AI is now an essential tool in media and marketing, yet its adoption remains inconsistent across the industry. While agencies and publishers are leading the charge, many brands are struggling to keep pace, facing challenges with data quality, tool fragmentation, and governance gaps.
That’s according to IAB’s new “State of Data 2025” report (no registration required), which provides a deep dive into how AI is reshaping media planning, activation and analysis, revealing the industry’s biggest hurdles — and where companies are making the most progress.
With 70% of agencies, brands and publishers yet to fully integrate AI across media planning, activation and analysis, half of them expect to do so by 2026, signaling a critical turning point for the industry. As AI adoption accelerates, companies that fail to keep up risk falling behind their competition.
In addition to the report, the “State of Data 2025 Companion Guide” delivers actionable recommendations for brands, agencies, publishers and ad tech firms to scale AI effectively in a rapidly evolving digital ecosystem.
Who’s leading and who’s lagging?
The initial wave of AI adoption= focused on efficiency, and agencies and publishers are reaping the benefits. Twice as many agencies and publishers have fully scaled AI compared to brands, with more than 70% saying it meets or exceeds expectations for reducing manual work, optimizing resources and delivering consistent performance.
Brands, however, remain cautious. While many recognize AI’s potential, they face greater internal pressure to prove ROI and navigate data governance challenges. Their hesitation leaves them at a disadvantage, particularly as AI-driven media strategies become the norm.
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AI adoption barriers
Challenges to AI adoption are clear: Nearly two-thirds of companies struggle with data quality, security and tool fragmentation. Yet, job displacement is not a primary concern, ranking lowest at just 37% — a sign that the industry sees AI as an enhancement to human expertise rather than a replacement.
Moreover, many organizations lack a clear AI strategy. At most, only 49% of agencies, brands and publishers are using or planning to use structured solutions like strategic roadmaps, formal AI training, governance boards or KPIs for AI measurement — leaving many companies unprepared to scale effectively.
AI is becoming a competitive differentiator — those who don’t act now risk falling behind.
AI’s role in planning, activation and analysis
AI is already reshaping three key areas of media campaigns:
- Planning: AI-driven insights help refine audience segmentation, optimize media mix models, and forecast performance. However, many brands still struggle with integrating AI into their planning processes, limiting its full potential.
- Activation: AI streamlines budget allocation, cross-channel execution, and predictive bidding, with more than half of companies already leveraging AI-driven budget optimization.
- Analysis: AI enhances measurement accuracy with multi-touch attribution, predictive modeling and real-time performance insights. Yet, publishers, in particular, face unique challenges in aligning AI-driven analysis with evolving industry standards.
Even with AI’s rapid advancement, many AI tools remain underutilized:
- Two-thirds to nearly 90% of companies use widely accessible AI tools, but these lack full-scale functionality.
- Only one-third to just over half leverage organization-wide AI solutions, such as enterprise AI platforms or proprietary models.
To unlock AI’s full potential, companies need a strategic approach to scaling AI across all campaign phases.
AI strategies for brands, agencies, publishers and ad tech
For companies to fully leverage AI, they must take a phased approach to adoption. This means:
- Ensuring high-quality data inputs and outputs.
- Training teams on AI best practices and governance.
- Collaborating across the industry to establish AI standards.
- Prioritizing key AI use cases before scaling organization wide.
For brands: AI for smarter marketing and customer insights
Brands need to enhance audience segmentation, optimize marketing spend, and build AI measurement frameworks to demonstrate value.
- Data-driven planning: AI-powered insights improve segmentation and media mix models, yet many brands are still behind in fully integrating AI.
- Real-time activation: AI can help brands optimize budget allocation and cross-channel targeting.
- Advanced analysis: AI is transforming measurement, and brands must adopt modern analytics to leverage its capabilities and stay competitive.
For agencies: AI for efficiency and targeting
Agencies are outpacing brands in AI adoption due to their ability to optimize across multiple clients. Their top AI use case — adopted by half — is audience segmentation.
- Audience identification and segmentation: Agencies are using AI to refine audience targeting as consumer behaviors shift.
- Emerging generative AI: Both agencies and brands are leveraging AI to build synthetic audience segments as data signals become harder to track.
- Operational efficiency: With over 70% of agencies saying AI meets expectations for time, resource and/or cost savings — proving AI’s value in streamlining workflows.
For publishers: AI for revenue and content optimization
Publishers are leveraging AI for inventory forecasting, cross-device attribution and audience analysis while also exploring generative AI for client deliverables.
- Ad inventory optimization: AI is helping publishers predict demand, improve pricing, and place ads efficiently.
- AI-powered reporting: One-third of publishers are using generative AI for sales proposals, campaign reports, and recommendations.
Dig deeper: How B2B and B2C brands adopt genAI — same tech, different strategies
The future of AI: strategy over automation
AI adoption in media is no longer a question of “if” but “when.” More than 80% of companies that haven’t fully scaled AI have a timeline for adoption, and half expect full integration by 2026.
However, while the buy-side is accelerating AI adoption, publishers face a longer timeline due to the complexities of balancing advertiser demands, data providers and evolving industry standards.
To scale AI effectively, companies must:
- Develop clear AI adoption plans and governance frameworks
- Invest in AI training and workforce upskilling
- Address critical challenges like data quality, privacy, and AI tool fragmentation
- Ensure AI is integrated across planning, activation, and analysis
The companies that embrace AI strategically — not just as an automation tool but as a core part of decision-making—will be the ones that stay ahead.
So the real question isn’t whether AI will reshape media campaigns — it’s whether your company is ready to lead the change.
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