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1、State of Data 2025 Companion GuideA Strategic Playbook for Agencies,Brands,Publishers,and Ad TechMarch 2025SPONSORED BY:STATE OF DATA 2025:Additional AI Recommendations ContentsPreface:An AI-Driven Approach to Smarter Marketing&Measurement0304Recommendations for Agencies0810Recommendations for Publi

2、shersRecommendations for Ad Tech&Measurement Providers2Recommendations for Brands 06STATE OF DATA 2025:Additional AI RecommendationsPreface:An AI-Driven Approach to Smarter Marketing&Measurement3This document serves as a companion to the IAB State of Data 2025 report,providing a strategic playbook f

3、or brands,agencies,publishers,and ad tech providers to navigate the evolving marketing landscape with AI-powered solutions.As AI becomes central to planning,activation,analytics,and optimization,industry stakeholders must adopt data-driven,privacy-first strategies to enhance media efficiency,measure

4、ment accuracy,and cross-channel effectiveness.This paper outlines key AI applications that stakeholders should prioritize,focusing on both long-term transformation and immediate,actionable solutions to stay competitive in an increasingly fragmented and regulated digital environment.With privacy regu

5、lations reshaping data availability and media fragmentation increasing complexity,brands must move toward AI-powered data integration,audience intelligence,and campaign automation to enhance cross-channel marketing effectiveness.Agencies,facing signal loss and evolving attribution challenges,must in

6、corporate AI-driven market mix modeling,predictive analytics,and real-time optimization to ensure more efficient media investment and performance measurement.For publishers,AI-enhanced inventory management,yield optimization,and contextual intelligence will be essential to maximizing revenue and del

7、ivering advertiser value in a privacy-first ecosystem.At the same time,ad tech and measurement providers must develop AI-powered solution for activation,attribution,and real-time optimization,ensuring that marketers and publishers can effectively measure success and adapt strategies in an environmen

8、t with fewer deterministic signals.To provide clear,actionable guidance,this supplement delivers both strategic direction and tactical implementation recommendations,helping industry stakeholders bridge the gap between long-term AI adoption and immediate operationaliimprovements.By leveraging AI-dri

9、ven automation,predictive modeling,and synthetic data strategies,businesses can drive greater efficiency,stronger audience engagement,and more precise measurement capabilities.In addition to the recommendations,specific AI-driven solutions are provided.These additional insights will provide stakehol

10、ders with more concrete applications of AI,reinforcing the practical steps needed to integrate AI-powered planning,activation,and measurement across the marketing ecosystem.The following sections explore how brands,agencies,publishers,and ad tech providers can implement AI-driven strategies today wh

11、ile preparing for the future,ensuring they remain agile,competitive,and privacy-compliant in an increasingly AI-powered world.STATE OF DATA 2025:Additional AI Recommendations AGENCIESRecommendations for Agencies to Leverage AI in Media Strategy4Integrate AI as a Core Component of Media PlanningAgenc

12、ies can strengthen media planning by incorporating AI-driven insights from ad tech platforms alongside first-party data,second-party partnerships,and probabilistic modeling.To navigate signal loss and privacy regulations,leveraging market mix modeling(MMM)and multi-touch attribution(MTA)provides a c

13、omprehensive view of media effectiveness.AI also enhances media partner selection and RFP evaluations by predicting success based on historical data,brand alignment,and projected ROI.Continuously Optimize Audiences&Campaigns Across PlatformsAI enables dynamic reassessment of audience behaviors and t

14、argeting refinements across display,search,social,and CTV throughout campaigns.To maintain privacy compliance while driving performance,agencies should incorporate probabilistic modeling and synthetic personas.AI-powered orchestration tools can adjust bids,pacing,and creative rotation in real time,e

15、nsuring efficiency in an increasingly fragmented media environment.Implement Real-Time Budgeting,Pacing&Anomaly DetectionAgencies can optimize spend,bids,and budget allocations with predictive AI models that adjust based on real-time performance.Automated quality assurance and anomaly detection help

16、 identify irregularities,such as suspicious traffic,cost fluctuations,or sudden performance drops,allowing for immediate course correction.AI-driven automation ensures campaigns remain efficient,privacy-safe,and accountable.Leverage AI-Powered Analytics for Smarter Decision-MakingWith deterministic

17、identifiers becoming more restricted,agencies should centralize cross-channel performance data from DSPs,ad servers,and SSPs using AI-powered analytics.Integrating MMM and MTA helps fill data gaps and identify effective strategies.AI-generated reports can provide clear next steps,such as rebalancing

