Spring clean your 2025 marketing strategy with sharper identity and smarter data

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: Model governance reviews before releasing new modeled attributes Feature-level checks ensuring no prohibited or sensitive signals are included Compliance-aware rebuilding and re-scoring, incorporating opt-outs and regulatory changes Validated delivery, ensuring attributes reflect the most current opt-outs, deletes, and compliance requirements 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. Our 2026 Digital trends and predictions report is available now and reveals 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 in 2026. Download 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: 1. Input Privacy-first, governed data: accurate, consented, continuously updated, and compliant. 2. Enrichment Predictive and contextual insights built from governed data, ensuring downstream intelligence reflects current and compliant information. 3. Orchestration Reliable, AI-powered workflows where governed data inputs ensures consistency in audience selection, activation, and measurement at scale. 4. Guardrails Transparent, responsible innovation. Clients apply their own model governance, explainability, and oversight supported by the visibility they have into Experian’s governed inputs. 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. Get started 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 What is AI data governance? AI data governance is the framework that manages data quality, consent, compliance and auditability before data enters AI systems. Why does AI data governance matter? AI decisions reflect the data used as inputs. Governance provides transparency, accountability and trust in automated outcomes. Does AI data governance prevent bias? AI data governance does not eliminate bias in models. It provides governed inputs that allow organizations to identify and address bias more effectively. How does privacy-first design support AI data governance? Privacy-first governance applies consent validation and compliance controls before data is activated, reducing downstream risk. Who is responsible for AI governance? Organizations govern their AI systems. Data providers govern the data foundation that feeds those systems. Latest posts

A decade ago, you could buy media by broad categories and call it a day. But today, your audience lives in a curated world. They watch what they want, skip what they don’t, and expect what they see to match their interests. Research shows that when ads are tailored to households, people pay more attention, stay engaged longer, and are more likely to remember your ads. That shift in expectations is why addressable advertising continues to grow. It’s a practical response to how media works today, with audiences moving fluidly across platforms, streaming spread across services, and measurement spanning screens and environments. Under these conditions, reaching the right people depends on clarity, not approximation. Artificial intelligence (AI) strengthens that clarity. When applied responsibly, AI helps connect signals, deepen audience understanding, and deliver relevant messages while protecting consumer data. The result is advertising that feels more human, not less. What is addressable advertising? Addressable advertising is the ability to deliver personalized ads to specific individuals or households and measure results using privacy-safe data and identity.  It works across digital, connected TV (CTV), linear TV, and over-the-top (OTT) streaming and relies on strong identity resolution and accurate data inputs to ensure your audience definitions remain consistent across channels and over time. Benefits of addressable advertising Addressable advertising changes how advertising performs by delivering messages to defined audiences, reducing wasted impressions, and making results simpler to measure. BenefitWhat it means for youClarityReach the right audience with the personalized messages they want, instead of hoping the right people are watchingEfficiencyAvoid wasted impressions by focusing spend where interest already existsHigher ROIImprove conversion by delivering messages that feel relevantOmnichannel consistencyCarry the same message across digital and TV without starting overMeasurable impactConnect exposure to actions so performance is clearPrivacy and complianceActivate audiences responsibly using privacy-safe data, clear governance, and compliant practices These are some of the reasons that addressable advertising has moved from a niche tactic to a core strategy. When audiences are clear, identity is connected, and measurement is built in, advertising becomes relevant, accountable, and easy to improve over time. Addressable advertising vs. traditional advertising Unlike traditional advertising, addressable advertising doesn’t depend on broad exposure or assumptions. It’s personalized by design and measurable by default, making it possible to connect ad exposure to outcomes. Another distinction is in how addressable delivers advertising to audiences and how performance is measured. Traditional media buysAddressable advertising buysYou pay for broad reachYou pay for relevant reach to defined audiencesAds run by placement or programAds are delivered to known households or individualsPersonalization is limitedPersonalization is built into deliveryMeasurement indicates