At A Glance
Agentic AI is moving faster through media planning than most organizations can define what it means for their business. Vendors are pitching it, conferences are built around it, and marketing teams feel pressure to move now. Before automation reallocates budget or reshapes a customer journey, marketers need three things in place: a shared definition of agentic AI, an identity foundation the system can trust, and independent measurement that keeps buying and performance separate.Agentic media planning has gone from emerging idea to assumed industry direction in a single cycle. The instinct to move fast on new technology makes sense. When a whole industry agrees on something quickly, though, the definitions, limits, and trade-offs that matter most tend to get skipped, and “agentic AI” still means very different things to different teams. Organizations building toward it without a shared definition, risk creating incompatible systems under the same label. There’s foundational work to do before automation takes the wheel.
What does agentic AI mean in media?
Much of the current enthusiasm around agentic AI conflates the technology with a specific tool. In many conversations, “agentic” has become shorthand for highly autonomous generative AI, as though large language models (LLMs) were the entire system rather than one component within it.
That framing understates what agentic systems are. Agentic systems are decision frameworks, not models. They coordinate predictive models, generative tools, and non-AI logic to move from signal to recommendation to action.
This pattern already exists outside media. Starbucks’ “Deep Brew” connects real-time purchase signals with personalized offers while informing what products stores stock and promote. The system coordinates customer demand with operational decisions across the business. Layering prompt engineering onto an LLM is a different thing entirely.
Without a shared definition of what “agentic” means for your organization, teams risk optimizing different visions of the same idea:
All may qualify as agentic, but without a shared definition, you can’t build toward the same goal. That’s why defining the problem statement comes first, not last.
Why do acting systems raise the stakes?
Here’s what sets agentic systems apart from earlier waves of automation: they don’t just inform decisions; they execute them. Programmatic has always operated within guardrails, executing and optimizing based on defined parameters. Agentic systems work more like navigation. They determine direction and weigh trade-offs against a wider set of context. When an agent reallocates budget mid-flight, suppresses an audience segment, or swaps creative, the quality of the identity and business logic behind that decision determines the outcome.
Here’s what sets agentic systems apart from earlier waves of automation: they don’t just inform decisions; they execute them.
Apply that framework to media. An agentic system operating on incomplete identity data or stale signals won’t slow down to account for the gap. It optimizes faster in the wrong direction. The coordination layer needs to weigh reach, incrementality, audience fatigue, and margin before it shifts spend, and that requires inputs that are accurate, current, and governed. Accountability and oversight aren’t optional anymore; they need to be built into the design from the start.
Watch our Curated Couch session on agentic media planning
Why should measurement stay separate from buying logic?
As autonomy grows in media systems, a structural problem emerges: the system shouldn’t measure its own performance.
When buying logic and measurement logic live in the same loop, performance numbers can look strong simply because they’re optimized to the system’s own signals. Success stops being defined externally and starts being defined internally. Agentic models trained on this pattern learn from the signals they favor, optimizing toward the outcomes they’re best equipped to observe. Performance looks good inside the system, and reflects a narrower view of what’s actually happening.
Independent measurement gets framed as friction on automation more often than not. In reality, it’s what lets automation to scale responsibly. Incorporating independent measurement signals into agentic decision-making, while maintaining meaningful separation from buying logic, produces an objective view of performance, one that can be compared consistently across systems rather than optimized within a single one. That distinction matters when you need to explain results to a client, stakeholder, or regulator.
AI as coordination layer, not an infrastructure replacement
Nothing here slows down automation. Independent measurement doesn’t add friction to execution but builds confidence in the outcomes those decisions generate. The organizations that will benefit most from agentic media won’t necessarily be the ones that adopt it fastest, but those that take the time to define where trusted autonomy creates measurable value and where human judgment needs to stay in the loop.
Before automation reallocates dollars or reshapes customer journeys, the data model has to hold up under scrutiny.
