IAB releases AI use case map for advertising professionals

The Interactive Advertising Bureau released its AI in Advertising Use Case Map on September 3, 2025, providing marketing professionals with structured guidance for understanding artificial intelligence applications across the advertising campaign lifecycle. The comprehensive framework organizes AI use cases into six distinct categories with maturity indicators distinguishing between established and emerging technologies.

According to the published document, the map addresses the urgent need for structured understanding as organizations evaluate AI opportunities, risks, and investments. "To demystify AI in advertising, help members prioritize focus areas, and provide shared language for evaluating opportunities, risks, and investments," the IAB states in its explanation of the project's objectives.

The framework categorizes AI applications across Audience Insights, Media Strategy & Planning, Creative & Personalization, Media Buying & Activation, Owned & Earned Media, and Measurement & Analytics. Each category contains specific use cases marked with visual indicators distinguishing mature implementations from emerging technologies requiring further development.

Audience Insights encompasses 12 distinct AI applications ranging from real-time sentiment analysis to synthetic data generation for modeling purposes. The category includes established applications such as customer value and engagement modeling alongside emerging capabilities like AI-powered customer identity mapping across platforms. Cross-sell and upsell recommendation engines represent mature implementations, while lookalike and behavioral cohort prediction technologies demonstrate advanced analytics capabilities.

Media Strategy & Planning contains 11 use cases spanning audience targeting, budgeting, and competitive analysis. AI-driven audience targeting and segmentation with privacy-safe methods represents established functionality, while dynamic media mix modeling showcases emerging capabilities for campaign optimization. The category emphasizes predictive analytics through seasonality forecasting and opportunity identification in emerging channels.

Creative & Personalization features 15 applications addressing content generation, testing, and optimization workflows. Automated creation and editing of copy, images, and video represents well-established capabilities including AI-powered tools for outpainting, inpainting, background removal, and upscaling. Interactive and immersive content creation through chatbots, games, augmented reality, virtual reality, and three-dimensional advertisements demonstrates advanced personalization capabilities.

Media Buying & Activation encompasses nine use cases focused on automated optimization and fraud prevention. Autonomous pacing and spend optimization agents represent mature implementations alongside rules-based media execution systems. Real-time bidding optimization and supply path optimization via AI demonstrate sophisticated programmatic advertising capabilities. The category addresses fraud detection and prevention through advanced algorithmic monitoring systems.

Owned & Earned Media includes 12 applications covering content optimization and reputation management. AI-powered social content agents and content scheduling optimization represent established capabilities, while predictive public relations outreach and media relation management demonstrate emerging applications. The category emphasizes crisis prediction and mitigation planning through automated monitoring systems.

Measurement & Analytics features 15 use cases spanning attribution analysis, performance forecasting, and data quality management. AI-driven attribution and conversion path analysis represents mature measurement capabilities, while conversational analytics assistants demonstrate emerging natural language interfaces for data access. Automated anomaly detection and alerting systems provide real-time campaign monitoring functionality.

The document includes specific technical implementations across different maturity levels. Content watermarking, fingerprinting, and provenance metadata embedding using Coalition for Content Provenance and Authenticity standards represents emerging intellectual property protection capabilities. Automated competitive separation enforcement and AI-powered bias detection systems address brand safety requirements through sophisticated monitoring algorithms.

Performance forecasting and campaign health monitoring utilizes predictive analytics to optimize media investment decisions. Yield forecasting for monetization optimization enables publishers to maximize revenue through intelligent inventory management. Natural language querying of marketing data simplifies analysis workflows through conversational interfaces that eliminate traditional dashboard complexity.

IAB Europe's research demonstrates significant adoption momentum, with 85% of companies already deploying AI-based tools for marketing purposes according to a comprehensive report released September 18, 2025. Targeting and content generation lead adoption patterns, with 64% and 61% of respondents respectively implementing these functions across European markets.

The IAB framework addresses varying implementation complexity across different use cases. Simple applications such as creative effectiveness scoring provide immediate implementation opportunities, while sophisticated systems like federated and clean-room model training require advanced technical infrastructure and expertise. Cross-platform optimization and automated data collection integration represent intermediate complexity implementations requiring coordination across multiple technology platforms.

Recent industry analysis from McKinsey identifies artificial intelligence as the most significant emerging trend for marketing organizations, with agentic AI systems moving from experimental to practical applications. The Technology Trends Outlook 2025 report positions autonomous AI agents capable of planning and execution as transformational technologies reshaping campaign management and customer targeting workflows.

The IAB document emphasizes practical implementation guidance through three primary usage scenarios. Organizations can benchmark current AI adoption against industry standards, identify relevant capabilities for experimentation or deployment, and inform strategic planning across education, product development, and policy workstreams. This structured approach enables systematic evaluation of AI opportunities aligned with organizational objectives and technical capabilities.

Technical applications demonstrate sophisticated integration across advertising workflow stages. AI-powered advertiser asset protection and content authentication chains provide intellectual property safeguards through advanced detection algorithms. Smart contracts for licensing using blockchain technology represent emerging applications combining artificial intelligence with distributed ledger systems for automated rights management.