trends, not who actually actedMeasurement connects exposure to actions by linking ads to defined audiences across channels But before you can activate addressable advertising, you need to understand who you’re actually trying to reach. What is an addressable audience? An addressable audience is a group of people you can identify and reach using data-based targeting. In other words, they’re not anonymous “maybe” viewers. They’re a defined audience you can activate across channels. Here’s what typically builds addressable audiences: FactorWhat it isWhy it mattersFirst-party dataData from your own relationships (site activity, app activity, CRM, emails, purchases)It’s your most direct view of existing customers and prospectsThird-party household and individual dataDemographic, behavioral, lifestyle, interest, and intent attributes from trusted providersIt fills gaps so your audience definitions don’t collapse when your own data is limitedIdentity resolutionA privacy-first way to match people across devices, households, and channelsIt improves accuracy so you don’t over-message the same people or miss them entirelyContextual signalsPage-level, content, or viewing context where ads appearIt reinforces relevance in the moment and complements addressable targeting when identity signals are limited How Experian helps with addressable audiences Experian helps you build and activate addressable audiences at scale without losing accuracy or trust. With more than 3,500 syndicated audiences available, you can activate consistently across 200+ destinations — including social platforms like Meta and Pinterest, TV and programmatic environments, and private marketplaces (PMPs) through Audigent. That means reaching people based on who they are, where they live, and their household makeup, using data governed with care. Our approach is built on accuracy first, which is why Experian data is ranked #1 in accuracy by Truthset for key demographic attributes. And when standard customer segments aren’t enough, Experian Partner Audiences expand what’s possible. These unique audiences are available through Experian’s data marketplace, within Audigent for PMP activation, and directly on platforms like DIRECTV, Dish, Magnite, OpenAP, and The Trade Desk. The evolution of addressability and why it matters more than ever As the media ecosystem shifts, reaching people across browsers, apps, CTV, and streaming platforms has become more complex. Signals are fragmenting everywhere as expectations for relevant, personalized experiences continue to rise, while reliable identifiers become increasingly challenging to access. In response, addressability is shifting from a channel-specific tactic to an identity-driven approach to reach and measure defined audiences across screens. That evolution puts new pressure on performance. Marketing budgets require accuracy and accountability, which means targeting must deliver measurable reach and outcomes you can trust. At the same time, the growth of CTV and streaming is expanding addressable TV opportunities. As CTV inventory grows, so does the need for cross-channel, identity-based activation that works consistently and supports reach, frequency, and measurement in one connected view. That’s why identity has become the foundation for making addressable advertising work today. When to apply addressable advertising You don’t need addressable for everything, but it shines when you need your spend to go farther with accurate targeting and resonant messaging. ScenarioWhy addressable helpsProduct launches and seasonal pushesReach people who are more likely to care without flooding everyone elseHigh-consideration purchases (auto, travel, financial services)Focus on likely intent and suppress audiences that don’t fitCross-channel campaigns (digital, TV, mobile)Keep messaging consistent across screensWhen using first-party data with AIUse AI customer segmentation to scale responsibly and improve performance without sacrificing accuracyRegulated categoriesRely on compliant data practices and clearer controls for regulated industries Addressable advertising is one way to put relevance and respect into practice — but it shouldn’t be the only time these principles apply. Marketers are expected to be thoughtful about who they reach, how often they show up, and how data is used across every channel. Addressable simply makes it easier to live up to that standard when accuracy, accountability, and scale matter most. Addressable advertising and third-party data There’s a common misconception that third-party data is no longer useful, but what’s really changed is the environment around it. In the early days of digital advertising, third-party data often felt like the Wild West. Today, modern third-party data is more transparent, better governed, and held to far higher standards with: Clear data sourcing Documented consent practices Regular quality audits Strict limits on how data can be used Used responsibly, third-party data plays a critical role in addressable advertising by complementing your first-party data and keeping audience strategies flexible as signals change. Benefits of third-party data When paired with identity resolution, high-quality third-party data helps you: Fill first-party gaps: Add demographic, behavioral, and interest-based insight when your own data is limited. Expand prospecting: Reach new audiences through modeling and lookalike