Every company a scout has read against the five things that compound in an AI application business — the customer relationship, the proprietary data, the evals, the workflow and a domain-specific model — each banded owns / partial / none / unknown with its own citation, and each dated.
Beside those five, each card carries AI adoption depth — banded deep / moderate / shallow / unknown, cited the same way. It is a paired axis, not a sixth band: the five ask whether the value would accrue to this company if the thesis works, and this asks whether it is working at all. It is never counted in the “owns of 5” line and the two are never added together — a company can own neither its data nor its model and still run one of the deepest deployments anywhere. Where no reading has been made, the card says so plainly instead of guessing at one.
Grouped by vertical, alphabetical by name within it. The counts are a pattern, not a ranking and not a score: owning five together differs in kind from being excellent at three, which no single number expresses. unknown means nobody found the evidence, not that the answer is no. Weightless — nothing on this page ever reaches a signal, and none of it is a forecast of returns.
13 of 198 companies covered. Scouting is manual and condition-led, so the other 185 carry no profile — an absence of research, never a verdict of “owns none”.
Customer support
Scouted against the condition: a company that simultaneously owns the customer relationship, the data, the evals, the workflow, and a domain-specific model
Salesforce reported $1.2 billion of Agentforce annual recurring revenue for the quarter ended April 30, 2026, up 205% year over year, inside nearly $3.4 billion of combined Agentforce and Data 360 ARR. Usage carries the evidence: 3.8 billion Agentic Work Units delivered to date across Agentforce and Slack, up 111% quarter over quarter, and 28.6 trillion tokens processed to date, up 152%. Chair and CEO Marc Benioff described Agentforce as powering every Customer 360 application across tens of thousands of businesses. Headroom sits in the same release: more than half of Agentforce and Data 360 bookings came from existing customers, and that $1.2 billion runs against full-year FY27 revenue guidance of $45.9 billion to $46.2 billion. source: sec.gov
Salesforce owns the enterprise relationship and the workflow surface outright, and holds partial positions on data, evaluation and models. The pattern is a company that owns where the work happens and who it is sold to, while the reasoning layer it runs on is largely bought.
Salesforce contracts directly with the enterprise: the FY26 10-K states it sells "to businesses worldwide, primarily on a subscription basis, through our direct sales efforts and also indirectly through partners," with subscription periods "typically 12 to 36 months." The direct sales motion, the contracting counterparty and the multi-year renewal cycle put Salesforce rather than an intermediary at the centre of the relationship, and the partner channel is disclosed as secondary. The product also reaches the enterprise's own end customers: "Our Agentforce Service offering enables companies in every industry to bring all of their customer, employee, IT and field service needs onto one integrated, AI-powered platform to deliver trusted, highly personalized customer support at scale." source: sec.gov
The corpus Agentforce reasons over is the customer's own tenant data, retrieved at run time rather than owned. The Einstein Trust Layer "takes any direct merge fields inside of the prompt and grounds it with record data from Salesforce," via Flow data providers and Data Cloud retrievers, substitutes "a designated placeholder" for PII, and commits that "This 'zero retention' architecture ensures that customer data is never stored outside of Salesforce" — contracting away cross-tenant learning. The FY26 10-K discloses no training or fine-tuning on customer data. What Salesforce holds is the CRM schema and metadata model plus the unification and residency layer: structure and custody, not an owned corpus. The 112 trillion records Data 360 ingested in FY26, up 114% Y/Y, measure that custody volume. source: developer.salesforce.com
Salesforce AI Research publishes its own benchmark, CRMArena-Pro ("Holistic Assessment of LLM Agents Across Diverse Business Scenarios and Interactions," 24 May 2025), covering "nineteen expert-validated tasks across sales, service, and 'configure, price, and quote' processes" with "multi-turn interactions guided by diverse personas and robust confidentiality awareness assessments." It reports that "leading LLM agents achieve only around 58% single-turn success on CRMArena-Pro, with performance dropping significantly to approximately 35% in multi-turn settings." The dataset is released under cc-by-nc-4.0 for "research purposes only in support of an academic paper," no in-product pass/fail bar or grader set is publicly reachable, and outside labs do not measure themselves against it. source: arxiv.org
The work happens inside Salesforce's own objects. The FY26 10-K states that "Agentforce is infused across every Salesforce application, so intelligence is embedded directly into the workflows where work actually happens. Instead of switching between tools, people can collaborate with agents inside and across the systems they already use every day." It adds that agents "can access live business data through Data 360, follow company policies defined in Salesforce metadata, and take action through Salesforce applications and MuleSoft Application Programming Interfaces ('APIs')," with "deterministic business logic, workflows, and policies" instantly accessible without rebuilding existing processes. Slack sits inside the same perimeter, at $8,882M FY26 subscription revenue in its segment. source: sec.gov