Voice and audio content creation capabilities enable multimedia campaign development through automated generation systems. AI-powered virtual product placement in media demonstrates advanced integration between content creation and advertising placement technologies. Cultural adaptation and localization of creative assets provide international campaign scaling through automated translation and cultural sensitivity analysis.

Dynamic creative adaptation for channel and format optimization enables cross-platform campaign consistency while maintaining platform-specific requirements. Emotion-based creative resonance measurement provides sophisticated audience response analysis beyond traditional engagement metrics. These applications demonstrate the technology's evolution toward comprehensive campaign lifecycle management.

Video advertising represents a significant AI adoption area, with the Interactive Advertising Bureau's 2025 Digital Video Ad Spend & Strategy report revealing that 86% of buyers currently use or plan to implement generative AI for video advertisement creation by 2026. This adoption pattern particularly benefits small and mid-tier brands lacking resources for traditional high-quality video content production.

The framework addresses measurement complexity through advanced analytics capabilities including post-campaign analysis automation and insight generation. AI-powered sponsorship ROI modeling enables sophisticated return on investment calculations across complex partnership arrangements. Automated data quality and change detection systems ensure measurement accuracy through continuous monitoring of data integrity issues.

Marketing data cleaning and preparation agents automate workflow optimization previously requiring manual data processing resources. Natural language querying eliminates technical barriers for accessing complex marketing analytics, enabling broader organizational access to performance insights. These capabilities demonstrate artificial intelligence's potential for democratizing advanced analytics across marketing teams.

The industry faces implementation challenges alongside adoption opportunities, with the IAB Tech Lab's AI in Advertising Primer addressing terminology confusion and incomplete understanding across marketing organizations. The document emphasizes the importance of standardized frameworks for evaluating AI technologies against brand and business requirements.

Content protection and intellectual property licensing represents critical infrastructure requirements as AI-generated content becomes prevalent across advertising campaigns. Autonomous IP violation detection agents provide automated monitoring systems identifying unauthorized content usage. These capabilities address growing concerns about intellectual property protection in artificial intelligence-powered creative workflows.

The use case map distinguishes between narrow AI systems designed for specific tasks and general artificial intelligence capabilities. Current advertising applications primarily utilize narrow AI implementations including programmatic advertisement buying, customer segmentation, and chatbots for customer service. These systems demonstrate proven effectiveness within defined operational parameters while avoiding the complexity associated with general artificial intelligence development.

Brand assurance, compliance, and responsible AI implementation require sophisticated governance frameworks addressing bias detection, cultural sensitivity, and regulatory compliance monitoring. AI hallucination and misinformation detection systems provide content quality assurance through automated fact-checking capabilities. These applications emphasize the technology's role in maintaining brand safety standards while enabling creative innovation.

The document includes emerging applications such as deepfake and synthetic media detection providing content authenticity verification. Account takeover detection and response systems address security concerns through behavioral analysis and automated threat mitigation. These capabilities demonstrate artificial intelligence's dual role in enabling new capabilities while protecting against associated risks.

AI Use Case Breakdown

Content Protection & IP Licensing

• Autonomous IP violation detection agents
• Automated licensing workflow engines
• Content watermarking, fingerprinting, and provenance metadata embedding (C2PA) and AI content origin detection
• Yield forecasting for monetization optimization
• Content authentication chains
• AI-powered content valuation
• Smart contracts for licensing using blockchain
• AI-powered advertiser asset protection

Brand Assurance, Compliance & Responsible AI

• AI hallucination and misinformation detection
• Deepfake and synthetic media detection
• Bias detection in targeting and creative
• Cultural sensitivity analysis
• Compliance QA agents for brand assurance, brand guideline, and disclosure enforcement
• Regulatory compliance monitoring across local markets
• AI ethics monitoring and governance
• Carbon footprint measurement for digital campaign
• Automated competitive separation enforcement
• Automated content rights verification
• AI-powered bias and cultural sensitivity detection
• AI-assisted IP risk detection for AI-modified assets
• Malvertising and cloaking detection
• Account takeover detection and response
• AI-powered influencer content pre-screening
• AI-enabled creative accessibility compliance

Measurement & Analytics

• AI-driven attribution and conversion path analysis
• Performance forecasting and campaign health monitoring
• Conversational analytics AI assistants
• Automated anomaly detection and alerting
• Creative effectiveness scoring
• Audience engagement dashboards powered by AI
• Natural language querying of marketing data
• Marketing data cleaning and preparation agents
• Post-campaign analysis automation and insight generation
• Automated data collection and integration into data platforms
• Emotion-based creative resonance measurement
• Federated & clean-room model training
• AI-powered sponsorship ROI modeling
• Automated data quality and change detection

Media Buying & Activation

• Autonomous pacing and spend optimization agents
• Send-time and channel optimization for outreach
• Cross-channel delivery orchestration agents
• Rules-based media execution agents
• Real-time bidding optimization
• Fraud detection and prevention
• Audience fatigue prediction and frequency capping optimization
• Inventory forecasting and opportunistic buying
• Supply path optimization via AI
• Dynamic pricing and merchandising optimization

