{
  "review": {
    "as_of": "2026-10-24",
    "run": "slb-data-ai-2026-10-24",
    "label": "24 October 2026 / SLB deep dive",
    "headline": "What is SLB’s data worth in the AI era?",
    "intro": "The investment case becomes more useful when you separate data access, model capability and the money customers actually pay.",
    "count_note": "Existing SLB platform dossier expanded. No new initiative, adoption or customer-result count. Digital financial results are broader than AI.",
    "method": "Editor checked original SLB investor scripts, full-year and quarterly financial tables, and public online-service terms. Investor opinion is identified separately. An exact Eisman passage remains unconfirmed. This is a targeted assessment, not a valuation or a full contract audit.",
    "featured_count": 1,
    "archive_label": "Earlier source reviews and company context",
    "findings": [
      {
        "id": "SLB-DATA-AI-THESIS",
        "company": "SLB",
        "record": "AI-009",
        "related_ids": [
          "AI-009",
          "AI-008",
          "AI-047",
          "AI-105",
          "AI-301"
        ],
        "sources": [
          {
            "id": "SLBTH-Q3",
            "title": "SLB third-quarter 2026 results — Digital economics and category definitions",
            "url": "https://investorcenter.slb.com/news-releases/news-release-details/slb-announces-third-quarter-2026-results",
            "date": "2026-10-23",
            "publisher": "SLB",
            "locator": "Digital results; Supplementary Information questions 10–13; Digital customer highlights.",
            "excerpt": "$693 million decreased 1% sequentially",
            "type": "Supplier earnings release",
            "access": "Editor read the accessible original publisher text on 24 October 2026. Statements remain publisher-reported; no independent performance validation."
          },
          {
            "id": "SLBTH-FY25",
            "title": "SLB full-year 2025 results — Digital financial baseline",
            "url": "https://investorcenter.slb.com/news-releases/news-release-details/slb-announces-fourth-quarter-and-full-year-2025-results",
            "date": "2026-01-23",
            "publisher": "SLB",
            "locator": "Supplementary Information question 12, Digital FY2025 table.",
            "excerpt": "Digital revenue increased 9% on a full-year basis",
            "type": "Supplier earnings release",
            "access": "Editor read the accessible original publisher text on 24 October 2026. Statements remain publisher-reported; no independent performance validation."
          },
          {
            "id": "SLBTH-MENON",
            "title": "Shashi Menon: The Race to Scale Digital Operations and AI",
            "url": "https://investorcenter.slb.com/static-files/cf773c3d-348f-479f-aeb0-81f5418844ca",
            "date": "2026-06-17",
            "publisher": "SLB",
            "locator": "PDF pp. 3–5: data access and control; p. 11: seismic training; pp. 14–15: monetization.",
            "excerpt": "we trained it with public and SLB multiclient seismic data sets",
            "type": "Investor presentation and prepared script",
            "access": "Editor read the accessible original publisher text on 24 October 2026. Statements remain publisher-reported; no independent performance validation."
          },
          {
            "id": "SLBTH-BIGUET",
            "title": "Stephane Biguet: Proven Growth. Accretive Returns.",
            "url": "https://investorcenter.slb.com/static-files/0835f6dc-d2fb-4bc0-b85e-afecadcf36fe",
            "date": "2026-06-17",
            "publisher": "SLB",
            "locator": "PDF p. 4: customer base; pp. 7–10: commercial models; p. 11: 2030 ambitions.",
            "excerpt": "more than 1,500 customers, including 90 of the world’s top 100 oil and gas producers",
            "type": "Investor presentation and prepared script",
            "access": "Editor read the accessible original publisher text on 24 October 2026. Statements remain publisher-reported; no independent performance validation."