Salesforce AI Research trains real domain models — the xLAM action and function-calling family and xGen — and the company says of xLAM that "A significantly more advanced, proprietary version is powering Agentforce," describing xGen-Sales as "a proprietary model trained and designed to power autonomous sales tasks with Agentforce." The reasoning and generation layer is bought: the default is "a managed mix of trusted models (currently including GPT-4o) optimized by Salesforce," and every selectable model is external — GPT-4o through GPT-5.x and o3/o4-mini, Anthropic Claude via Bedrock, Gemini via Vertex, Amazon Nova, NVIDIA Nemotron — plus bring-your-own-LLM. The proprietary claim rests on the filing's own characterisation from September 2024; the FY26 10-K names no such model. source: salesforce.com
ServiceNow's AI business crossed $1 billion in annual contract value in the second quarter of 2026, and the company reported that agentic deployments of ServiceNow AI rose ninefold over the preceding nine months. The footprint is broad rather than confined to lighthouse accounts: nearly all 50 U.S. states run the ServiceNow AI Platform, with state agencies citing outcomes such as a 66% service desk cost reduction, and the quarter closed with 658 customers above $5 million in annual contract value. Set against quarterly subscription revenues of $3,877 million, that $1 billion AI base remains a modest slice of the installed estate; management's Financial Analyst Day target of 30% of ACV from AI by 2030 measures how much of its own customer base it treats as unconverted. source: sec.gov
ServiceNow owns the customer relationship, the workflow execution layer and the evaluation standard for agents on its platform, and the economics reflect it: $13.28B FY2025 revenue at 97% subscription, $28.2B RPO up 27%, and 603 customers above $5M ACV against a roughly flat ~8,700 logo base. The softer dimensions are data, where a multi-instance architecture keeps the operating corpus per-tenant by design, and models, where in-house LLMs stay available but lose the default inference path to third-party providers from July 2026.
ServiceNow sells directly: "We sell our products and services to enterprises across a wide variety of industries through subscription agreements facilitated by our global direct sales organization," and "As of December 31, 2025, we had approximately 8,700 customers across a wide variety of industries." The relationship is quantified, not asserted — "Revenues from our direct sales organization represented 78% of our total revenues for each of the years ended December 31, 2025 and 2024." The remaining ~22% is indirect: "We also sell through managed service providers and resale partners," plus integrator ties with "Accenture, Cognizant, Deloitte, EY, Infosys and KPMG," and a risk factor noting "we and our customers rely on our partners to provide professional services, including custom implementations." source: sec.gov
The operating corpus is per-tenant customer data that ServiceNow deliberately does not centralize: "We operate a multi-instance architecture that provides each customer with a dedicated application layer and database," and Workflow Data Fabric works by "connecting to real-time external data without copying or moving the data from its source." What ServiceNow does own is structure rather than corpus — the CMDB, workflow schema and process taxonomy — plus first-party telemetry from the "Now on Now" program, which the filing describes as using "our own products to collect real-time feedback on new and existing features," a product-feedback loop rather than a training corpus. The filing discloses no cross-customer aggregated training set. On that evidence this sits at the generous end of partial. source: sec.gov
WorkArena is a peer-reviewed artifact, not a product name: "a remote-hosted benchmark of 33 tasks based on the widely-used ServiceNow platform" measuring agents on "the typical daily work of knowledge workers utilizing enterprise software systems," by 12 ServiceNow Research staff, shipped with BrowserGym as a "unified testing ground for MiniWob, WebArena, WorkArena" (arXiv 2403.07718; ICML 2024, PMLR v235). ServiceNow also gates production models: "all integrated models are regularly evaluated on Platform-representative data," "models vetted for reliability and performance," and "ServiceNow product teams test and validate OOTB skills against the assigned third-party provider before any default changes." The scope limit is real: this defines good on and for the ServiceNow platform, not an industry-wide support standard. source: servicenow.github.io
The 10-K frames the platform as the execution layer AI models lack: they "cannot independently execute transactions, route approvals, update systems of record, or support compliance with business rules and regulatory requirements. Our platform addresses this fundamental gap by providing the underlying infrastructure that connects AI-generated insights to the operational systems and processes where work actually gets done," and "AI agents developed using our solutions follow a human-in-the-loop governance model." Subscription revenues were $12,883M of $13,278M total — 97% of revenue, growing 21%; the auditor cites "subscription revenues of $12.9 billion for the year ended December 31, 2025." The moat rests on "expertise in the operational processes specific to different industries, functional areas and user roles." source: sec.gov
ServiceNow offers its own models but is moving them off the default inference path: "Beginning July 9, 2026, ServiceNow will begin rolling out third-party model providers as the default for out-of-the-box (OOTB) Now Assist skills and AI agents," and "If you've set the Now LLM Service as your instance level model provider, we recommend starting the process of getting at least one third-party model provider approved." Any skill "still running OOTB default of Now LLM Service will switch to the new third-party defaults when you update," against a table of "deprecation targets, and retirement targets." In-house models remain selectable — "organizations can choose to leverage ServiceNow's language models or integrate third-party or proprietary models" — but third-party providers are becoming the defaults. source: servicenow.com
