Data & Trust Alliance

What Data & Trust Alliance does

Data & Trust Alliance (D&TA), legally known as Data & Trusted AI Alliance, is a 501(c)(3) non-profit consortium founded in September 2020 and operated as a subsidiary of the Center for Global Enterprise in New York. The organization is CEO-led, with co-chairs Ken Chenault (former American Express CEO, General Catalyst chairman) and Sam Palmisano (former IBM CEO, CGE chairman), Executive Chairman Jon Iwata, and Executive Director Saira Jesani. D&TA develops operational practices, standards, and frameworks — not technology products — to advance the responsible deployment of data and AI across enterprises. Its core deliverables include the Data Provenance Standards (22 metadata fields across Source, Provenance, and Use categories, now stewarded by OASIS Open), the AI Vendor Assessment Framework (8-category procurement evaluation tool), Algorithmic Bias Safeguards (55-question workforce bias scorecard), the Cyber Readiness Companion, an M&A due diligence toolkit, and policy recommendations developed in collaboration with partners such as NACD.

The alliance serves large enterprises deploying data and AI in business operations, alongside business and procurement leaders evaluating AI vendors, HR teams assessing algorithmic bias in workforce tools, and policymakers shaping AI governance. D&TA is funded exclusively through membership fees from 26 member companies spanning 17 industries — including AARP, AMD, AT&T, Best Buy, Chevron, Deloitte, General Catalyst, GM, IBM, Johnson & Johnson, Mastercard, Meta, Nielsen, Nike, Pfizer, Salesforce, UPS, Walmart, and Warby Parker — with a combined $1.8T in annual revenues, $4.8T+ market capitalization, and 4M+ employees. All tools, frameworks, and standards are published freely for practitioner adoption, with adoption (rather than revenue) as the organization's stated sole KPI. Distribution occurs through direct website download, GitHub technical resources, strategic partnerships with standards bodies (OASIS Open, EDM Council, NACD), and member-driven adoption within enterprise procurement ecosystems.

Name

Data & Trust Alliance

Legal name

Data & Trusted AI Alliance

Website

https://dataandtrustalliance.org

Company type

Private

Founded year

2020

Operating status

Operating

Headcount range

1–10 employees

Short description

Data & Trust Alliance is a 501(c)(3) non-profit consortium of 26 CEOs from Fortune 500 enterprises across 17 industries that develops free standards, frameworks, and governance tools — including the Data Provenance Standards and AI Vendor Assessment Framework — to advance responsible data and AI deployment, funded exclusively through membership fees.

Ownership category

akta.pro rank

Product category

AI and Data Governance Standards

SIC

Services-Membership Organizations (8600)

akta.pro primary industry

Ethical Data Sourcing, Consent & Data Provenance (HDAAAMAI)

akta.pro secondary industries

Audit, Explainability & Accountability Tooling (traceability, reporting) (HDAAAKAL), Responsible AI, AI Governance & Compliance Services (BPAEAHAJ), Bias, Fairness & Representativeness Testing for Datasets (HDAAALAK), Data Governance Platforms (Policies, Stewardship, Workflows) (HDAEADAB)

Keywords

• Data governance standards
• AI vendor assessment
• Algorithmic bias safeguards
• Data provenance metadata
• Responsible AI policy

Headquarters

HQ city

New York

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2B

Offering type

Services

Cost components

Personnel, Operations, Technology or R&D, Marketing or Sales, Others

Revenue model

1. Membership Fees: The Data & Trust Alliance is funded exclusively through membership fees from its 26 member companies. As a 501(c)(3) subsidiary of the Center for Global Enterprise (CGE), the organization does not generate revenue from product sales. All tools, frameworks, and standards are developed for free adoption by practitioners.

Go-to-market motion1 record

Distribution channels5 records

Marketing channels9 records

Core offering

Data & Trust Alliance is a CEO-led non-profit consortium that develops and publishes cross-industry standards, frameworks, and governance tools for the responsible use of data and AI. Its core deliverables include the Data Provenance Standards (22 metadata fields for dataset transparency), the AI Vendor Assessment Framework (8-category procurement evaluation tool), the Algorithmic Bias Safeguards (55-question scorecard for HR and procurement), the Cyber Readiness Companion, and policy recommendations for AI governance. All tools and frameworks are provided free of charge to practitioners and are funded entirely through membership fees from 26 member companies.

