our AI tools and availing themselves of those in MI, we're seeing a couple of hundred basis points higher retention rates. In Energy, over 500 basis points of higher retention rates because, again, usage is value for clients.
    Eric Aboaf, SPGI earnings call
  • T5Q&A· CEO· Product-embedded AI
    Analyst questionparaphrased· Morgan Stanley· Toni Kaplan
    I was hoping that you could expand on how you're thinking about the partnership strategy with the large AI players? Are you building SMP, MCP apps on the platforms? Or you just plan to continue to provide the data through the MCP integrations and the APIs? And maybe if you could just talk about the monetization model and directional economics between the different distribution channels.
    in the quarter two financial clients who are just subscribing to our data at renewal, were opting to get that data available in an AI-ready format. And were willing to pay in the range of 35% to 45% on the renewal increase to get the AI access.
    Martina Cheung, SPGI earnings call
  • T4Q&A· CFO· Product-embedded AI
    Analyst questionparaphrased· Evercore· David Motemaden
    Are you seeing any meaningful differences in usage patterns or engagement with your data across those two broad channels today? And I guess I'm wondering, as adoption scales, where do you see the balance between direct delivery through your own solutions and third-party large language models ultimately settling out?
    in iLEVEL, the automated data ingestion through AI is up 2x. And so seeing very significant increases, which we're monitoring in our minds, that's the way clients are gaining value. At the same time, in the -- through the LM channels, the frontier models, the models that our clients have. As we said earlier, call volume is up very significantly, literally 2x from February to March, 5x from December to March.
    Eric Aboaf, SPGI earnings call
    ProductsiLEVEL
  • T4Prepared remarks· CEO· Product-embedded AI
    nearly 150 customers across the Market Intelligence and Energy divisions, were interacting with our data through AI applications like Claude and Copilot. We now have more than 300 customers under contract or in trial periods for Kensho-LLM-ready APIs.
    Martina Cheung, SPGI earnings call
    PartnersAnthropic, Microsoft
    ProductsKensho-LLM-ready APIs
  • T4Prepared remarks· CEO· Product-embedded AI
    in the first quarter, the volume of API calls made by our customers was more than 5x the volume that we saw just 1 quarter ago. Volumes doubled month-over-month just from February to March.
    Martina Cheung, SPGI earnings call
  • T4Prepared remarks· CEO· Product-embedded AI
    More than 1/3 of our CapIQ Pro users engage with the AI features we've launched, including ChatIQ and Document Intelligence.
    Martina Cheung, SPGI earnings call
    ProductsCapIQ Pro, ChatIQ, Document Intelligence
  • T4Prepared remarks· CFO· Product-embedded AI
    the number of user queries in our Energy platforms, ChatAI feature more than doubled quarter-over-quarter.
    Eric Aboaf, SPGI earnings call
    ProductsChatAI
  • T3Prepared remarks· CEO· Standalone AI product
    We unveiled our new AI native Upstream product for data and insights called CERA Titan. As we've discussed with you previously, we are in the process of completely revamping the Upstream business within our Energy division. 70 customers were able to demo the new platform and feedback was overwhelmingly positive. We immediately saw an increase in leads and sales pipeline for Upstream Data & Insights. And one large strategic customer was so pleased with the new platform that we were able to close a large renewal with a meaningful increase in contract value.
    Martina Cheung, SPGI earnings call
    ProductsCERA Titan
  • T3Q&A· CEO· Internal use
    Analyst questionparaphrased· Huber Research Partners· Craig Huber
    I wanted to ask about AI efficiencies at your company. To the extent that you can give us some more examples of how AI internally is helping you guys be more efficient across your various sectors, including outside of the MI division? And also, Eric, I wanted to ask your 50 to 75 basis points expected improvement, excluding OSTTRA, how much ballpark do you think AI efficiencies is actually helping that number?
    we have been tackling AI by looking at some of our largest strategic processes across the company. And so at our IR Day, for example, we mentioned four particular areas that we were focused on, including our Ratings analytic workflows, our research workflows in Energy and in Market Intelligence as well as our technology and data workflows. And these comprise roughly around half of the resources that we have at the company.
