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In December, our recap focuses on three developments shaping publishers’ priorities heading into 2026. The growing practical impact of AI on the sell-side, early but concrete progress in programmatic deal automation through IAB Tech Lab’s Deals API, and new insights into addressability and measurement readiness across Europe.
In this summary, our experts outline what these shifts mean in practice: how AI is affecting traffic, content and operations on the sell-side, what publishers can realistically expect from the first version of the Deals API, and why strengthening first-party data, contextual strategies, and measurement capabilities is becoming critical heading into 2026.
AI on the Sell-Side: What Actually Matters for Publishers
It’s everywhere in every conversation, newsletter, podcast and feed. It’s a threat and an opportunity, good and bad. And it’s not going anywhere, it’s here to stay. Industry is continually launching new standards and projects in AI. But what is important today, what tomorrow, that might be hard to understand for all of us who work in digital advertising and publishing. But let’s recap the biggest buzz acronyms and see if it makes sense.
One way to approach everything going on is to observe the landscape from two perspectives. Audience and sales, let’s start with the audience.
AI, discovery and the audience problem publishers face today
The negative issue is that LLM crawlers are bombing publishers' servers more than ever, generating, in most cases, unwanted tech costs and sometimes also ad calls. And at the same time, LLMs are crabbing part of the publisher's audience with the content they have stolen from publishers. Double trouble, and an urgent one indeed. Common sense says that this is the AI issue we should solve first.
From a tech cost perspective, publishers should focus on blocking all unwanted crawlers immediately. In some cases, it might be easier to turn this around and unblock only humans and a few well-known friendly crawlers. If you can identify friendly crawlers from impostors pretending to be something else, they actually are.
For blocking or allowing only certain parties, there is already tech available. Infrastructure providers like Cloudflare have launched their solutions, and companies like Gravito offer monitoring and blocking solutions.
Content access, control and monetisation
LLM content crawling can also be good for publishers, or at least tolerable, if it brings an audience and or money. Once analytics and control are in place, the next step is monetisation. We’ve already been reading positive news about leading publishers signing agreements with leading LLM providers. That's a great start, but we haven't heard any news on smaller, independent local publishers making these deals. Understandable but worrying.
How will a local publisher sort this out? One option is standardised monetisation mechanisms, which are in the works. IAB Techlabs Content Monetization Protocols (CoMP) and other initiatives are building solutions to address this issue, but the challenge is that these projects take time. And the audience and content are stolen right now. So maybe the best approach for those publishers unable to sign deals with LLM providers is to block LLM scrapers as tightly as possible and revisit this once there are working, scalable monetisation standards in place.
AI in advertising sales: automation, agents and realism
The other side of the AI coin in advertising sales. It's a busy time on this front as well. The H2:s biggest launch and buzz has been around the Ad Context Protocol -standard (AdCP).
The standard aims to bring a new wave of automation, with agentic AI, to advertising buying and selling. Right now, AdCP mainly focuses on scaling direct sales-type activities and does not aim to replace OpenRTB. The vision is bold and lucrative. What if buyers could scale their direct buys to hundreds of websites without significant manual work?
But everyone who has experience working with sell-side adtech knows that it requires quite a lot of coffee, cigarettes and complex development before real-life complexity with changing inventories, campaign updates, workflows and integrated systems and updating API’s are ironed out and simplified for sleek agents.
So, advice for publishers at this point is: If you have resources, jump on the wave, join the community and start testing with your tech partners. For those who don’t have enough resources to burn on uncertain pilots, my advice is to follow this development closely and get to know companies that might help you with implementation if or when the time comes. It’s fair to say that there is some scepticism in the market, but who knows, maybe we all will be agentic soon.
Supporting standards: UCP and ARTF explained
And then we have these supportive standards, which might cause hair loss for me if I had any left.
First UCP, which stands for User Context Protocol. Why would we need this? Well, based on Tech Lab’s Anthony Katsur’s release, existing ways to communicate people's intents, interests, and the contexts they spend time in do not scale to the upcoming agentic era. We need something lighter, faster, reliable, and privacy-compliant. And UCP might be the solution for that.
If I got this right, we are kind of talking about a new language made for AI systems to exchange complex data combinations quickly as simple strings. Like an old marriage, where the husband understands immediately from the wife's look that a mistake was made? No words needed. But yeah, words-to-math is what we are talking about. Does this make more ad revenue? Well, not yet. And this goes more on the tech providers' table than publishers.
