Interactive Advertising Bureau (IAB) has published its report “State of Data 2025: The Now, The Near, and The Next Evolution of AI for Media Campaigns”, revealing how artificial intelligence has been integrated into various stages of media campaigns, highlighting opportunities and challenges for those looking to boost their competitiveness in an increasingly demanding market.
We analyze the key findings from this report, the impact of AI on marketing, and the industry’s response to the possibilities offered by this technology. The goal is to provide a comprehensive view for those interested in exploring the current and future dynamics of Artificial Intelligence applied to digital marketing.
Why is Artificial Intelligence Transforming Digital Marketing?
AI has been present in various areas of digital marketing for years, but recent developments—particularly with generative AI and agentic AI models—have challenged traditional methods of campaign analysis and execution. This leap not only improves specific processes (such as bid optimization or audience segmentation) but also proposes much deeper changes in how campaigns are planned, activated, and analyzed.
IAB’s “State of Data 2025” study shows that this technology is no longer seen merely as a tool to streamline tasks; today, it can “think, plan, and execute” with increasingly high levels of accuracy. In fact, artificial intelligence not only creates audiences from collected data but can also generate synthetic data (“fake” but statistically modeled data) to compensate for the loss of signals caused by restrictions on third-party cookies. In the context of digital marketing, this opens new doors for personalization and attribution strategies, even in environments with limited data access.
AI in Agencies, Brands, and Publishers
One of the most relevant findings from the report is that, despite the importance of Artificial Intelligence and its disruptive potential, 70% of companies—including agencies, brands, and publishers—have not yet fully and consistently adopted AI across all stages of their media campaigns. In other words, although there is significant interest and ongoing pilot programs, most companies are still in limited or experimental integration phases.
However, the future outlook appears optimistic: half of companies that have not yet fully integrated AI expect to achieve full integration by 2026. The study also highlights additional key points:
- Agencies and Publishers Lead the Way: These groups tend to integrate AI more quickly and effectively than brands. Agencies, for example, value AI for its efficiency and ability to create audiences across various client verticals, while publishers use it to forecast inventory and better understand user behavior.
- Brands are Falling Behind: Adoption among brands has been slower, partly due to internal requirements to justify ROI. About 60% of surveyed brands mention costs and resource allocation as major barriers.
Nevertheless, the trend is clear: 80% of those who have not fully adopted AI have established timelines and expect significant progress in the coming years.
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What are the Main Benefits of AI for Marketing?
The IAB study highlights AI as a critical factor in taking digital marketing to the next level of efficiency. Among the perceived benefits, the following stand out:
- Efficiency in Time and Resources:
- 76% of participants indicate that AI meets or exceeds expectations in reducing manual labor.
- Agencies point out that analyzing large volumes of data and automating reporting significantly accelerate processes.
- Effectiveness in Achieving Goals:
- 71% report that AI delivers desired performance based on established KPIs, whether in terms of cost-per-acquisition (CPA) or brand awareness.
- In audience management, AI enables real-time updating and refinement of strategies.
- Long-Term Reliability:
- 73% consider AI reliable in terms of consistent results.
- Although some brands remain cautious, an increasing number of publishers and agencies express high satisfaction with AI’s predictive capabilities.
This combination of efficiency, effectiveness, and reliability confirms why artificial intelligence is currently considered one of the strategic pillars of modern marketing.
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Uses of Artificial Intelligence in Digital Marketing
The document details specific use cases in each phase of the campaign lifecycle, including:
Planning Phase
- Audience Segmentation: A large percentage of agencies (over 50%) use AI to identify audiences and microsegments, leveraging behavioral data across multiple channels.
- Generating Proposals (RFPs): Publishers are beginning to use AI to rapidly respond to advertiser requests, optimizing negotiation times.
Activation Phase
- Real-time Bid Optimization: Both agencies and brands seek to automate bid adjustments. AI reviews campaigns minute-by-minute, allocating budgets to the most profitable channels and segments.
- Content Creation: Although still limited, generative AI is increasingly used for creating creative pieces and ad variations—something that giants like Coca-Cola and Suzuki are already implementing.
Analysis Phase
- Multi-touch Attribution (MTA) and Marketing Mix Modeling (MMM): To measure real campaign impact, AI combines multiple data sources, even synthetic data, to fill measurement gaps.
- Anomaly Detection and Ad Fraud: Though still in development, there is a growing trend toward using AI to monitor suspicious activities and enhance brand safety.
What Barriers Does Artificial Intelligence Face in Digital Marketing?
Despite the enthusiasm, the study highlights significant obstacles preventing the complete adoption of AI:
- Data Quality and Security:
- 62% of respondents describe as “critical” the complexity of preparing and maintaining an optimal data environment.
- Concerns also include protection against data breaches and compliance with privacy regulations.
- Technological Fragmentation:
- Nearly 60% mention difficulties integrating multiple AI platforms and tools.
- Lack of interoperability among solutions leads to high implementation costs.
- Lack of Internal Expertise:
- 58% view the shortage of expert AI talent as a significant limitation.
- Additionally, only 49% are developing solutions such as strategic roadmaps or user guidelines.
- Governance and Regulation:
- 54% emphasize legal and governance risks, including unclear accountability for outcomes and data management.
- The industry needs common standards, especially given the rise of generative models and increasing scrutiny from regulatory authorities.
- Cultural Resistance:
- Among agencies, 56% acknowledge that certain clients or internal teams doubt the reliability of AI.
- Brands remain concerned about partner transparency when employing AI.
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The Future of Marketing and Artificial Intelligence
The IAB study indicates that as AI evolves, a complete transformation of roles and workflows involved in digital marketing is expected. On the employment front, AI is not expected to entirely replace professionals, but rather to demand new profiles capable of interpreting and interacting with automated models.
Furthermore, industry cooperation will be crucial for success. Establishing standards that encompass everything from data hygiene to accountability in the use of generative models, along with transparent measurement methodologies, will be essential. Without addressing this, fragmentation will remain an obstacle to adoption.
In the short term (2025-2026), most companies are expected to be in advanced pilot and adoption stages, rapidly validating AI’s effectiveness. This period will involve adjustments and experimentation, evaluating which tools deliver greater ROI and identifying marketing areas worth deeper investment.
For the medium term (2026 onward), the expectation is that AI will naturally integrate into all processes within the advertising industry. The proliferation of synthetic data and consolidation of high-precision generative models will pave the way for large-scale personalization and more refined attribution. Likewise, new business models based on transparency and shared accountability will emerge.