    Martina Cheung, SPGI earnings call
  • T3Q&A· CEO· Product-embedded AI
    Analyst questionparaphrased· Evercore· David Motemaden
    Are you seeing any meaningful differences in usage patterns or engagement with your data across those two broad channels today? And I guess I'm wondering, as adoption scales, where do you see the balance between direct delivery through your own solutions and third-party large language models ultimately settling out?
    we have one large global bank that signed an extended contract with us in the first quarter. It included expanding the usage of the Desktop Capital IQ Pro to additional users around the organization. And it also included increasing licensing for AI use of several of our data sets. And the bank actually made our data sets the standard on their own internal LLM
    Martina Cheung, SPGI earnings call
    ProductsCapital IQ Pro
  • T3Q&A· CEO· Product-embedded AI
    Analyst questionparaphrased· Morgan Stanley· Toni Kaplan
    I was hoping that you could expand on how you're thinking about the partnership strategy with the large AI players? Are you building SMP, MCP apps on the platforms? Or you just plan to continue to provide the data through the MCP integrations and the APIs? And maybe if you could just talk about the monetization model and directional economics between the different distribution channels.
    the announcement of the S&P Global plug-in, which was announced in line with the Claude for Financial Services announcement in the first quarter. And that's essentially a series of agents that teach AI agents within the platform, how to actually conduct specific tasks for data, AI-ready data that the client might be licensed to.
    Martina Cheung, SPGI earnings call
    PartnersAnthropic
    ProductsS&P Global plug-in
  • T3Prepared remarks· CEO· Product-embedded AI
    25% of these clients are engaged with our Kensho Labs Technologies to explore opportunities to leverage our technology and data to help solve their most challenging problems.
    Martina Cheung, SPGI earnings call
    ProductsKensho Labs Technologies
  • T3Prepared remarks· CFO· Customer demand signal
    Transactional revenue increased 15%, driven by strength in investment grade, supported by a number of large hyperscaler or M&A transactions in the first quarter.
    Eric Aboaf, SPGI earnings call
  • T2Q&A· CFO· Internal use
    Analyst questionparaphrased· Huber Research Partners· Craig Huber
    I wanted to ask about AI efficiencies at your company. To the extent that you can give us some more examples of how AI internally is helping you guys be more efficient across your various sectors, including outside of the MI division? And also, Eric, I wanted to ask your 50 to 75 basis points expected improvement, excluding OSTTRA, how much ballpark do you think AI efficiencies is actually helping that number?
    AI is just beginning to have some positive impact on margin. I'd say beginning because, remember, AI is just a continuation of machine learning tools and a wide range of capabilities that we've used and leveraged across our processes. I've talked at length about the enterprise data office and what we do in data operations. And so I'll say the predicate to the the new LLM tools have aided the margin expansion over the last year, some into this year. But I think the upside from the broad adoption of Frontier models is just beginning. And really will have an impact in '27, '28 and in the future years
    Eric Aboaf, SPGI earnings call
  • T2Q&A· CEO· Customer demand signal
    Analyst questionparaphrased· Morgan Stanley· Toni Kaplan
    I was hoping that you could expand on how you're thinking about the partnership strategy with the large AI players? Are you building SMP, MCP apps on the platforms? Or you just plan to continue to provide the data through the MCP integrations and the APIs? And maybe if you could just talk about the monetization model and directional economics between the different distribution channels.
    we are really thinking about monetization through the lens of enterprise value. So as you know, we don't do seat-based licensing. We don't do usage only. We track usage, channels, the value we create and a number of other metrics as part of the discussions that we have with our clients on value and price accordingly. And that's going to be true for plug-in. It's going to be true for MCP. It's going to be true for AI-ready data as well.
    Martina Cheung, SPGI earnings call
  • T2Prepared remarks· CEO· Internal use
    We have announced you will see the joining of Firdaus Bhathena as our Chief Technology and Transformation Officer. And Firdaus really as part of that is looking at how we will scale AI and other technologies like quantum and blockchain so that we can actually get the full benefit around the Enterprise. And he will also look at this transformation program that has started with these four strategic
    Martina Cheung, SPGI earnings call
  • T2Prepared remarks· CEO· Product-embedded AI
    we are deploying AI native solutions and tools for those seeking speed and scale on CapIQ Pro, including ChatIQ and Chart Explainer. These features are already driving customer engagement, and we expect many of our customers will continue to consume our content and data primarily through an integrated desktop solution.