expansion. Enrich segmentation: Combine household, behavioral, and interest signals to tailor creative, offers, and messaging to interests for more accurate and personalized activation. Support cross-channel addressability: Maintain consistent audience reach across devices and channels even as individual signals change. Why work with Experian for your data needs? At Experian, we approach third-party data with the belief that trust comes first. Our data is privacy-compliant, ethically sourced, and governed by strict standards so you can use it confidently. Accuracy matters just as much. Our identity and data-quality framework verifies that the data behind your audiences holds up in the real world — a key reason Experian is ranked #1 by Truthset for key demographic attributes. And because addressable advertising only delivers value when audiences move seamlessly from planning to activation, our audiences are interoperable by design. You can activate them across digital, social, and CTV platforms without rebuilding or reformatting your strategy for each channel. How AI is redefining customer segmentation Addressable advertising depends on audiences that stay accurate as people move across devices, platforms, and moments. Traditional segmentation built on static rules and snapshots in time can’t keep up with that reality. AI customer segmentation analyzes massive sets of household and individual data (such as intent, household demographics, purchase behavior, and content consumption) to identify patterns, predict intent, and group people into addressable audiences. As the AI advertising ecosystem continues to mature, reflected in industry frameworks like the LUMA AI Lumascape, segmentation and identity have become foundational layers rather than standalone tools. Those audiences update as conditions change, so they stay relevant instead of aging out. Here’s how AI-driven segmentation supports addressable advertising. What AI enablesWhy it mattersPredictive, intent-based audiencesAnalyze behavioral and transactional data to group people based on likely next actionsBroader audience availabilityAs more data signals are incorporated responsibly, AI makes it possible to support a wider range of addressable audience options without sacrificing accuracyDeeper insights from dataDiscover what people care about, how intent is forming, and which signals are most important with larger, more diverse data setsReal-time audience updatesKeep segments aligned as behaviors change, not weeks laterHigher accuracy, less guessworkRely on data-driven patterns for decision-making instead of assumptionsOngoing optimizationRefine audiences throughout the campaign lifecycle as performance signals come in We’ve used machine learning and analytics for decades to support responsible segmentation — balancing performance with privacy and transparency. That foundation now supports addressable advertising that adapts in real time while staying grounded in trust. Addressable TV: Targeting in the streaming era TV has become an addressable channel powered by data and identity resolution. CTV and OTT streaming are booming, while linear TV continues to decline, reshaping how people watch and how advertising works alongside it. For the first time, CTV spending is expected to outpace traditional TV ad spending in 2028, reaching $46.89 billion and signaling that addressable TV is now central to the media mix. With CTV and OTT platforms, advertising can now be delivered at the household level. That means two homes watching the same show can see different ads based on who lives there and what they like. This is what makes addressable TV possible. Benefits of addressable TV As streaming inventory continues to grow, addressable TV creates new ways to bring relevance and accountability to a channel once defined by broad exposure. Experian links identity data across streaming, linear, and digital platforms to help you manage frequency, attribution, and household-level insights in one connected view. Addressable TV also raises the bar. To manage reach, frequency, and measurement across streaming and linear environments, addressable TV depends on identity resolution that connects households across screens. Here’s how addressable TV helps you when identity is in place. What addressable TV enablesWhy it mattersHousehold-level targetingDeliver messages that reflect who’s watching, not just what’s onFrequency control across screensReduce overexposure and improve viewer experienceCross-channel measurement and attributionConnect TV exposure to digital actions, site visits, and conversionsMore efficient use of TV spendBring accuracy, accountability, and outcome-based insight to premium inventory and improve reach of streaming-first, harder-to-reach viewer segments Ultimately, addressable TV isn’t a replacement for linear TV, but it is an evolution. As streaming becomes the default viewing experience, the ability to engage TV audiences with the same care and clarity as digital is essential. Use cases for addressable advertising Addressable advertising works across industries because it adapts to how people make decisions. The examples below are illustrative scenarios that show how addressable audiences, identity resolution, and AI-driven segmentation can come together in practice using Experian solutions. Retail: Seasonal promotions A home décor retailer could use identity resolution and AI-driven segmentation to