Product overview

Data & Trust Alliance (D&TA) is a nonprofit consortium that develops practical frameworks, standards, and tools rather than a traditional product company. Their portfolio centers on three core offerings: Data Provenance Standards (cross-industry metadata standards for dataset transparency), the AI Vendor Assessment Framework (procurement tool for evaluating AI vendors on risk and value), and Algorithmic Bias Safeguards (workforce decision evaluation criteria). These are complemented by supplementary tools like the Cyber Readiness Companion, policy documents including Policy Recommendations and Board Governance guidance developed with NACD, and technical resources including a metadata generator and GitHub repository. The organization operates on an adoption-focused model, providing free tools developed by practitioners across 26 member companies spanning 17 industries.

Differentiator

Problem solved

Functional benefit

Products and services

• Data Provenance Standards Cross-industry metadata standards bringing transparency to the origin of datasets. Version 1.0.0 comprises 22 metadata fields grouped into Source (6 fields), Provenance (9 fields), and Use (7 fields), designed for both traditional data and AI applications.
• AI Vendor Assessment Framework (VAF) Structured procurement tool for evaluating AI vendors during the buying process, balancing risk assessment with business value across eight categories: Privacy & Data Protection, Model Development & Explainability, Intellectual Property & Content Rights, Regulatory Compliance & Ethical Alignment, Performance & Reliability, Integration & Technical Risk, Vendor Stability & Support, and Cost & Value Realization.
• Cyber Readiness Companion to the AI Vendor Assessment Framework Companion guide showing how the AI Vendor Assessment Framework can be used to assess AI vendor security maturity; highlights how framework questions surface security considerations and provides guidance for identifying vulnerabilities and mitigating risk during AI adoption.
• Algorithmic Bias Safeguards Criteria and education for HR and Procurement teams to evaluate vendors on their ability to detect, mitigate, and monitor algorithmic bias in workforce decisions. Includes 55 questions in 13 categories covering training data, model design, bias testing, remediation, transparency, and accountability.
• Responsible Data & AI Diligence for M&A Due diligence tool helping M&A teams assess value and risk when acquiring AI startups; covers algorithmic discrimination, model transparency, data rights, IP considerations, and how organizational culture serves as an indicator of future value.
• Data Provenance Standards Metadata Generator

Quantifiable outcome

• Data scientists spend 35-46% of time on data preparation; standards can reduce this by establishing clear provenance documentation
• +4 more outcomes

Named customers11 records

Segments3 records

Ideal customer profiles3 records

Technology focussed No

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Feature4 records

Partnerships

Nine partnerships are on record, tiered core and important.

