The report“AI Forecasts & Predictions for 2026”, on which Rob Hill, CEO of the agency Social.Lab Belgium, states that AI has moved beyond isolated productivity-boosting tools and has begun to form a new operational layer. This layer is increasingly running marketing operations itself: managing campaigns, influencing how people discover brands and products, optimising creative outputs and adjusting metrics in real time. At the same time, it brings together creativity, media, commerce, brand identity and analytics within a constantly learning system.
The report identifies 2026 as the first truly ‘AI-native’ year, in which the benefits stem not from a superficial adoption of AI, but from its responsible integration into practice, representing faster learning cycles, more accurate measurement, privacy protection, and human judgement and creativity at the very heart of the entire process.
AI is blurring the boundaries between the previously separate worlds of creativity and media, brand and performance, privacy and growth, as well as automation and the establishment of accountability and control. At the same time, it heightens the importance of trust, data quality, governance and strategic oversight. As execution accelerates and scales, execution itself ceases to be the primary source of competitive advantage. The difference between companies will increasingly lie in strategy, system design, creativity and trustworthiness. And this will have a major impact on what leaders should focus on and how they should build their agencies to succeed in the market.
In the next section of this article, we present all 12 key points from the report and also include quotes from industry experts, provided by the European Association of Advertising Agencies (EACA) as part of a discussion among its members in the AI Hub working group.
1) Agent AI as the new ‘media buyer’
The report predicts that agency AI systems – that is, tools capable of planning, executing, learning and adjusting their operations in just a few steps – will become the default operating model for media execution. This does not mean that human expertise will disappear, but that the value of human input will shift elsewhere: towards scenario planning, setting ethical boundaries and deciding when and how a human should intervene. The AI itself will then manage bidding, creative rotation and budget allocation in real time, within pre-approved rules. This will also have a significant impact on job roles: the scope for junior execution roles will narrow, whilst strategists will shift into the role of system architects who design and manage automated media operations.
2) Search is shifting from query to answer
According to the report, search no longer resembles a mere list of links, but increasingly functions as an interpretative layer of answers that infers the user’s intent, synthesises information and offers direct recommendations. This fundamentally changes the way we discover and evaluate brands, and how they build our trust. The report predicts a decline in organic visibility across a number of categories and the emergence of a new discipline, which it refers to as ‘AI-surface optimisation’ – that is, optimisation for surfaces and interfaces where the answer is delivered by AI. At the same time, the importance of retail media search interfaces – such as large e-commerce platforms – will grow as discovery channels, carrying comparable strategic weight to traditional search. In such a model, brands will be successful if they provide rich structured data, well-structured product data and well-linked customer identity data, which will help AI systems to correctly represent and recommend their offerings.
3) Creative effectiveness as the main driver of ROI
One of the key predictions is that creative effectiveness will become the most measurable and, at the same time, the most scalable driver of marketing ROI. It will cease to be merely the subject of subjective debate or post-campaign reflection and will become a quantifiable performance variable. Thanks to advances in AI-driven creative analytics and measurement frameworks, it will be possible to assess the quality of creative and directly link it to business outcomes. This shifts priorities: media effectiveness and targeting will remain important, but it is creativity that will determine whether these investments actually generate incremental value. The report predicts that data on creative quality will become just as important as reach and frequency. Specialised ‘creative intelligence’ centres will emerge, and there will be wider use of AI in tagging and classifying creative assets, which will help reduce wasted investment.
Shift towards expertise:
“AI will shift the focus of marketing ROI towards creative effectiveness. This will require organisations to stop separating creative, media, production and brand teams and start managing them within a single, unified operating model. At the same time, the relationship between client and agency will also change: agencies will shift from being execution partners to providers of specialised AI solutions, expertise and strategic orchestration.”
Matthieu Vercruysse, Publicis Groupe Belgium
4) Retail media and AI as a closed system
According to the report, retail media networks will cease to be a space for sponsored product placements and will instead transform into a closed marketing system. Within this system, it will be possible to track the entire chain from initial exposure through interaction to purchase and customer retention. AI is intended to assist with product recommendations, product page optimisation, real-time promotion management and the creation of new customer segments. This is precisely why the study’s authors consider retail media to be one of the fastest-growing AI advertising formats.
The measurement paradox:
“If AI both generates and measures marketing effectiveness, the question arises: who checks the one who checks performance? This is particularly important in the retail media environment, where the platform selling the advertising space also evaluates its own effectiveness. This is precisely why independent verification is essential. And this is precisely where agencies have an important role to play: as a party capable of challenging methodologies and not letting interpretations that are too convenient for the platforms slip through.”
David Towers, WPP Media
5) Privacy-driven marketing as a competitive advantage
Privacy is no longer seen as a constraint, but as a competitive advantage. It is becoming one of the fundamental prerequisites for trust, access to data and the responsible deployment of AI at scale. The report anticipates that structural changes – the complete phase-out of cookies and likely federal privacy regulation in the US by 2026 – will shift the entire model towards ‘first-party’ data, towards privacy-preserving measurement methods (such as clean rooms, federated learning, cryptographic attribution), and also towards consent that will be applicable for working with models.
In other words: the ability to work with data in a privacy-preserving manner should not merely be a matter of ‘compliance’, but something that truly sets companies apart. The report even claims that organisations investing in their own data systems will be significantly more successful in terms of demonstrable ROI than those that underestimate this.
