At A Glance
Trustworthy AI depends on AI data governance. Automated systems rely on governed data that is accurate, fresh, consented, and interoperable at every stage. Without governance at the data foundation, organizations lack visibility, accountability and confidence in AI-driven decisions. Responsible automation begins with privacy-first data governance that supports transparency, compliance, and long-term sustainability.Why AI data governance determines trust in automated decisions
AI is reshaping audience strategy, media investment, and measurement. Automated systems now make more decisions at scale and in real time. Trust in those decisions depends on the data that informs them.
AI data governance provides the framework that allows organizations to answer foundational questions like:
- Which information or inputs guided this decision?
- Is the model respecting consumer rights?
- Could bias be influencing the outcome?
- If AI made the wrong call, how would we know?
Without governed data, these questions remain unanswered. AI data governance creates accountability by establishing quality controls, consent validation and auditability before data enters automated systems.
Most organizations are still building their readiness to govern data at scale. Many vendors highlight “fast insights” or “transparent reporting,” but few can support true data governance — the auditability, privacy-by-design, quality controls, and continuous compliance required for responsible AI.
That foundation is where responsible automation begins. And it’s why trust in AI starts with data governance.
Responsible automation begins with governed data
Automation produces reliable outcomes only when data is accurate, current, consented and interoperable. AI data governance makes responsible automation possible by applying controls before data reaches models, workflows, or activation channels.
AI systems may interpret context, predict signals, and act in real time. But no model, logic layer, or LLM can be responsible if the data feeding it isn’t governed responsibly from the start.
This raises a core question: How do we ensure AI systems behave responsibly, at scale, across every channel and workflow?
The answer begins with trust. And trust begins with AI data governance.
Governing the data foundation for responsible AI
Experian’s role in AI readiness begins at the data foundation. Our focus is on rigorously governing the data foundation so our clients have inputs they can trust. AI data governance at Experian includes:
By governing data at the source, we give our clients a transparent, accurate, and compliant starting point. Clients maintain responsibility for bias review within their own AI or LLM systems — but they can only perform those reviews effectively when the inputs are governed from the start.
This is how AI data governance supports responsible automation downstream.
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Privacy-by-design strengthens AI data governance
Privacy gaps compound quickly when AI is involved. Once data enters automated workflows, errors or compliance issues become harder, and sometimes impossible, to correct. AI data governance addresses this risk through privacy-first design.
Experian privacy-first AI data governance through:
- Consent-based, regulated identity resolution
- A signal-agnostic identity foundation that avoids exposing personal identifiers
- Ongoing validation and source verification before every refresh and delivery
- Compliance applied to each delivery, with opt-outs and deletes reflected immediately
- Governed attributes provided to clients, ensuring downstream applications remain compliant as data and regulations evolve
Experian doesn’t govern our client’s AI. We govern the data their AI depends on, giving them confidence that what they load into any automated system meets the highest privacy and compliance standards.
Good data isn’t just accurate or fresh. Good data is governed data.
How AI data governance supports responsible automation at scale
With AI data governance in place, organizations can build AI workflows that behave responsibly, predictably, and in alignment with compliance standards.
Responsible automation emerges through four interconnected layers:
Together, these layers show how data governance enables AI governance.
AI integrity starts with AI data governance
Automation is becoming widely accessible, but responsible AI still depends on governed data.
Experian provides AI data governance to ensure the data that powers your AI workflows is accurate, compliant, consented, and refreshed with up-to-date opt-out and regulatory changes. That governance carries downstream, giving our clients confidence that their automated systems remain aligned with consumer expectations and regulatory requirements.
We don’t build your AI. We enable it — by delivering the governed data it needs.
Experian brings identity, insight, and privacy-first governance together to help marketers reach people with relevance, respect, and simplicity.
Responsible AI starts with responsible data. AI data governance is the foundation that supports everything that follows.
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About the author
Jeremy Meade
VP, Marketing Data Product & Operations, Experian
Jeremy Meade is VP, Marketing Data Product & Operations at Experian Marketing Services. With over 15 years of experience in marketing data, Jeremy has consistently led data product, engineering, and analytics functions. He has also played a pivotal role in spearheading the implementation of policies and procedures to ensure compliance with state privacy regulations at two industry-leading companies.
FAQs about AI data governance
AI data governance is the framework that manages data quality, consent, compliance and auditability before data enters AI systems.
AI decisions reflect the data used as inputs. Governance provides transparency, accountability and trust in automated outcomes.
AI data governance does not eliminate bias in models. It provides governed inputs that allow organizations to identify and address bias more effectively.
Privacy-first governance applies consent validation and compliance controls before data is activated, reducing downstream risk.
Organizations govern their AI systems. Data providers govern the data foundation that feeds those systems.