Trust in data, systems, and decision-making processes becomes the real constraint as agentic systems move from insight to action. That trust doesn’t come from autonomy alone, but it comes from governed data and decisions that can be explained, audited, and defended. Every brand that has operationalized automation at scale has learned the same lesson: before automation reallocates dollars or reshapes customer journeys, the data model has to hold up under scrutiny.
How does Experian help you build a defensible foundation?
Experian’s approach to AI in marketing starts from the same principle: intelligence is only as reliable as the foundation it’s built on.
We have spent decades building and governing data in regulated industries. That experience is what makes our foundation AI-ready: not just technically capable but built to withstand the scrutiny that responsible automation requires.
2026 State of advertising report
Our 2026 State of advertising report brings together perspectives from 14 leaders operating across key parts of the advertising ecosystem to show how shifts in AI, commerce media, healthcare, and more, are taking shape in practice.
Download our 2026 State of advertising report and hear from Scott Bender, Head of Publisher & Platform Partnerships, Newton Research, on how AI in advertising is reshaping planning, activation, and measurement.
The data foundation comes first
Agentic AI will reshape how media is planned and bought. That shift is happening now, and the opportunity is significant. But the advantage belongs to organizations that build on a foundation their systems, partners, and stakeholders can trust. Before automation runs, the inputs must be defensible, identity must be accurate, measurement must be independent, and the problem statement must be clear. Get those things right, and automation becomes more powerful. Skip them, and you’re simply moving faster in the wrong direction.
About the author
Budi Tanzi
SVP, Product, Experian
Budi Tanzi is the Senior Vice President of Product at Experian Marketing Services, overseeing all identity products. Prior to joining Experian, Budi worked at various stakeholders of the ad-tech ecosystem, such as Tapad, Sizmek, and StrikeAd. During his career, he held leadership roles in both Product Management and Solution Engineering. Budi has been living in New York for almost 11 years and enjoys being outdoors as well as sailing around NYC whenever possible.
FAQs
Agentic AI refers to systems that move from signal to recommendation to action with a high degree of autonomy. In media, this means an agent can reallocate budget, adjust audience targeting, or swap creative mid-flight based on real-time signals. Unlike standard programmatic systems that execute within predefined guardrails, agentic systems function more like a navigation layer, coordinating across data inputs, predictive models, and business rules to make directional decisions.
Data quality matters more as media automation becomes more autonomous because autonomous systems don’t slow down to account for bad inputs. If an agentic media system operates on incomplete identity data or stale audience signals, it optimizes faster toward the wrong outcomes. The quality of the identity foundation, the accuracy of audience attributes, and the reliability of measurement inputs all become more consequential, not less, as human oversight is reduced.
Programmatic executes and optimizes within defined parameters whereas agentic systems function at a higher level of abstraction, weighing reach, incrementality, fatigue, and margin before determining where and how to shift spend. Programmatic is the engine. Agentic AI, when built correctly, is the navigation layer that determines direction based on wider context and business objectives.
Measurement should be kept separate from buying logic in agentic systems because when a system measures its own performance, it optimizes toward outcomes it’s best equipped to observe. The definition of success becomes internal rather than external, and performance numbers may look strong while reflecting a narrower view of what’s working. Independent measurement, kept meaningfully separate from buying logic, produces results that can be compared across systems and explained to stakeholders without ambiguity.
Experian’s Offline Graph and Digital Graph provide a privacy-first identity foundation covering more than 250 million U.S. consumers and 4.2 billion digital IDs. Experian’s Marketing Data adds more than 5,000 attributes per audience, and Experian’s outcomes measurement keeps performance signals independent from buying logic.
