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.
Our2026 Digital trends and predictions reportis available now andreveals five trends that will define 2026. From curation becoming the standard in programmatic to AI moving from hype to implementation, each trend reflects a shift toward more connected, data-driven marketing. The interplay between them will define how marketers will lead in2026.
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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Experian, the leader in powering data-driven advertising through connectivity, is thrilled to unveil our latest solution, Digital Graph and Marketing Attributes. This joint solution supplies marketers and platforms with the insights and connectivity needed to understand who their customers are and reach them across digital channels. The uncertainty around third-party cookies in Chrome and the overall decline in signal complicates the industry’s ability to reach the right consumer. Omnichannel media consumption results in scattered data, making it harder for marketers and platforms to understand consumer behavior and reach them across channels. These challenges call for a comprehensive solution. Our Digital Graph and Marketing Attributes solution addresses these challenges by providing identifiers for seamless cross-channel engagement. By adding Marketing Attributes, like demographic and behavioral data, marketers and platforms also gain a better understanding of their customers. This solution uses Experian’s Living Unit ID (LUID) to combine offline and digital data, giving customers deeper insights into consumer behavior, greater audience reach, and improved cross-channel visibility. Benefits of Digital Graph and Marketing Attributes Both our Digital Graph and Marketing Attributes provide value to clients as standalone products. When clients license our Digital Graph and Marketing Attributes joint solution, they have more data at their fingertips, unlocking: Consumer connectivity: When clients license Experian’s Digital Graph, they get access to digital identifiers like mobile ad IDs (MAIDs), connected TV (CTV) IDs, hashed emails (HEMs), and universal IDs so they can target the right consumers with the relevant messages across all digital media channels. Consumer insights: Experian’s 5,000 Marketing Attributes provide our clients with detailed consumer information and insights, such as age, gender, purchase behaviors, and content consumption habits. Marketing Attributes help clients create more relevant messaging and informed audience segmentation. Client examples How OpenX offers richer targeting and more connectivity with Experian OpenX is an independent omni-channel supply-side platform (SSP) and a global leader in audience, data, and identity-targeting. With industry-leading technology, exceptional client service, and extensive scalability across all formats, including CTV, app, mobile web, and desktop, OpenX has a legacy of innovating products that enhance buyer outcomes and publisher revenue while addressing complex challenges in programmatic. In recent years, OpenX has licensed Experian’s Digital Graph with identifiers, contributing to the SSP’s largest independent supply-side identity graph, which offers advanced audiences to buyers and improved data resolution to content owners. More recently, OpenX licensed Experian’s Marketing Attributes to enrich its supply-side identity graph, which includes IPs, MAIDs, and client IDs, with a variety of attributes. This strategic move has helped OpenX’s clients benefit from enhanced consumer insights and addressability, in turn delivering greater reach to the demand side and higher revenue for publishers, despite industry signal loss. "We built on our long-term partnership with Experian to enrich our digital IDs with Experian’s Marketing Attributes, which help provide buyers better insights to audiences, thereby helping our publishers monetize their inventory. With partners like Experian, OpenX effectively facilitates the value exchange between demand and supply, ensuring our partners are able to drive results for their business in the era of signal loss"Craig Golaszewski, Sr. Director of Strategic Partnerships, OpenX How StackAdapt licenses our product bundle to address three different use cases StackAdapt is the multi-channel programmatic advertising platform trusted by marketers to deliver exceptional campaigns. They drive superior results through a variety of solutions, like contextual and first-party targeting, brand lift measurement, and optimization through insights. StackAdapt licensed a similar yet unique product combination, our Digital Graph and our Audiences. StackAdapt uses the Digital Graph to allow clients to onboard their first-party data in a seamless, self-serve manner that allows them to further segment their data using Experian Audiences. “StackAdapt has been recognized as the most trusted programmatic platform by marketers, and with the integration of Experian’s Digital Graph and Audiences, we are strengthening our leadership in the space. This partnership improves our ability to deliver precise cross-channel segmentation, reach, and measurement, helping advertisers run more successful campaigns. Our collaboration with Experian allows us to offer a differentiated solution in the market and ensure our clients can deliver the most precise and impactful ads to their audiences.”Denis Loboda, Senior Director of Data, StackAdapt We recently announced a new partnership with StackAdapt. This collaboration brings the power of Experian's identity graph, syndicated and custom audiences