18、 investments based on historical trends and predictive modeling.AI dashboards integrating contextual signals,pacing insights,and ROI metrics support real-time decision-making.Adopt Advanced Measurement&Iterative LearningAgencies can improve campaign effectiveness by implementing AI-enhanced attribut

19、ion frameworks that combine MMM with MTA.AI enables cross-client campaign insights to uncover high-performing strategies and scalable optimizations,while maintaining privacy compliance.Taking an iterative learning approach ensures agencies continuously refine strategies,improve ROI,and enhance measu

20、rement accuracy.Leverage AI to Maintain a Competitive EdgeAI is no longer optionalit is essential for navigating cross-channel complexity,signal loss,and evolving privacy regulations.Agencies that integrate AI-driven MMM,MTA,and probabilistic modeling will stay ahead of market shifts,deliver stronge

21、r client outcomes,and build a sustainable competitive advantage in a privacy-first media ecosystem.STATE OF DATA 2025:Additional AI Recommendations 5 PlanningRefine Audiences&Optimize Media Mix.Leverage AI-powered audience segmentation by integrating first-party data,second-party partnerships,and sy

22、nthetic personas with contextual signals.Use AI-driven scenario planning and Market Mix Modeling(MMM)to simulate channel allocations,forecast ROI,and optimize media spend in real time.Streamline Media Partner Selection&Strategic Insights.Apply AI-based scoring to evaluate RFP responses,assess histor

23、ical performance,and identify top-performing media partners that align with client goals.Use AI to analyze market data and refine partner recommendations based on brand alignment and predicted ROI.Monitor Competitors&Market Trends.Deploy AI tools to track competitor activity,emerging trends,and mark

24、et shifts,integrating insights into planning strategies.Enhance Collaboration&Continuous Improvement.Use real-time AI-driven insights in collaborative workshops,establishing feedback loops to refine audience segmentation,media mix,and partner selection,ensuring continuous campaign improvement.Activa

25、tionOptimize Campaign Orchestration&Audience Targeting.Use AI-powered automation to manage paid campaigns across display,search,social,and CTV,making real-time adjustments to maximize ROI.Continuously refine audience segmentation mid-flight with AI modeling and synthetic data to improve cross-channe

26、l alignment and performance.Enhance Budgeting,Pacing&Forecasting.Leverage predictive AI to dynamically adjust bids and budgets,refining pacing and forecasts by comparing real-time performance metrics(CPA,CTR)to predicted outcomes for maximum efficiency.Automate Quality Assurance&Anomaly Detection.De

27、ploy AI-driven monitoring to track key performance indicators across cost,conversions,and click patterns,quickly detecting and resolving anomalies like suspicious traffic or performance shifts to protect campaign ROI.Enable Transparency with AI-Powered Dashboards.Utilize collaborative dashboards to

28、integrate cross-channel performance and ROI metrics,ensuring transparent,data-driven decision-making across teams and clients.AnalyticsCentralized Data Aggregation&Benchmarking.Consolidate performance data(impressions,conversions,revenue)into an AI-ready environment to uncover cross-campaign pattern

29、s and create actionable benchmarks for smarter decision-making.AI-Driven Reporting&Recommendations.Use natural language generation to automate wrap-up reports,translating complex data into clear,predictive insights.AI-driven recommendations help adjust budget allocations and optimize channel investm

30、ents based on historical synergies.Flexible MMM&Advanced Attribution.Integrate Market Mix Modeling(MMM)with multi-touch attribution,adapting to client-specific data and KPIs.Leverage synthetic or proxy data to fill measurement gaps while maintaining privacy compliance.Real-Time Monitoring&Continuous

31、 Optimization.Combine historical data with live performance metrics to refine forecasts,optimize underperforming segments,and dynamically adjust the media mix,ensuring campaigns remain agile and ROI-focused.AGENCIESRecommended AI Applications and Use CasesSTATE OF DATA 2025:Additional AI Recommendat

32、ions BRANDSRecommendations for Brands to Leverage AI in Marketing6Transition to a Unified,AI-Driven StrategyTo fully harness AI,brands need to move beyond siloed campaign management and adopt a data-driven strategy that integrates marketing signals from ad tech,mar tech,and paid,owned,and earned cha

33、nnels.This consolidation enables continuous audience recalibration,ensuring marketing efforts remain adaptive,scalable,and aligned with consumer behavior.Leverage Holistic Audience Insights Across PlatformsBrands can create a comprehensive consumer view by integrating data from CRM,CDP,site analytic