Latest posts
Advertisers continue to increase their spending across addressable TV, connected TV (CTV), and digital. According to IAB’s “2021 Video Ad Spend and 2022 Outlook” report, digital video ad spending is expected to increase by 26% to $49.2 billion in 2022. Understanding who consumers are and how to best reach them in their preferred channel is becoming more complex. Damian Amitin and Colleen Dawe discuss how a seamless identity strategy can address the complexity of the emerging TV space. The evolution of identity resolution Around ten years ago, the idea of digital “identity resolution” or “Device Graphs” was born. This idea connected cookies and MAIDs to understand when many IDs were the same person or household. In more recent years, our industry began to connect that initial understanding to the CTV ecosystem. But, a large part of the TV ecosystem existed in silos, like first and third-party audience data, and the growing advanced TV market. The goal of identity resolution has always been to understand the consumer better. To achieve more accurate targeting and measurement in the CTV ecosystem, we must incorporate the following: What we know about the household and consumer from an ID perspective Who the consumer is as it relates to audience data, as well as the wealth of first-party data in the advanced TV space We know the cookie is a flawed way to collect data. While Google delayed the deprecation of third-party cookies, there are other challenges that we face right now. Such as the glaring gap in Safari traffic and the Identifier for Advertisers (IDFA) turning to “opt-in.” Understanding consumer behavior across devices and platforms continues to challenge marketers and publishers. These challenges are creating the need to find more stable identifiers. Though the cookie remains valuable, it has an uncertain future. This has led advertisers to place bigger bets on the combination of addressable and CTV. The overlap in addressable and CTV data leads to fragmentation Personally identifiable information (PII) makes up the majority of addressable TV households’ data. Part of the attraction to CTV is that their IDs remain universal, persistent, and stable. Analysts project that CTV ad spending will hit $23B in 2023. Consumers now have an average of 4.7 streaming subscriptions per household. It’s no surprise then, that Disney+, HBO, and Netflix released or announced ad-supported tiers. Addressable TV and CTV are often thought of as distinct markets across the industry. But, in the context of identity, we should look at them through the same lens. Millions of households still consume TV and video content via a set-top box or through apps on CTVs. This is in addition to what they consume on their laptops, tablets, and phones. Of the top 11 cable and satellite providers, 65 million U.S. households still have a box in their homes. On the other hand, approximately 96 million U.S. households have at least one or more Smart TVs and streaming services. With about 126 million total U.S. TV households, that’s a lot of overlap. There are still significant numbers of both addressable and CTV homes. How can we address fragmented TV consumption? Through a holistic and comprehensive approach to identity. An approach that captures addressable TV, CTV, and digital identifiers. An approach that captures all audience attributes inside of a single identity graph. This is the ideal approach for publishers, AdTech vendors, and brands. Discover how to unlock holistic identity How can we achieve a holistic identity? Through a three-pillared approach: First-party data onboarding Digital identifiers Consumer data First-party data onboarding Bringing offline data from a brand’s consumers is very valuable due to the quality of the data. Because the data is being collected right from the source, you know it’s accurate. It provides the foundation you can build your identity strategy from. Digital identifiers Once you create a foundation with first-party data, you need to connect it. Either with an internal or licensed digital ID graph. Then you can understand the connections between all devices within the household. Consumer data After you know which devices tie to a single consumer, you’ll want to act on that knowledge. The next step is to partner with a data provider that can help you understand your consumers. Establishing this partnership will help improve targeting, measurement, and the customer experience. To achieve a well-rounded customer view tomorrow, we need to start today The three-pillared approach bridges the gap between the offline and online worlds. This provides a well-rounded view of customers and audiences. However, the ability to tie these aspects of identity together still presents several challenges. To achieve the three-pillared approach today, you need to use many vendors and fragmented data sources. Often with conflicting data. As we look forward, the tools to do this are becoming more advanced and unified. The players in our ecosystem should adopt a seamless identity strategy. One that provides a privacy-safe yet full-picture solution. That means capturing and unifying all devices within a household. While also understanding the consumer behaviors and profiles behind those devices. Keep up with your customers and their data Once we create an informed identity strategy, we can begin to understand the makeup of each household and the individuals within. In this new world, personalizing the experience for an audience is key. Where do they prefer to spend their time? What type of content are they most engaged in? Only then can we as an industry provide an optimal experience for each consumer. All while driving greater ROI for advertisers and publishers. Are you ready to know more about your customers than ever before? Let’s get to work together to achieve your marketing goals. Contact us to learn how we can connect the complex dots of identity resolution. About our experts Damian Amitin, VP of Enterprise Partnerships, Experian Marketing Services Damian Amitin is the VP of Enterprise Partnerships and joined Experian during the Tapad acquisition in November 2020. Damian is a senior sales and partnerships executive, specializing in the identity resolution and marketing data ecosystem. Damian helps brands, publishers, and technology vendors enable enhanced ID resolution through The Experian/Tapad platform to attain a 360 view of the customer across targeting analytics, attribution, and personalization. Colleen Dawe, Senior Account Executive, Experian Marketing Services Colleen Dawe is a Senior Account Executive on the Advanced TV Team within Experian Marketing Services. With 15 years of experience working within the television ecosystem, Colleen works with clients to bring the value and expertise of Experian to support their objectives in the areas of data, identity, activation, and measurement. Get in touch
Brands can leverage non-clinical factors, like the social determinants of health, to gain a holistic view of their patients and increase access to care.