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Tapad expands linear TV analytics solution, enabling optimal reach and frequency across TV and digital platforms NEW YORK, Jan. 24, 2017 /PRNewswire/ – Tapad, now a part of Experian, has partnered with WideOrbit, the leading provider of advertising management software for media companies, to develop the industry's first programmatic TV-buying platform powered by a device graph. Tapad is the leading provider of unified, cross-screen marketing technology solutions and was first to market with a device graph, the Tapad Device Graph™. WideOrbit's robust supply platform and industry-leading footprint offers access to premium TV inventory on top networks, reaching more than 99 million households across local affiliates. The partnership pairs Tapad's demand-side technology with WideOrbit's supply-side inventory. As a result, marketers can leverage cross-device audiences in their TV buys for the first time. Additionally, integrating the Tapad Device Graph™ with digital feedback loops and audiences both accelerates optimization and enables precise audience discovery for TV marketers. "The integration of WideOrbit's quality TV supply takes orchestrated cross-screen media buys to the next level," said Marshall Wong, Tapad's SVP of TV market development. "Marketers can now optimize TV campaigns within days instead of weeks. This also untethers them from buying against generic demographics like age and gender. By allowing brands to employ their own CRM or third-party data, we can move them much closer to audiences who will take action." "Integrating Tapad's device graph with WideOrbit's programmatic marketplace delivers enormous value to marketers looking to add TV to cross-device campaigns," said Ian Ferreira, EVP of programmatic at WideOrbit. "Television still delivers the most efficient reach of any medium, and Tapad's platform now allows marketers to purchase premium broadcast inventory that extends the power of cross-screen campaigns to TV with a single, unified solution." "Our clients build lasting relationships with consumers through thoughtful and pioneering marketing," said Jeff Giacchetti, VP of digital at Mediavest Spark. "The strategic partnership of demand-side technology and supply-side inventory makes it easier for brands to find efficient, incremental reach and are critical in this endeavor." For more information about Tapad's cross-platform advertising solutions, please visit https://www.experian.com/marketing/consumer-sync. Contact us today
Global Engineering Team Staffing Up New Oslo Hub; Nordic Operational Team Also Slated for Q1'17 NEW YORK, Jan. 11, 2017 /PRNewswire/ – Tapad, now a part of Experian, the leader in cross-device marketing technology, is opening an office in downtown Oslo, Norway, effective January 16, 2017. This development reflects Tapad's continued growth following its acquisition by the Telenor Group in early 2016. Tapad Oslo will be comprised of a globally-focused engineering team as well as an upcoming operational headquarters for the region. Jeff Olchovy, a senior Tapad developer and one of its earliest employees, will forge the company's Nordic engineering presence by supporting the build-out of the team. The initial hiring plan of more than 20 open positions includes roles such as Head of Engineering, Senior Software Engineers and Solution Engineers. Plans for Tapad's Nordic Region business line, including its leadership, will be announced within the first quarter of 2017. "Given the caliber of technical talent and our extensive network in the region, Oslowas the logical choice at this stage of our growth," says Dag Liodden, Tapad CTO and co-founder. "This enables us to continue building out our innovative team on a global scale in a region that is close to our hearts and minds." In collaboration with its New York-based developers, Tapad's Oslo-based engineers will continue to advance the company's renowned product portfolio, such as the Tapad Device Graph™. An early adopter of Scala and big data processing technologies, Tapad has long been an influencer in U.S. tech. "As the head of our platform group, which daily processes several petabytes of data and is the foundation for all of our real-time systems, Jeff is a highly respected engineer," said Pål Høye, Tapad's senior vice president of engineering. "Given his experience and skillset, he is ideally suited to find and lead an innovative team focused on building the industry-leading products we are known for." About TapadTapad Inc. is a marketing technology firm renowned for its breakthrough, unified, cross-device solutions. With 91.2% data accuracy confirmed by Nielsen, the company offers the largest in-market opportunity for marketers and technologies to address the ever-evolving reality of media consumption on smartphones, tablets, home computers and smart TVs. Deployed by agency trading desks, publishers and numerous Fortune 500 brands, Tapad provides an accurate, unified approach to connecting with consumers across screens. In 2015, Tapad began aggressively licensing its identity management solution, the Tapad Device Graph™, and swiftly became the established gold-standard throughout the ad tech ecosystem. Tapad is based in New York and has offices in Atlanta, Boston, Chicago, Dallas, Detroit,Frankfurt, London, Los Angeles, Miami, Minneapolis, San Francisco and Toronto. Tapad's numerous awards include: EY Entrepreneur of The Year (East Coast) 2014, among Forbes' Most Promising Companies two year's running, Deloitte's Technology Fast 500, Crain's Fast 50, Entrepreneur 360, Digiday Signal Award, iMedia ASPY Award and a MarCom Gold Award. Contact us today