What are the best recommendations for implementing artificial intelligence in marketing? AI is here to stay and transform campaigns. What used to be auxiliary tools for automating tasks have now become systems capable of planning, executing, and analyzing campaigns with unprecedented precision. This is demonstrated by the latest study from the Interactive Advertising Bureau (IAB), titled State of Data 2025: The Now, The Near, and The Next Evolution of AI for Media Campaigns.
The IAB study reveals that 70% of companies have not yet fully integrated AI across all stages of their advertising campaigns, including planning, activation, and analysis. However, the outlook is promising, as half of these companies expect to achieve full adoption by 2026.
Most of those who have advanced in implementation come from agencies and publishers. As the report notes, these players value AI for its efficiency, time and resource savings, and consistent results, according to the document.
How to use Artificial Intelligence in marketing effectively? Recommendations
One of the main contributions of the study is a set of practical recommendations for implementing AI gradually, ensuring efficiency and reliability throughout the campaign lifecycle.
1. Design a phased roadmap
IAB recommends identifying all potential AI use cases (segmentation, automation, campaign optimization, attribution, etc.) and setting clear milestones for implementation. Planning should consider both business goals and the specific KPIs of the adopted AI solutions.
2. Ensure data quality and security
AI is only as good as the data it receives. Therefore, the report emphasizes the need to ensure that data is clean, structured, and protected through audits, encryption, and human oversight. The use of synthetic data, the study notes, is a powerful alternative to fill gaps and comply with privacy regulations.
3. Ongoing training and AI culture
According to IAB, it is essential to create training programs tailored to all levels of the organization. It also suggests establishing AI Centers of Excellence and fostering a culture of experimentation to adapt processes to technological advances.
4. Establish ethical and governance standards
Implementing transparency protocols, accuracy standards, fairness, and data protection is vital to avoid biases, comply with regulations, and build trust both internally and externally.
5. Prioritize key use cases
Not all solutions are equally relevant for every company. The recommendations suggest that each company identify areas where AI can have the greatest impact, such as large-scale personalization, multichannel attribution, media mix optimization, or audience creation using synthetic data.
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What benefits does artificial intelligence offer to digital marketing?
The IAB report states that more than 70% of surveyed experts believe that AI has met or exceeded their expectations in terms of:
- Efficiency: Saving time and human resources.
- Effectiveness: Meeting campaign goals.
- Reliability: Consistent results over time.
What are the main challenges in implementing AI strategies in marketing?
Despite the enthusiasm, the IAB warns that challenges are significant. Among them are:
- Data quality and readiness (62%)
- Information security and privacy (62%)
- Technological fragmentation and lack of interoperability (61%)
- Shortage of AI-specialized talent (60%)
- Lack of a clear vision for AI’s role in the company (54%)
Interestingly, concern about job loss was the least cited, at only 37%, reflecting that the industry sees AI as a complementary, not a replacement, tool.
How to transform marketing processes with AI?
The report proposes a comprehensive vision that divides the campaign lifecycle into three main phases:
Planning
- Audience generation with synthetic data
- Budget simulation to forecast ROI
- Predictive analysis of inventory and performance
Activation
- Real-time bid optimization
- Dynamic adjustments to budgets and segmentations
- Automated generation of creatives and formats
Analysis
- Multitouch attribution using multiple sources
- More accurate marketing mix models
- Anomaly detection and ad fraud prevention
What does IAB recommend to leverage AI in marketing strategies?
Beyond technical recommendations, the IAB calls on the advertising ecosystem to collaborate and move forward together. Among its final suggestions are:
- Promote interoperability across platforms
- Establish contractual clauses on the use of AI
- Conduct regular bias and fairness audits
- Adopt sustainability standards in model development
- Promote collaboration among brands, agencies, publishers, and tech providers
Artificial intelligence is already transforming marketing. However, companies that do not act strategically risk falling behind. The difference between leaders and laggards will be defined mainly by the level of AI adoption throughout the entire campaign lifecycle.