6) Synthetic data as a necessity for AI training
As access to real consumer data is restricted by regulation, platform limitations and growing ethical demands, synthetic data is becoming an essential alternative that will enable the development of AI without undermining trust. It is set to become a standard part of marketing processes – for training models on creative content, simulating consumer behaviour and filling gaps in datasets. This will transform not only how models are trained, but also how they are tested and deployed. The report also predicts that agencies will begin building synthetic research laboratories, which will partially replace research panels and some traditional research methods. This would mark a shift in how insights are generated at all under stricter data handling conditions.
“Privacy-safe” does not yet mean rich in insights:
“Synthetic data may satisfy regulators, but current approaches carry the risk of homogenised datasets that reflect the assumptions of algorithms rather than actual human diversity. If personalisation strategies are derived from such data, clients may comply with the rules, but at the cost of losing relevance.
Jessica Chapplow, Heartifical Intelligence & Flywheel Digital
7) Multimodal AI creation is becoming a standard part of production
According to the report, creative production will expand significantly and accelerate as brands increasingly utilise multimodal AI, which can work simultaneously with text, images, audio and video. The authors predict that entire video production cycles will be reduced to a matter of hours, that AI-generated virtual ambassadors will become a standard part of communication, and that hyper-local creative variations will grow to thousands, or even millions, of versions. In such an environment, the role of human creatives will shift from execution itself to concept development, leadership and curation.
8) Trust in AI, security and provenance as a topic for the board
The report positions AI as both a company-wide source of risk and value, thereby elevating issues of trust, security and verifiable content provenance to the level of senior management. As AI increasingly influences creative outputs, media investment, pricing, personalisation and the customer experience, governance ceases to be merely an operational detail and becomes a strategic imperative. According to the report, boards will no longer ask whether AI is being used, but whether its actions can be trusted and verified.
The document highlights threats such as deepfakes, disinformation or ‘hallucinated’ ad placements, and anticipates wider adoption of standards relating to provenance (including C2PA – digital content fingerprints created using cryptographic hash functions), so-called ‘brand governance clouds’ and mandatory labelling of AI-generated creative. According to this logic, platforms should label AI-generated adverts in a similar way to how ingredients are listed on products.
9) Measurement is breaking through the attribution ceiling
The report claims that measurement is approaching a tipping point after years in which its value was constrained by the limits of last-click attribution, metrics reported by the platforms themselves, and fragmented dashboards. AI-powered marketing mix models and causal inference are set to shift measurement from merely counting interactions to understanding connections. This should enable continuous testing of incrementality, near-instant updates to marketing mix models, and the unification of the impact of creative, placement and audience into a single decision-making framework. Performance teams should therefore rely less on metrics directly from platforms and more on model-derived insights, which better capture the true incremental impact.
10) Premium publishers as an antidote to an AI-flooded content landscape
According to the report, generative AI will flood the open web with low-quality, duplicate or synthetic content, leading to the ‘signal getting lost’ in this deluge and weakening the advantage of a large supply of advertising space.
The response to this is expected to be a resurgence of premium publishers, as advertisers increasingly seek trust, context and differentiation. Quality will thus become scarcer, and therefore more valuable. The report anticipates the emergence of a ‘human-made inventory’ category as a premium tier and a return to more precise contextual targeting, this time no longer based on keywords but driven by AI. In this model, trust becomes one of the main currencies of targeting.
11) AI is changing the relationship between client and agency
The report predicts that AI will fundamentally reshape the client–agency relationship: from execution based on human labour, headcount and time-based remuneration towards systems, proprietary know-how and strategic orchestration. Agencies are increasingly to be judged on the strength of their ‘AI stack’, the maturity of their data governance, the strength of their ‘creative intelligence’ capabilities, and their ability to implement brand-safe automation. As AI reduces the volume of production work, the report suggests that production fees will fall and the importance of remuneration for strategic AI orchestration will grow. This will require a new definition of what clients truly value and how agency expertise is differentiated and priced.
Outdated business models:
“In an environment of autonomous systems and synthetic content, the question arises: who guarantees the integrity of the relationship between brands and people? The report rightly identifies trust as one of the key currencies of contemporary marketing. However, trust is not merely a consumer sentiment that can be optimised – it is an institutional responsibility that extends across the entire value chain. Agencies can position themselves as a responsible ‘human layer’, but this will require an open debate about outdated business models, as well as a willingness to accept that remuneration should be directed towards what has always been most valuable yet hardest to price: judgement, the ability to anticipate risks, and the orchestration of the entire complexity on behalf of the client.”
Andie Garford-Tull, Dentsu International
12) The transformation of job roles: fewer junior positions, more hybrid roles
The report predicts that the marketing workforce will undergo its greatest transformation in the last decade. AI is reshaping career paths, flattening hierarchies and redefining the meaning of ‘entry-level’. The authors expect a decline in junior operational roles in creativity, account management and media, and conversely, rapid growth in hybrid positions that combine creativity, technology and strategic judgement – such as ‘creative technology’ specialists, prompt engineers, specialists in quality control of AI outputs, or brand strategists with a strong understanding of data. According to the report, this polarisation is structural: execution is being scaled through automation, whilst human value is increasingly concentrated on oversight, conception, design and judgement.
The premium value of human creation:
“If human-created content holds premium value, purely human creative ability will become a scarce asset – and scarcity comes at a price. The risk lies in the fact that efficiency-driven restructuring may weaken precisely the resource that will achieve the highest value and margins in an AI-saturated environment.”
Ioan Ungureanu, Pastel
Competitive advantage will not simply stem from a greater volume of media bought, a larger amount of data or increased content production. What will matter are better ideas, responsible management and faster learning cycles. For leaders, this means focusing on how to manage both creativity and control with the help of AI without losing trust.
Source: aka.cz