    Martina Cheung, SPGI earnings call
    ProductsCapIQ Pro, ChatIQ, Chart Explainer
  • T2Prepared remarks· CEO· Product-embedded AI
    Much of our data is accessible via model context protocol or MCP, and other standard protocols to customers in these environments. Our branded custom business logic and calculation engines as well as many of the tools that exist in Cap IQ Pro will integrate with platforms like Copilot and Claude.
    Martina Cheung, SPGI earnings call
    PartnersMicrosoft, Anthropic
    ProductsCapIQ Pro
  • T2Prepared remarks· CEO· Product-embedded AI
    we are deploying AI native solutions and tools like ChatAI and Document Intelligence for those seeking speed and scale on our platform. For those who want to build their own AI-enabled or Agentic solutions, we are increasingly making our data accessible via standard protocols like MCP.
    Martina Cheung, SPGI earnings call
    ProductsChatAI, Document Intelligence
  • T2Q&A· CFO· Internal use
    Analyst questionparaphrased· Wolfe Research· Scott Wurtzel
    On the Market Intelligence margin, just wondering if you can maybe help contextualize how much of the margin expansion that you're seeing is being driven by efficiency gains associated with AI.
    there's certainly a set of AI benefits that we're getting as we think about our data operations, which is a big part of MI. We see emerging progress or I think I'd say good progress in software development activities that are AI-driven with all the new tools available to it.
    Eric Aboaf, SPGI earnings call
  • T2Q&A· CEO· Customer demand signal
    Analyst questionparaphrased· Baird· Jeffrey Meuler
    Just looking out past the Iranian conflict thinking about your Energy business, how do you expect it to be impacted by the energy complex build-out associated with the data center and AI infrastructure build-out. Just any specific products that you'd expect to benefit any new customer type opportunities.
    we also saw increased issuances from utilities. In the power sector in Ratings. We see demand for additional scenario planning around power and utilities in the Energy team, and we've seen particular demand in the Energy team's unique insights and data on critical minerals.
    Martina Cheung, SPGI earnings call
  • T2Q&A· CEO· Internal use
    Analyst questionparaphrased· Huber Research Partners· Craig Huber
    I wanted to ask about AI efficiencies at your company. To the extent that you can give us some more examples of how AI internally is helping you guys be more efficient across your various sectors, including outside of the MI division? And also, Eric, I wanted to ask your 50 to 75 basis points expected improvement, excluding OSTTRA, how much ballpark do you think AI efficiencies is actually helping that number?
    we can see tremendous capacity expansion within Ratings, for example, where they have been a very early adopter of AI as part of augmenting analytical capacity and making sure that our analysts can do more high-value things like thought leadership and additional research.
    Martina Cheung, SPGI earnings call
  • T2Prepared remarks· CFO· Customer demand signal
    We do expect investment grade to continue to represent a higher mix of issuance compared to historical averages, particularly if we continue to see elevated hyperscale CapEx driving large volumes in the second quarter.
    Eric Aboaf, SPGI earnings call
  • T2Prepared remarks· CFO· Customer demand signal
    some of the strength in issuance in the first quarter was driven by front-end loading of hyperscaler issuance relative to our initial expectations.
    Eric Aboaf, SPGI earnings call
  • T2Prepared remarks· CEO· Customer demand signal
    Investment grade benefited from hyperscaler investments in AI infrastructure.
    Martina Cheung, SPGI earnings call
  • T1Prepared remarks· CEO· Customer demand signal
    the markets are reacting quite aggressively to new AI frontier model headlines, shifts in diplomatic initiatives and the unpredictability of the current environment. That manifests in volatility across the global markets.
    Martina Cheung, SPGI earnings call
Q&A Dynamics

What management wouldn’t quantify.

Analyst questions where management declined to share a specific number. The pattern of refusals is often as informative as the disclosures.

  1. Management did not disclose absolute AI-related revenue or ARR figures, only relative growth differentials between AI and non-AI customers.
  2. No specific capex or R&D spend attributed to AI was disclosed.
  3. When asked directly how much of margin expansion is driven by AI efficiencies (Craig Huber, Huber Research Partners), CFO declined to quantify, saying AI impact is 'just beginning' and more significant in future years.
  4. No disclosure of the number of total CapIQ Pro users, making the '1/3 engagement' figure difficult to size in absolute terms.
  5. No disclosure of revenue contribution from Kensho or AI-specific product lines as a standalone segment.
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Sourced from primary documents · See the methodology for the extraction approach.