          },
          {
            "id": "SLBTH-TERMS",
            "title": "SLB Online Services Terms and Conditions",
            "url": "https://www.software.slb.com/slb-online-services-terms-and-conditions",
            "date": "Unknown",
            "publisher": "SLB",
            "locator": "Definitions: Customer Data and Interaction Data; sections 8(a)–(b), 9(a), 10(a).",
            "excerpt": "SLB claims no ownership rights in Customer Data.",
            "type": "Published online-service terms",
            "access": "Editor read the accessible original publisher text on 24 October 2026. Statements remain publisher-reported; no independent performance validation. Effective/publication date unknown. Public standard terms do not establish the terms of every negotiated customer agreement."
          },
          {
            "id": "SLBTH-GENAI",
            "title": "SLB Online Services Service Specific Terms",
            "url": "https://www.software.slb.com/slb-online-services-service-specific-terms",
            "date": "Unknown",
            "publisher": "SLB",
            "locator": "Generative AI Services: definitions; Connected Gen AI A(i), A(iv); Embedded Gen AI B(iii).",
            "excerpt": "SLB shall not use Customer Prompts or Output to train models or further develop the Online Services without Customer’s consent.",
            "type": "Published online-service terms",
            "access": "Editor read the accessible original publisher text on 24 October 2026. Statements remain publisher-reported; no independent performance validation. Effective/publication date unknown. Public standard terms do not establish the terms of every negotiated customer agreement."
          },
          {
            "id": "SLBTH-MULLIN",
            "title": "Robert Mullin interview: 3.5% of the S&P, 20% of the Cash",
            "url": "https://georgenoble.substack.com/p/35-of-the-s-and-p-20-of-the-cash",
            "date": "2026-10-20",
            "publisher": "The Noble Update",
            "locator": "Host introduction and linked interview; exact SLB interview timestamp not established.",
            "excerpt": "The oil service giant hiding a real AI business that could be worth more than the whole company",
            "type": "Investor opinion / interview",
            "access": "Original host introduction reviewed; confirms the investment framing and interview identity. Full interview passage and exact timestamp not independently checked. An Eisman episode containing the same argument remains unconfirmed."
          },
          {
            "id": "SLBTH-RANNEN",
            "title": "Trygve Randen: Our Digital Advantage",
            "url": "https://investorcenter.slb.com/static-files/7aa731c6-2f38-47e4-9aa2-473a8d04ec6e",
            "date": "2026-06-17",
            "publisher": "SLB",
            "locator": "PDF pp. 2–3: governed platforms; pp. 5–6: hosting and trust; p. 7: operational footprint.",
            "excerpt": "more than ninety percent of global production is simulated or modelled using at least one of our digital solutions",
            "type": "Investor presentation and prepared script",
            "access": "Editor read the accessible original publisher text on 24 October 2026. Statements remain publisher-reported; no independent performance validation."
          }
        ],
        "date": "2026-10-23",
        "source_id": "SLBTH-MENON",
        "source_title": "Shashi Menon: The Race to Scale Digital Operations and AI",
        "url": "https://investorcenter.slb.com/static-files/cf773c3d-348f-479f-aeb0-81f5418844ca",
        "publisher": "SLB",
        "locator": "PDF pp. 3–5: data access and control; p. 11: seismic training; pp. 14–15: monetization.",
        "excerpt": "we trained it with public and SLB multiclient seismic data sets",
        "source_type": "Original investor materials, financial disclosures and public terms",
        "title": "What holds up in SLB’s data and AI investment thesis?",
        "status": "Existing commercial platform; investor valuation argument remains unproven",
        "department": "IT, data & enterprise transformation",
        "summary": "SLB has a credible route to earning more from AI: it can put specialized models into software and operating workflows that customers already use. The public evidence supports a platform, engineering and governed-access advantage. It does not support treating every customer’s downhole data as an unrestricted SLB-owned training pool.",
        "mechanism": "Menon describes a seismic model trained on public and SLB multiclient datasets, with customers able to fine-tune for their own assets. Lumi connects governed data; domain models handle technical formats; Tela provides interaction and workflow orchestration. SLB describes subscription upgrades, metered usage, tailored workflows and marketplace revenue sharing. These are commercial mechanisms, not disclosed AI-only earnings.",