34、s,ad servers,DSPs,SSPs,and media measurement platforms.A cross-channel strategy ensures that AI-driven optimization accounts for the entire marketing funnel,helping brands identify synergies and make smarter investment decisions.Continuously Adapt to Audience Behavior ShiftsAI-powered analytics enab

35、le brands to detect emerging patterns and refine audience segmentation in real time.Marketers should leverage AI to adjust messaging dynamically based on real-time engagement data across programmatic,direct,and organic channels.By continuously reassessing behaviors,brands can improve targeting preci

36、sion and content relevance.Optimize Campaign Execution for Agility&EfficiencyAI-driven campaign optimization helps brands make real-time adjustments to media mix modeling,bid strategies,pacing,and audience segments.Automated AI tools reduce wasted spend,enhance budget flexibility,and improve overall

37、 campaign performance by continuously refining targeting and media allocations.Use Predictive AI for Future-Ready Marketing StrategiesPredictive AI enhances strategic foresight by anticipating shifts in consumer demand,media performance,and competitive landscapes.Brands can benefit from AI-driven sc

38、enario planning,which helps proactively adjust budget allocations,media strategies,and audience segmentation based on historical and real-time data.This approach future-proofs marketing efforts and strengthens resilience in a dynamic environment.Scale AI-Driven Automation for Continuous Performance

39、ImprovementTo ensure long-term success,brands should integrate AI-driven automation and iterative learning frameworks into their marketing operations.AI can refine campaign models,audience segmentation,and media pacing based on performance insights.Automated multi-touch attribution modeling and dyna

40、mic optimization enhance efficiency,allowing marketing teams to focus on strategic growth.Build a Future-Proof AI-Enabled Marketing FrameworkAI is revolutionizing brand marketing by enabling real-time data integration,continuous audience assessment,and adaptive campaign execution.Brands that unify a

41、d tech and mar tech ecosystems,embrace predictive analytics,and scale AI-powered automation will drive greater efficiency,performance,and long-term marketing resilience.STATE OF DATA 2025:Additional AI Recommendations 7 PlanningUnify Data for Smarter Audience Targeting.Integrate CRM,CDP,site analyti

42、cs,and other platforms to power AI-driven audience segmentation and persona refinement,ensuring more precise and effective targeting.Optimize Media Mix with AI-Driven Scenario Planning.Use AI-powered modeling to optimize marketing mix across paid,owned,and earned channels,maximizing efficiency and i

43、mpact across display,social,CTV,websites,email,and PR.Leverage AI for Market Intelligence&Strategic Decision-Making.Deploy AI tools to monitor competitor movements,track consumer sentiment,and identify emerging trends,focusing on insights that drive smarter strategic pivots.Enhance Journey Mapping&C

44、ontingency Planning.Use AI-driven journey mapping to analyze consumer pathways across online and in-store experiences,identifying friction points and aligning marketing efforts.Run“what-if”simulations to plan for market shifts,ensuring budget flexibility and minimal disruptions.ActivationAI-Driven C

45、ampaign Orchestration&Content Optimization.Leverage AI tools to coordinate and launch campaigns across paid,owned,and earned channels.Monitor real-time performance and automatically adjust tacticsincluding modifying content,enhancing the user experience,and shifting targeting strategies.Continuously

46、 Reassess Audiences&Personas.Use fresh,in-flight data from all channels to refine your audience segments.Combine emerging signals(like updated contextual data and lookalike insights)with your first-party data to regenerate synthetic personas that remain current and privacy safe.Recalibrate Market Mi

47、x,Pacing,and Forecasts.Employ ongoing scenario planning that incorporates comprehensive data from all advertising and marketing channels.Recalibrate your media mix and pacing while generating updated forecasts based on real-time performance,ensuring every investment is optimized for maximum ROI.Iter

48、ate AI-Enhanced Testing Frameworks.Adapt testing parameters mid-flight as AI identifies new audience behaviors or flags underperforming tactics.Scale successful variations and retire those that lag,continuously feeding updated performance data back into your models for ongoing improvement.AnalyticsI

49、ntegrate AI for Attribution&Performance Insights.Consolidate CRM,CDP,site analytics,and media performance data into a unified AI-powered dashboard.Leverage multi-touch attribution(MTA)and market mix modeling(MMM)to track direct interactions and channel synergies for more accurate measurement.Enhance

50、 Decision-Making with Real-Time Dashboards&Predictive Analytics.Use AI-powered dashboards to aggregate real-time cross-channel data,ensuring faster,data-driven decisions and improved transparency with agency partners.Implement AI forecasting models to predict reach,engagement,and ROI,allowing for pr