Owned & Earned Media

• AI-powered social content agents
• Content scheduling and optimization
• AI-native content visibility optimization
• AI tools for monitoring and improving brand representation in AI responses
• SEO content optimization
• Predictive PR outreach and media relation management
• Automated earned mention monitoring and analysis
• Content authority and expertise scoring
• Crisis prediction and mitigation planning
• AI-powered influencer identification and performance prediction
• Automated reputation management and response generation
• AI-powered content repurposing

Creative & Personalization

• Automated creation and editing of copy, images, and video, including AI-powered tools like outpainting, inpainting, background removal, and upscaling
• Interactive & immersive content creation (chatbots, games, AR/VR, 3D, ads)
• Real-time creative personalization & optimization
• Cultural adaptation and localization of creative assets
• AI-supported campaign activation & ecommerce personalization
• Voice and audio content creation
• AI-powered creative testing and optimization
• Creative briefing assistants and concept exploration
• Dynamic creative adaptation for channel and format
• AI-powered virtual product placement in media
• AI-generated product detail page content
• AI-powered competitive creative analysis with multimodal recognition
• Automated social content generation
• AI-powered music selection for ads

Media Strategy & Planning

• AI-driven audience targeting and segmentation with privacy-safe methods
• Budgeting & cross-channel media allocation
• AI-assisted campaign briefing and planning
• Contextual targeting using AI-based content analysis
• Dynamic media mix modeling
• Competitor insights including spend analysis, creative trends, and channel strategies
• Seasonality and market condition predictions
• Opportunity identification in emerging channels
• Dynamic summaries of inventory performance
• AI-driven knowledge search and summarization
• Audience attention prediction and media selection
• Keyword expansion

Audience Insights

• Real-time sentiment analysis & trend detection
• Voice of customer analysis from surveys, reviews, and support interactions
• Lookalike and behavioral cohort prediction
• Synthetic data generation for modeling and experimentation
• Customer value & engagement modeling
• AI-powered customer experience mapping and journey optimization
• Cross-sell/upsell recommendation engines
• Alternative-data discovery & evaluation
• Synthetic audience testing
• Predicting customer value & behavior
• AI-powered customer identity mapping/unification across platforms

Platform automation continues expanding as demonstrated by Google's announcement removing language targeting settings from Google Ads search campaigns by 2025. The platform will automatically detect user languages using artificial intelligence systems, eliminating manual campaign configuration requirements while maintaining targeting effectiveness through automated detection algorithms.

Supply path optimization via AI enables sophisticated programmatic buying decisions through real-time inventory analysis and bidding strategy adjustment. Dynamic pricing and merchandising optimization provides e-commerce integration capabilities adjusting product presentation based on user behavior patterns. These applications demonstrate artificial intelligence's capacity for complex decision-making across multiple variables simultaneously.

Inventory forecasting and opportunistic buying capabilities enable media planning optimization through predictive analytics identifying advantageous inventory acquisition opportunities. Audience fatigue prediction and frequency capping optimization prevent overexposure while maintaining campaign effectiveness through sophisticated exposure modeling algorithms.

Timeline

• September 3, 2025: IAB releases AI in Advertising Use Case Map providing comprehensive framework for marketing organizations
• September 18, 2025: IAB Europe reveals 85% AI adoption rate across European digital advertising companies
• August 18, 2025: Google announces language targeting removal from search campaigns by 2025
• July 30, 2025: Integral Ad Science receives first Ethical AI Certification from Alliance for Audited Media
• July 27, 2025: McKinsey analysis identifies AI agents as most significant marketing trend
• July 16, 2025: IAB research shows 90% of advertisers will use AI for video ads by 2026
• July 12, 2025: IAB Europe releases comprehensive AI whitepaper addressing growth and policy frameworks
• October 20, 2024: IAB Tech Lab releases AI in Advertising Primer guide for industry professionals

Summary

Who: The Interactive Advertising Bureau released the AI in Advertising Use Case Map targeting marketing organizations, advertisers, agencies, and technology providers seeking structured understanding of artificial intelligence applications.

What: A comprehensive framework organizing 84 AI use cases across six categories including Audience Insights, Media Strategy & Planning, Creative & Personalization, Media Buying & Activation, Owned & Earned Media, and Measurement & Analytics, with maturity indicators distinguishing established versus emerging technologies.

When: The use case map was released on September 3, 2025, representing the culmination of industry collaboration and research into artificial intelligence applications across advertising campaign lifecycles.

Where: The framework addresses global advertising markets with applications spanning programmatic advertising, social media marketing, connected television, search advertising, and emerging digital channels across multiple geographic regions.

Why: Organizations require structured guidance for evaluating AI opportunities, risks, and investments as artificial intelligence transforms advertising operations, with 85% of European companies already deploying AI-based marketing tools according to industry research, creating urgent demand for standardized evaluation frameworks and implementation guidance.