directly to the StackAdapt platform. Read the full details in our press release here. Four ways to use Digital Graph and Marketing Attributes When these two products come together, our clients have a 360-degree view of their consumers, which helps them power four critical use cases: Analytics and insights: Learn more about your consumers by connecting our Marketing Attributes with our Digital Graph's identifiers. For example, a retailer can discover that their recent customers over-index as pickleball fans and players, leading the retailer to sponsor a professional pickleball event. Inventory monetization: When supply-side partners know their audience better, they can attract advertisers in search of that audience. For example, a publisher might find out that their audience is full of pickleball fans, leading them to reach out to brands that want to reach this audience. Activation: Companies with access to more digital identifiers from our Digital Graph can reach more people, while controlling frequency across channels. A company might know that they want to reach pickleball fans. Now, they have the digital identifiers needed to reach pickleball fans across all digital channels where they consume content, leading to increased reach. Measurement and attribution: Use the Digital Graph’s support for various digital identifiers to understand all consumer touchpoints, from media impressions to conversions. Then, lean on our Marketing Attributes to determine who your messaging resonated with. For example, a company uses our Digital Graph to know if it was the same individual who was exposed to an ad on CTV and converted via e-commerce. On top of that, the company can use our Marketing Attributes data to find out that the people who purchased were overwhelmingly pickleball fans. Connect with us to learn more about how our Digital Graph and Marketing Attributes joint solution can provide the data and insights you need to create, activate, and measure cross-channel media campaigns. 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After a six-month beta period, collaboration in Snowflake Data Clean Rooms using Experian's offline or digital graph is now generally available for all clients. As part of this, Experian is excited to announce that Experian's identity graph will be integrated into Snowflake's Data Clean Rooms. With the growing importance of data privacy and marketing efficiency, this partnership builds off of Experian's previously-announced integration into Snowflake's AI Data Cloud for Media. Adding Experian's identity graph to Snowflake Data Clean Rooms helps advertisers, advertising platforms, and measurement partners work more effectively. Built upon Experian’s rich offline and digital identity foundation, with support for various identifiers across platforms, collaboration in Snowflake Data Clean Rooms helps clients maximize the value of their data and meet the diverse needs of modern business: Collaborate with partners for richer data insights Achieve higher match rates Improve audience building Produce more accurate and complete reports Ensure data privacy Seamless integration of AdTech and MarTech platforms Regardless of the identifier type you are looking to collaborate on, Experian has the identity data in Snowflake Data Clean Rooms to support you and your partner. This leads to higher match rates and more resolved data for you to use to benefit your media initiatives. "Integrating Experian's identity graph into Snowflake Data Clean Rooms marks a transformative leap for digital marketing. This collaboration empowers advertisers, programmatic platforms, and measurement partners with unparalleled accuracy, privacy, and efficiency. Together, we are excited to provide innovative solutions to meet the evolving needs of our clients."Kamakshi Sivaramakrishnan, Head of Data Clean Rooms at Snowflake The Experian and Snowflake partnership showcases how collaboration can enhance scalability and cost-efficiency. Data clean rooms provide a secure environment where multiple parties can share, join, and analyze their data assets without leaving the clean room or exposing the underlying data. By integrating Experian's identity graph within Snowflake's secure platform businesses of all sizes can receive advanced data collaboration and identity tools without the high costs usually involved. The integration prioritizes consumer privacy and data security. Backed by Experian’s Global Data Principles, Experian's deep roots in data protection and security provide customers with the most trusted way to share data and protect consumer privacy. With Experian's graph in Snowflake Data Clean Rooms, customers will get a solution that respects customer consent, safeguards sensitive data, and ensures that processing occurs with the utmost respect for user confidentiality and preferences. Further, Snowflake Data Clean Rooms uses advanced methods to preserve privacy, such as differential privacy and secure computations on encrypted data, enabling data security and integrity. Together, these methods prevent unauthorized access by keeping sensitive data within the secure confines of the cleanroom on a strict, collaboration-to-collaboration basis. The collaboration between Experian and Snowflake significantly enhances data matching and identity resolution within the Snowflake Data Cleanroom. Experian’s identity solution uses digital identifiers like hashed emails, MAIDs, and CTV IDs and offline identifiers like name and address. This allows advertisers to reach more consumers and enrich their data. Marketers can easily use their first-party data in the cleanroom, and with Experian's Graph, they get higher match rates for more accurate targeting and campaign measurement. The continued partnership between Snowflake and Experian provide advertisers, platforms, and measurement providers a secure and effective way to collaborate. This sets the stage for continued innovation in programmatic advertising, ensuring that our solutions evolve in step with our clients' needs. If you're not utilizing clean rooms for collaboration but have advanced identity needs, you can license our Graph and seamlessly integrate it into your Snowflake account. Reach out to our team to learn more Latest posts