        "measure": "FY2025 Digital revenue was $2.660bn and adjusted EBITDA $928m (34.9% margin). Q3 2026 Digital revenue was $693m, adjusted EBITDA $228m and ARR $1.04bn. These are division-wide figures, not AI revenue or customer ROI. The CFO’s 2030 $1.8–2.0bn adjusted EBITDA and approximately $2bn ARR are ambitions, not results.",
        "operating_period": "Original investor-day scripts: 17 June 2026. FY2025 baseline released 23 January 2026; Q3 results released 23 October 2026. Terms dates unknown. Investor interview framing published 20 October 2026.",
        "limit": "SLB disclaims ownership of Customer Data in its published online-service terms, while allowing specified service/product-improvement uses. Embedded Gen AI prompts and outputs require customer consent for training. Those clauses do not settle rights to every historical field dataset, derivative or negotiated contract. Digital includes software, operations, data licensing and professional services, with no AI-only profit bridge. Digital Operations overlaps Core segment reporting and is eliminated in consolidation. No demonstrated undervaluation or complete customer net cash ROI follows from these disclosures.",
        "question": "Ask for AI-specific paid usage and retention, incremental profit after compute and support, training rights by data category, held-out-basin model performance, customer-specific control boundaries, and a valuation using post-elimination earnings. For the full evidence map and interactive revenue chart, read the SLB briefing linked from the homepage.",
        "problem": "Evaluate whether SLB can convert specialized data, technical software and customer reach into durable incremental AI earnings.",
        "ai_role": "Technical domain models plus general LLMs and agents; not a single text model trained without restriction on all downhole data.",
        "human": "Presentation describes engineering recommendations under human control and more autonomous workflows under physical constraints. It does not establish one common approval boundary for every customer deployment.",
        "asset": "Global Digital business; named operating cases retain their own asset and evidence boundaries.",
        "partner": "SLB, customer operators and technology partners; no new partner adoption count.",
        "baseline": "Segment accounts are not AI-only economics. No pooled value or return estimate is admitted.",
        "category": "Data rights and commercial AI strategy",
        "relationship": "Expanded existing Lumi dossier and analytical context; no new initiative, operator adoption or reported-result count.",
        "core_company": true,
        "technology_note": "SLB-DATA-AI-THESIS",
        "technology_label": "Read the source review"
      }
    ]
  },
  "economics": {
    "unit": "USD millions",
    "source_id": "SLBTH-Q3",
    "scope": "Digital division, as reported; includes non-AI business",
    "periods": {
      "q3": {
        "label": "Q3: July–September",
        "years": [
          "2025",
          "2026"
        ],
        "values": [
          [
            273,
            131,
            80,
            174
          ],
          [
            299,
            163,
            78,
            153
          ]
        ],
        "totals": [
          658,
          693
        ]
      },
      "nine": {
        "label": "Nine months: January–September",
        "years": [
          "2025",
          "2026"
        ],
        "values": [
          [
            774,
            302,
            253,
            507
          ],
          [
            797,
            454,
            306,
            474
          ]
        ],
        "totals": [
          1836,
          2030
        ]
      }
    },
    "categories": [
      "Platforms & Applications",
      "Digital Operations",
      "Digital Exploration",
      "Professional Services"
    ],
    "limits": "Reported totals may differ from category sums because of rounding. As-reported growth includes ChampionX; it is not organic or AI-only growth. Digital Operations revenue also appears in Core segments and is eliminated at group consolidation. ARR is a different measure and must not be added to revenue.",
    "fy2025": {
      "revenue": 2660,
      "adjusted_ebitda": 928,
      "margin": 34.9,
      "source_id": "SLBTH-FY25"
    },
    "ambition2030": {
      "adjusted_ebitda_low": 1800,
      "adjusted_ebitda_high": 2000,
      "arr": 2000,
      "source_id": "SLBTH-BIGUET",
      "status": "Management ambition, not realized or discounted"
    }
  }
}