build addressable audiences, such as holiday decorators and recent movers, who are more likely to engage during peak seasonal periods. Campaigns could then be activated across CTV, display, and social, helping the retailer stay visible across screens while tailoring creative to seasonal intent. Automotive: In-market car buyers An auto brand might identify consumers nearing lease expiration using automotive-specific data tied to household and individual attributes. By suppressing current owners, the brand could avoid wasted impressions and activate addressable audiences across OTT and mobile to reach likely buyers during active consideration. Financial services: Credit card launch For a new credit card launch, a national bank could use modeled financial segments to reach credit-qualified prospects. Addressable digital advertising campaigns could apply frequency controls and personalized messaging, balancing reach with relevance while seamlessly measuring response. Streaming media: New subscriber growth A streaming platform looking to grow subscriptions could use an identity graph to exclude current subscribers. Likely viewers could then be targeted across CTV based on content preferences and viewing behavior, keeping spend focused on net-new growth. Media and entertainment: Audience expansion for a new release Ahead of a new release, a film studio could use behavioral and lifestyle data to identify likely moviegoers and fans of similar franchises. Addressable campaigns across CTV and digital video could help drive awareness and opening weekend attendance. Travel: High-value traveler acquisition A travel brand could use travel propensity data and household-level demographics to identify frequent flyers and family vacation planners. Personalized offers could then be activated across display, social, and programmatic channels to increase bookings while keeping spend focused on higher-value travelers. How Experian enables more effective addressable campaigns Addressable advertising is most effective when identity, data, and activation are connected from the start. Experian brings trusted household and individual data, privacy-first identity resolution, and broad activation partnerships together so you can move from audience insights to activation with minimal friction. Here’s how that comes to life across our core offerings. Identity resolution with Consumer Sync Consumer Sync connects devices, emails, digital identifiers, and offline data into a single, privacy-safe identity foundation. This connection helps your audiences stay consistent across streaming, linear TV, mobile, and digital despite changing signals. Audience insight and segmentation with Consumer View Consumer View supports clear segmentation, prospecting, and enrichment across industries. It combines demographic, behavioral, and interest-based data to help you build accurate, intent-driven audiences that reflect real people, not assumptions. Data is continuously updated and governed for accuracy. Omnichannel activation with Audience Engine Audience Engine enables direct activation of Experian audiences across CTV, digital, social, and programmatic platforms. It supports suppression, frequency management, and cross-channel consistency to keep messaging aligned and exposure controlled. More efficient media through curation and Curated Deals Curation combines data, identity, and inventory through Experian Curated Deals. These deal IDs, available off-the-shelf or privately, make it easier to activate high-quality audiences and premium inventory in the platforms you already use without custom setup. AI-enhanced segmentation and optimization Our AI-enhanced models analyze large data sets to create and refresh addressable audiences in real time, supporting intent-based targeting and ongoing optimization throughout the campaign lifecycle. These models work seamlessly with demand-side platforms (DSPs), ad platforms, and data clean rooms, so audience insights flow directly into activation and measurement without added complexity. Seamless integration with your ecosystem As an advertiser, you want addressable advertising to fit naturally into how you already plan and buy media. That’s why integration matters as much as insight. Experian integrates with leading DSPs, ad platforms, and data clean rooms, so you can activate addressable audiences in the environments you already use without reworking your strategy or adding complexity. This approach helps you: Build and activate addressable audiences: Reach the people you want with accuracy and respect. Activate across channels: Keep messaging consistent across digital, TV, and streaming. Optimize with data ranked #1 in accuracy by Truthset: Improve performance using the industry’s most reliable data. When identity, data, AI, and activation come together, addressable advertising does what it’s supposed to do: deliver relevance naturally, measure impact clearly, and give you confidence in every decision along the way. That’s the foundation for campaigns people want to engage with. Start creating campaigns audiences want to see Experian can help you apply addressable advertising in ways that respect consumers, perform across channels, and stand up to real-world measurement. Connect with our experts today to explore how addressable audiences, AI-driven segmentation, and identity-powered activation can work together in support of your goals. FAQs about