51、oactive budget and strategy adjustments.Refine Audience Segmentation&Behavioral Analysis.Analyze audience behavior,uncover hidden segments,and identify emerging trends with AI-driven insights.Use these findings to enhance personalization and sharpen targeting across paid,owned,and earned channels.Au

52、tomated Anomaly Detection&Iterative Model Refinement.Deploy AI-powered anomaly detection to monitor key performance indicators,automatically flagging unexpected deviations.Use real-time feedback to iteratively refine analytics models,ensuring agility and responsiveness to market changes.BRANDSRecomm

53、ended AI Applications and Use CasesSTATE OF DATA 2025:Additional AI Recommendations PUBLISHERSRecommendations for Publishers to Leverage AI for Growth&Efficiency8Adopt AI for Smarter Inventory&Revenue ManagementPublishers can maximize revenue opportunities by using AI-driven predictive analytics and

54、 dynamic yield management to optimize pricing,forecast demand,and allocate inventory strategically across multiple channels.Automating trafficking,bidding adjustments,and inventory discovery allows publishers to align high-value placements with advertiser goals while improving operational efficiency

55、.Automate RFP&Proposal Management for Data-Driven DealsAI enhances RFP analysis and response generation,helping publishers quickly identify advertiser needs and build data-backed,outcome-focused proposals.By integrating consumer insights,past performance,and revenue potential,AI improves deal conver

56、sion.Predictive modeling further increases advertiser confidence by presenting clear performance expectations and value propositions.Optimize Campaign Orchestration&Real-Time PerformanceAI-powered automation enables publishers to streamline campaign scheduling,activation,and tracking,ensuring seamle

57、ss execution across platforms.AI tools can dynamically adjust bid strategies,pacing,and creative rotation to enhance engagement and ad relevance.With continuous audience and content optimization,publishers can effectively serve a diverse set of advertisers while maintaining audience alignment.Streng

58、then Brand Safety,Suitability&ViewabilityTo mitigate brand safety risks,publishers can leverage AI-driven risk assessment for real-time ad placement monitoring,content suitability tracking,and viewability optimization.Contextual AI and sentiment analysis allow publishers to proactively shift ad plac

59、ements,safeguarding advertiser trust and maintaining high-quality inventory across audience segments.Leverage AI-Powered Analytics for Smarter Insights&ForecastingPublishers are encouraged to consolidate cross-channel performance data into AI-powered analytics dashboards,enabling holistic inventory

60、analysis,cross-client benchmarking,and trend identification.AI-driven reach,frequency,and attribution modeling helps refine inventory allocation and pricing strategies.Additionally,predictive AI models support revenue forecasting,allowing publishers to proactively adjust monetization strategies to a

61、lign with advertiser demand.Develop a Scalable,AI-Driven Growth StrategyAI is redefining how publishers manage inventory,optimize revenue,and strengthen advertiser relationships.By integrating AI-driven yield management,campaign automation,and predictive analytics,publishers can streamline operation

62、s,enhance audience engagement,and maximize ROI across cross-channel environments.As privacy regulations evolve and deterministic signals decline,embracing AI-powered probabilistic modeling,dynamic attribution,and contextual intelligence will be essential for sustainable growth and long-term success.

63、STATE OF DATA 2025:Additional AI Recommendations 9 PlanningAutomated RFP Analysis&Response Generation.Parse incoming RFPs,highlight key requirements,and draft initial responses based on past successes.This approach speeds up the process and ensures consistency across all submissions.Intelligent Inve

64、ntory Discovery&Optimization.Scan and evaluate your inventory across platforms,identifying high-value placements that match client needs.Predictive analytics can forecast inventory availability and revenue potential,guiding smarter allocation decisions.Data-Driven Proposal Assembly&Consumer Insights

65、 Integration.Consolidate performance metrics,audience insights,and consumer journey data using AI tools.Use natural language generation to craft tailored proposals that not only articulate expected ROI but also demonstrate how strategic placements influence consumer behavior.Collaborative AI-Enhance

66、d Planning Workflows.Integrate AI-powered project management and reporting tools to streamline the planning processfrom RFP analysis to proposal finalizationensuring alignment,transparency,and effective collaboration among all stakeholders.ActivationAI-Driven Campaign Orchestration.Schedule,launch,a

67、nd monitor campaigns in real time while automating trafficking and ad placements.Ensure creative assets reach the right platforms at optimal times,reducing manual workload and improving efficiency.Dynamic Yield Management,Budgeting and Pacing Optimization.Combine predictive budgeting with dynamic yi