• Alfaisal UniversitycoreStrategic or Co-development Partner · 28 January 2026Partnered with D&TA to pilot data provenance standards in a regulatory sandbox for AI-enabled healthcare in Saudi Arabia. Demonstrated how international provenance standards can be localized to certify metadata across institutional boundaries while maintaining compliance with Saudi data localization laws and Personal Data Protection Law (PDPL).
• SDM DiagnosticscoreStrategic or Co-development Partner · 28 January 2026Partnered with D&TA, Alfaisal University, and LabTrace to pilot data provenance standards in a regulatory sandbox for AI-enabled healthcare data exchange. Part of Saudi Arabia's Vision 2030 for a digitized, AI-enabled healthcare ecosystem.
• LabTracecoreTechnology or Integration · 28 January 2026UK blockchain technology company from Kings College London that co-developed the prototype with D&TA, enabling machine-verifiable provenance of healthcare datasets while maintaining privacy compliance.
• OASIS OpencoreStrategic or Co-development Partner · 9 July 2024OASIS Open standards body is hosting and managing long-term the Data Provenance Standards. Building an open community of practice for standards evolution, feedback, troubleshooting, and updates. The OASIS DPS Technical Committee is refining the standards into de jure technical standards under sponsorship of Cisco, IBM, and Microsoft.
• EDM CouncilimportantStrategic or Co-development Partner · 9 July 2024Partnership to adopt D&TA's Data Provenance Standards into next versions of EDM Council's flagship data management capability frameworks (DCAM and CDMC). Leverages EDM Council's expertise in data management best practices.
• Dun & BradstreetimportantStrategic or Co-development Partner · 30 November 2023Partnered with D&TA to test proposed data provenance standards. As a leading global provider of business decisioning data and analytics, they believe the standards help establish trust through transparency, interoperability, and compliance insights.
• National Association of Corporate Directors (NACD)coreStrategic or Co-development Partner · 18 September 2023D&TA partnered with NACD to publish AI governance guidance for corporate boards. Released 'Director Essentials: Implementing AI Governance' (September 2025) building on the original 2023 report. The partnership provides board-ready signals, scenarios, and KPIs for AI oversight from pilots-to-production to third-party procurement.
• Responsible Innovation LabsimportantStrategic or Co-development PartnerCollaboration on AI policy development. Responsible Innovation Labs supports D&TA's policy recommendations and goal to iterate with startup feedback on the AI Vendor Assessment Framework.
• Center for Global Enterprise (CGE)coreOthersD&TA is a 501(c)(3) subsidiary of the Center for Global Enterprise, a New York-based non-profit. CGE terms of use govern access to the D&TA website. D&TA co-chair Sam Palmisano is chairman of CGE.

Scale indicators7 records

Recent moves6 records

Expansion highlights6 records

Direct peers

• Partnership on AI: Non-profit multistakeholder coalition of companies, civil society, and academia focused on responsible AI practice. Directly comparable to D&TA in operating model (non-profit consortium publishing frameworks/best practices) and audience (enterprise AI deployers).
• Future of Privacy Forum: Non-profit think tank that convenes industry, academics, and policymakers on data privacy and responsible data practices. Highly comparable as a non-profit standards/policy convener addressing overlapping issues in data governance, provenance, and AI.
• World Economic Forum AI Governance Alliance: Multistakeholder initiative producing AI governance frameworks and policy guidance for business and government leaders. Comparable in its cross-industry convening power and emphasis on responsible AI deployment guidelines, though anchored in a broader institution.
• Center for AI Safety: Non-profit research organization focused on AI safety standards, risk evaluation, and policy recommendations. Comparable in producing frameworks and policy papers that inform responsible AI deployment, though more research/academic in orientation.
• Responsible AI Institute: Non-profit that develops responsible AI certification and assessment frameworks for organizations procuring and deploying AI. Closely comparable to D&TA's VAF and Algorithmic Bias Safeguards, with similar non-profit certification-focused model.

Emerging players

• Holistic AI: AI governance, risk, and compliance tooling vendor for enterprises deploying AI. Comparable focus area (AI vendor assessment, bias testing) but with commercial product model that competes for the same practitioner budgets as D&TA's free frameworks.
• Credo AI: Venture-backed software vendor offering AI governance, risk, and compliance SaaS products. Adjacent in serving the AI vendor assessment use case D&TA addresses with the VAF, but operating as a commercial platform rather than a free non-profit framework.

Broad incumbents

• IAPP (International Association of Privacy Professionals): Established non-profit professional association for privacy and data protection practitioners. Comparable as a non-profit standards/training body, with overlapping membership of data governance leaders and influence in regulatory engagement for responsible AI/data practice.
• ISO (ISO/IEC 42001 AI Management): International standards body publishing AI management system standards (ISO/IEC 42001). Direct competition for D&TA's AI governance frameworks as the formal global standard, but with formal certification pathway and broader enterprise/government reach.
• NIST (AI Risk Management Framework): U.S. federal agency producing the AI RMF—the leading government-anchored AI governance framework. Functionally comparable to D&TA's VAF and policy products but with formal regulatory backing and broader scope across all AI use cases.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks7 records

Key highlights7 records

Customer concentration

• GitHubgithub.com/Data-and-Trust-Alliance
• LinkedInlinkedin.com/company/data-trust-alliance

Revenue estimate

Valuation estimate

Number of profiles

Profiles4 records

Funding overview

Funding rounds

Investors

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M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Data & Trust Alliance