addressable advertising What is addressable advertising? Addressable data-driven advertising involves delivering personalized ads to specific individuals or households using privacy-safe data and identity. What is an addressable audience? An addressable audience is a defined group of consumers you can identify and reach based on known household or individual attributes. What makes advertising addressable? Advertising becomes addressable when it’s possible to identify the audience by linking devices and households to people through identity graphs. This allows you to measure ad performance at the audience level and provide more personalized advertising. Is addressable advertising just for TV? Addressable advertising isn’t just for TV; it also works across digital, mobile, streaming, and social channels. How does AI help addressable advertising? AI improves addressable advertising by analyzing large data sets to predict intent, build more accurate audiences, boost performance over time, and improve your ability to find and build your audiences. Can addressable advertising work without cookies? Yes — identity resolution and first-party data are key to cookieless addressability. How does Experian support addressable advertising? Experian supports addressable advertising by providing trusted consumer data, privacy-centric identity resolution, and curated audience segments that activate across CTV, digital, mobile, and streaming platforms. Latest posts

Year after year, CES signals where marketing is headed next. In 2026, the message was clear. Progress comes from connecting data, intelligence, and outcomes with discipline, not spectacle. Across AI, programmatic media, and measurement, the same priorities surfaced again and again. Under the bright lights of Las Vegas, three themes cut through, and each one pointed to a future where data, intelligence, and outcomes move in lockstep. Here are the three themes that defined CES 2026. 1. Agentic AI proved that it’s only as good as its data inputs AI was once again the star of the show. At CES 2026, marketers focused less on demos and more on proof that AI improves decisions, reduces friction, and drives outcomes. Every credible use case traced back to accurate, privacy-first data. What changed at CES was how that intelligence is being applied. Agentic AI systems designed to act autonomously are moving beyond insights and into execution. From media buying to optimization, these agents are increasingly expected to make decisions at speed and scale. That shift raises the stakes for data quality. When AI is operating campaigns, not just informing them, accuracy and privacy are non-negotiable. “This year's CES made agency priorities crystal clear. Efficiency, differentiation, and outcomes. As agentic AI takes on more responsibility across planning, activation, and measurement, Experian gives agencies a robust data and identity foundation they can trust to own the outcome for every client.”Greg Williams, Chief Operating Officer Without accurate, privacy-compliant data, AI agents struggle to reflect real behavior or support responsible personalization. A reliable, privacy-first data foundation is what turns AI from an interesting experiment into an operational advantage. That advantage gets even stronger when it’s anchored in an identity graph that understands people and households across channels. When identity and intelligence move together, AI becomes more accurate, accountable, and effective at driving outcomes. In an AI first world, the strongest signal isn't scale. It's data quality. 2. Curation goes mainstream Curation is no longer experimental. At CES, it showed up as a mandated capability for buyers and sellers navigating fragmented signals and complex supply paths. Marketers want intentional media buys they can explain, defend, and repeat. AI is accelerating this shift. As AI systems take on more responsibility for planning, packaging, and optimization, curation provides the guardrails. It defines what “good” looks like (premium supply, trusted data, and clear performance goals), and allows AI to operate within those constraints driving the optimal outcomes for marketers. “Our sell-side clients walked into CES asking how to stand out in a crowded landscape. The answer kept coming back to data-driven curation. With Experian Audiences and Curated Deals, SSPs and publishers can improve targeting within PMPs, package inventory more intelligently, and prove value with confidence. As we head into 2026, data is no longer a supporting input. It needs to be at the center of every conversation.”Chris Meredith, Head of Sell-Side Rather than maximizing inventory access, curation prioritizes control, transparency, and performance. Buyers want premium supply aligned to specific goals. Sellers want clearer paths to demand. They can play the odds or own the outcome. When data leads, they own it. When curation is powered by high-fidelity audiences and a connected identity framework, it becomes even stronger. That’s what allows curated deals to deliver clarity, confidence, and repeatable performance. This shift reflects a broader move away from probability-based buying toward outcome ownership, where AI-driven systems are measured not on activity, but on results. 