With U.S. brands expected to invest over $28 billion in connected TV (CTV) in 2024, balancing linear TV and CTV is now a top priority. Advertisers need to integrate these platforms as the TV landscape evolves to reach audiences with various viewing habits. A successful strategy requires both linear and CTV approaches to effectively reach audiences at scale. We interviewed experts from Comcast Advertising, Disney, Fox, Samsung Ads, Snowflake, and others to gain insights on the evolving landscape of linear and CTV. In our video, they discuss audience fragmentation, data-driven targeting, measurement challenges, and more. Watch now to hear their perspectives. Five considerations for connecting with linear TV and CTV audiences 1. Adapt to audience fragmentation With consumers' rapid shift toward streaming, it's easy to overlook the enduring significance of linear TV, which still commands a large portion of viewership. According to Jamie Power of the Walt Disney Company, roughly half of the current ad supply remains linear, highlighting the need for brands to adapt their strategies to target traditional TV viewers and cord-cutters. As streaming continues to rise, ensuring your strategy integrates both CTV and linear TV is crucial for reaching the full spectrum of audiences. "I don't think that we thought the world would shift so quickly to streaming, but it's not always just all about streaming; there's still such a massive audience in linear."Jamie Power, Disney 2. Combine linear TV’s reach with CTV’s precision Blending the reach of linear TV with the granular targeting capabilities of CTV allows advertisers to engage both broad and niche audiences. Data is critical in understanding audience behavior across these platforms, enabling brands to create highly relevant campaigns tailored to specific audience segments. This strategic use of data enhances engagement and ensures that the right viewers see advertising campaigns. "The future of TV is really around managing the fragmentation of audiences and making sure that you can reach those audiences addressably wherever they're watching TV."Carmela Fournier, Comcast Advertising 3. Manage frequency across platforms Cross-platform campaigns require managing ad frequency to avoid oversaturation while ensuring adequate exposure. With a variety of offline and digital IDs resolved to consumers, our Digital and Offline Graphs can help maintain consistent messaging across linear TV and CTV. This approach allows advertisers to strike the right balance, preventing ad fatigue and delivering the right audience reach for campaign impact. "You've got to make sure that you're not reaching the same homes too many times, that you're reaching everybody the right amount of times."Justin Rosen, Ampersand 4. Focus on consistent measurement Linear TV and CTV offer different data granularities, necessitating tailored approaches for accurate cross-platform campaign measurement. Bridging these data gaps requires advanced tools that streamline reporting for both mediums. As the industry moves toward consistent measurement standards, advertisers must adopt solutions that provide a comprehensive view of campaign performance, enabling them to optimize their cross-platform efforts. "Where I think there are pitfalls are with the measurement piece, it's highly fragmented, there's more work to be done, we're not necessarily unified in terms of a consistent approach to measurement."April Weeks, Basis 5. Align with shifts in audience behavior The success of cross-platform campaigns hinges on staying agile and responsive to shifting audience preferences. As CTV adoption grows, advertisers must proactively adjust their strategies to align with how viewers engage across linear and streaming platforms. Ideas include: Regularly updating creative Adjusting the media mix Utilizing real-time data insights to ensure campaigns remain relevant "At Fox we were a traditional linear company, and essentially what we're trying to do is merge the reach and the scale of TV as well as the reach and the scale of all the cord-cutters and cord-nevers that Tubi possesses." Darren Sherriff – FoxDarren Sherriff, Fox As streaming TV rapidly changes, brands must stay ahead of trends and shifts in consumer behavior to tap into CTV's growing potential. By focusing on these opportunities, advertisers can blend linear TV and CTV, ensuring their campaigns reach audiences wherever they watch. Connect with Experian's TV experts As a trusted leader in data and identity services, Experian offers the expertise to help you succeed in television marketing. With our strong partnerships with key players in the TV industry, we provide access to unique marketing opportunities. Learn how Experian’s data and identity solutions can deliver outstanding results in advanced TV advertising. Partner with us today to enhance your marketing strategies using our Consumer View and Consumer Sync solutions. Connect with our TV experts Contact us Latest posts