And one acronym more: ARTF, also from IAB Techlab, stands for Agentic RTB Framework. ARTF is not an AI thingy itself; more like a standardised playground for AI applications to play by jointly agreed guidelines and rules, running tasks for orchestrating and hosting platforms. Simple example: The host platform could be, for example, the publisher's ad server and the agentic service provider ID provider. And then there could be a secure container with ID decryption and matching logic.
In this scenario, publishers wouldn’t need to share their own IDs with ID providers; matching is done privately, locally, and in real time within the container. In this example, the container could be a scalable, agile, local cleanroom running ID matching in real time. Did I get it right? Of course, the ID example is only one; there can be a lot of applications and host platforms utilising the standard.
What publishers should focus on next
So, a lot of AI-related conversation topics for our Christmas tables to save awkward silent moments. And things to follow after the New Year's party. We'll continue to closely follow everything in the digital advertising domain and remain actively involved in industry-level work through associations. A lot is indeed going on, and some trends are more important right now than others. We are always ready to provide advice and help for our customers. If you need help with integrations, setting priorities or whatever, let us know if we can help!
Our AI priorities will focus on making Relevant Yield AI assistants better and better, teaching new concepts and tasks, and making it more independent and agentic. We are also building entirely new applications to support publishers' operations and sales; their launches are not too far away, so stay tuned. Once again, an exciting year ahead.
Petri Kokkonen - CEO & Partner, Member of the IAB Finland Board
Deal API: What should publishers realistically expect from it?
IAB Tech Lab’s new Deals API is currently in the public comments period until the end of January.
Traditionally, when creating a deal after negotiation, the seller has had to set up the deal in their supply-side platform (SSP), send the details to the buyer, and the buyer has had to do the same in their demand side platform (DSP). This has already changed with some SSPs and DSPs that have implemented their own APIs to ease this manual process. However, before this, there has not been a standard way of doing this. Sometimes there has been API, sometimes manual work and what has been transferred through the API has varied.
The Deals API is meant to standardise this process across systems. The API allows the details of the deal to be sent from the SSP to DSP in a standardised way, which hopefully leads to wide-scale adoption and removes some of the manual work and need for troubleshooting. It allows very minimal two-way communication in a form where the SSP is able to enquire whether the deal has been accepted or not, and whether it is active. Therefore, at least in the first version, it does not facilitate negotiations or alterations to the deals so everything needs to be confirmed already beforehand.
So the Deals API is meant to address some, but not all of the challenges all of us who have been buying or selling through deals are all too familiar with. It does not revolutionise setting up deals, nor does it guarantee that all deals that will be set up in future will be adopted by buyers. It does not even guarantee to the buyer in the first version that the deal will stay exactly the same as when it was sent. However, what it could do is standardise how deals are set up and potentially remove some manual work that is often associated with the process. It also creates potential for increased transparency by detailing the curator or other intermediaries, which has not been done before.
Overall, Deal API v1 would be a good first step in improving programmatic deals. It will most likely leave many to hope for the subsequent versions with more two-way communication and a chance for alterations after the establishment of the deal. But nevertheless, a welcome first step.
Tuukka Aaltonen - Project Manager and Vice Chair of IAB Finland’s Data & Martech Working Group
Addressability in Europe: What are the most important takeaways for publishers?
IAB Europe’s new Addressability Report highlights persistent gaps in how targeting and measurement are implemented across Europe. Adoption of privacy-centric solutions such as unified IDs, data clean rooms, and advanced contextual targeting remains uneven, and many publishers still face limited access to cross-platform data. Measurement without cookies remains one of the biggest challenges, with attribution inconsistencies slowing progress across markets.
For publishers, the most crucial takeaway is clear: first-party data and contextual strategies are becoming the default foundation for maintaining performance. As browser-level consent models reduce the availability of user-level identifiers, publishers need setups that can flexibly support multiple ID solutions and stronger contextual signals. The report also shows how wide the knowledge gaps still are. Many teams cannot assess which identity approaches actually improve results, making transparent reporting and testing critical as publishers move into 2026.
This is where platforms like Relevant Yield provide practical support: publishers can compare setups, track the real performance impact of different ID solutions, measure the effectiveness of contextual strategies, and evaluate how each configuration behaves in production. In addition to reporting, Relevant Yield’s HB Manager offers a wide range of integrated ID partners that can be enabled and tested effortlessly, as well as built-in integrations for contextual targeting, making it easier to experiment and identify what truly works for their inventory.
While no universal addressability framework has emerged, the direction is unmistakable. Success will depend on strengthening data foundations, improving measurement capabilities and adopting flexible architectures that can adapt as signal loss accelerates and privacy requirements evolve.
Suvi Leino - Head of Marketing