3. Activation and measurement finally shared the same stage Activation and measurement are now coming together around shared data and identity. CES 2026 marked a turning point where closing the loop felt achievable, not aspirational. Both the buy-side and sell-side face pressure to show that media investment drives outcomes. Agentic AI was a quiet driver of this optimism. As AI agents increasingly manage activation decisions in real time, marketers need measurement systems that can keep up. That requires a shared data and identity foundation. One that allows AI-driven actions to be evaluated against outcomes consistently, across channels and partners. In healthcare, accuracy is everything. Our clients need to reach patients and healthcare professionals in ways that respect privacy while driving meaningful outcomes. CES underscored that privacy, identity, and measurement must work in harmony. That’s how health marketers reduce risk and increase the likelihood that every message leads to better care.Sheila Wirick, Sales Director, Health Achieving that requires a consistent identity spine that connects planning, activation, and outcomes across channels. And that spine is strongest when it’s built on accurate, privacy-first data and audiences that understand people and households. That connection allows marketers to move beyond proxy metrics and evaluate performance based on tangible results. When campaigns and measurement rely on the same data foundation, AI-driven platforms can optimize toward outcomes such as new customers, account growth, or in-store activity, not just delivery metrics. That’s the connective layer that turns disconnected touch points into a measurable, outcomes-based system. Our 2026 Digital trends and predictions report is available now and reveals 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 in 2026. Download now Three takeaways from CES 2026 AI is maturing, but only for teams with accurate, connected, privacy-first data that AI agents can act on responsibly. Curation is scaling, giving both humans and AI systems clearer paths to quality, control, and differentiation. Activation and measurement are aligning, allowing AI-driven decisions to be judged on outcomes, not assumptions. We’re building for that world today. One where agentic AI operates on a trusted data and identity foundation, curation defines the rules, and outcomes determine success. With the right foundation and the deep data inputs, you can move faster, reduce risk, and let intelligence (human and artificial) work together to deliver results that last long after the neon lights fade. Connect with us FAQs What was the biggest shift discussed at CES 2026 for marketers? The biggest shift was the move from hype to accountability. Marketers focused on data quality, intentional media buying, and outcome-based measurement rather than experimental technology. Why did AI discussions emphasize privacy-first data? Privacy-first data supports accuracy, compliance, and trust. AI models built on unreliable or opaque data struggle to reflect real consumer behavior and create risk for brands. At Experian, privacy and compliance are built in. Every data signal, attribute, audience, and partner goes through our rigorous review process to meet federal, state, and local consumer privacy laws. With decades of experience in highly regulated industries, we’ve built processes that emphasize risk mitigation, transparency, and accountability. How does curation help reduce programmatic complexity? Curation simplifies buying by pairing premium inventory with specific audience and performance goals. This approach reduces waste and creates clearer, more repeatable buying paths. With the acquisition of Audigent, Experian is now more than just a premier data provider. We’re also a full-service curation partner. Together, we deliver end-to-end programmatic curation across data, inventory, and optimization, helping brands and publishers unlock smarter, more scalable media strategies. What does it mean to align activation and measurement? It means using the same identity and data foundation to plan campaigns and evaluate results. This alignment allows marketers to measure success based on business outcomes, not just delivery metrics. With Experian, marketers can plan, reach, and measure in a connected cycle. Every impression is measurable. Every audience is accurate. Every decision is powered by data ranked #1 in accuracy by Truthset. Why is identity central to all three CES themes? Identity connects data across channels and stages of the customer journey. It enables accurate AI, effective curation, and consistent measurement within one system. Experian delivers identity resolution at the scale, accuracy, and compliance required by the world’s largest enterprises. Our solutions are:- Built on trust: Backed by 40+ years as a regulated data steward and rated #1 in data accuracy by Truthset, so you can act with confidence.- Powered by our proprietary AI-enhanced identity graph: Combining breadth, accuracy, and recency across four billion identifiers, continuously refined by machine learning for maximum accuracy.- Seamlessly connected: Pre-built data integration with leading CDPs, DSPs, and MarTech platforms for faster time to value.- Always up to date: Frequent enrichment and near-real-time identity resolution through Activity Feed for timely personalization and more responsive customer engagement.- Privacy-first by design: Compliance with GLBA, FCRA, and emerging state regulations baked in at every step, supported by rigorous partner vetting. Latest posts