Next up in our Ask the Expert series, we hear from Sarah Ilie and Lauren Portell. Sarah and Lauren talk about the internet’s value exchange – what we gain and lose when it’s so easy to share our information. Is convenience hurting or helping us? The age of connectivity Today, it’s almost unimaginable to think about how your day-to-day life would look without the convenience of the internet, smartphones, apps, and fitness trackers; the list goes on and on. We live in the age of connectivity. We have the convenience to buy products delivered to our homes on the same day. We can consume content across thousands of platforms. We also have watches or apps that track our health with more granularity than ever before. The internet’s value exchange In exchange for this convenience and information, we must share various kinds of data for these transactions and activities to take place. Websites and apps give you the option to “opt in” and share your data. They also often let you know that they are collecting your data. This can feel like an uncomfortable proposition and an invasion of privacy to many people. What does it mean to opt-in to a website or app’s tracking cookies? What value do we exchange? What opting in means for you Opting in to cookies means that you are allowing the app or website to track your online activity and collect anonymous data that is aggregated for marketing analytics. The data provides valuable information to understand users better to create better online experiences or offer more useful products and content. Granting access to “tracking” offers several benefits to users such as a customized, more personal user experience or advertising that is more likely to be relevant. For example, let’s imagine you have recently been using an app or website to plan a camping trip. By sharing your data, the website or app has visibility into what is interesting or useful to you which can lead to related content suggestions (best campsites) or relevant advertising and product recommendations (tents and camping equipment). It’s important to know that the marketing data collected when you opt in is extremely valuable. The revenue that advertising generates is often very important to websites and apps because this is how they make money to continue providing content and services to consumers. Data privacy practices Privacy concerns regarding how companies and developers use tracking information have risen over the last couple of years and have resulted in additional protection for consumers’ privacy while still allowing companies to improve their products and advertising. One big step in this direction has been simply making people aware that their data is being collected, why it’s being collected, and providing users with the option to share this data for marketing analytics through opting-in or not. Other important steps to maintain online privacy include formal legal legislation and self-regulation. The right to privacy is protected by more than 600 laws between individual states and federal legislation and the U.S. House Committee on Energy and Commerce recently voted to pass the American Data Privacy and Protection Act. Additionally, marketing organizations such as the Interactive Advertising Bureau and Association of National Advertisers regulate themselves with codes of conduct and standards given there is so much attention on privacy issues. Is the internet’s value exchange worth it? The data that we choose to share by opting in has a lot of benefits for us as consumers. There are laws in place to protect our data and privacy. Of course, it’s important to be aware that data is collected and used for marketing purposes, but it’s also reasonable to share a certain amount of data that translates into benefits for you as well. The best data unlocks the best marketing. Contact us to tap into the power of the world’s largest consumer database. Learn how you can use Experian Marketing Services’ powerful consumer data to learn more about your customers, drive new business, and deliver intelligent interactions across all channels. Meet the Experts: Lauren Portell, Account Executive, Advanced TV, Experian Marketing Services Sarah Ilie, Strategic Partner Manager, Experian Marketing Services Get in touch