68、eld management and header bidding into one seamless process.Adjust bids,redistribute budgets,recalibrate pacing,and optimize header bidding strategiesall based on live performance metricsto maximize revenue opportunities and ROI.Continuous Audience,Creative&Content Optimization.Monitor audience enga

69、gement,creative performance,and content resonance mid-flight.Use these insights to fine-tune targeting strategies,adjust messaging,and optimize content across channels,ensuring campaigns remain effective and responsive to evolving consumer behavior.Enhanced Brand Safety,Suitability&Viewability Optim

70、ization.Continuously monitor ad placements for brand safety,evaluate content suitability,and track viewability metrics.Automatically adjust placements to avoid risky environments and ensure ads meet strict brand guidelines while maximizing exposure and engagement.AnalyticsUnified Inventory Analytics

71、 Dashboard.Integrate data from O&O channels and third-party audience extensions into a unified dashboard for cross-channel comparisons and comprehensive inventory insights.Use AI-driven forecasting to predict key performance metrics such as revenue,engagement,and ROI.Benchmarking&Trend Analysis.Aggr

72、egate and analyze data across your client portfolio,creating industry benchmarks and spotting cross-campaign patterns.Identify emerging trends to refine future strategies.Advanced Reach,Frequency&Attribution Modeling.Measure and manage reach and frequency across devices and channels,while applying m

73、ulti-touch attribution to assess incremental impact and optimize revenue strategies.Predictive Performance,Audience Insights,and Content Optimization.Analyze audience behavior through engagement metrics such as viewability,time on page,and content interaction across different inventory elements.Opti

74、mize inventory allocation,and tailor content strategies based on audience behavior.PUBLISHERSRecommended AI Applications and Use CasesSTATE OF DATA 2025:Additional AI Recommendations AD TECHRecommendations for Ad Tech&Measurement Providers to Leverage AI10Develop AI-Driven Media Planning&Forecasting

75、 SolutionsAd tech providers must create AI-powered media planning tools that enable brands,agencies,and publishers to test cross-channel scenarios before activation.AI models need to support first-party,second-party,and privacy-compliant data to allow granular audience segmentation and budget optimi

76、zation.Interactive,AI-powered dashboards can integrate historical performance trends,competitive insights,and predictive analytics to help advertisers fine-tune strategies before launch for maximum efficiency and performance.Enable Real-Time Integration&Optimization for ActivationTo drive greater ef

77、ficiency,ad tech platforms can focus on seamless integration across DSPs,SSPs,ad servers,social platforms,and verification solutions for real-time bid,pacing,and targeting updates.AI-powered budget reallocation enables adaptive media investment strategies,continuously adjusting bid strategies,creati

78、ve placements,and audience targeting based on in-flight performance data.AI-driven anomaly detection plays a crucial role in identifying performance trends,fraud risks,and efficiency gaps,triggering automated alerts and self-correcting mechanisms to maintain campaign health and maximize ROI.Offer a

79、Unified,AI-Powered Measurement FrameworkMeasurement providers are encouraged to integrate multi-touch attribution(MTA)and market mix modeling(MMM)into a single framework that allows brands and agencies to analyze real-time channel performance and long-term impact.AI-powered models incorporating prob

80、abilistic approaches help address signal loss and privacy regulations,ensuring continued measurement accuracy.AI-driven automation enhances incremental lift and synthetic control group testing,offering marketers a transparent view of campaign impact across devices and media environments.A centralize

81、d AI-driven dashboard consolidates real-time attribution,MMM insights,and revenue impact,providing clear,actionable insights to optimize future media investments.Strengthen Industry Trust,Standards&CollaborationTo foster industry-wide AI adoption,ad tech and measurement providers must focus on trans

82、parency,governance,and interoperability.Establishing AI governance frameworks promotes responsible AI use and compliance with data privacy regulations.Ad tech providers can enhance AI-powered solutions by collaborating with brands,agencies,and publishers to refine solutions with real-world use cases

83、,improving interoperability and cross-industry collaboration.Clear,explainable AI reportingincluding data sources,decision logic,and model performance metricshelps build trust and accelerate AI adoption across the digital advertising ecosystem.Drive AI Innovation While Ensuring Privacy&ComplianceAs

84、AI becomes central to media planning,activation,and measurement,ad tech providers need to prioritize building adaptable,privacy-first solutions that support cross-channel execution,probabilistic modeling,and automated optimization.By integrating real-time intelligence,unified measurement frameworks,

85、and transparent AI reporting,these platforms empower brands,agencies,and publishers to execute smarter,more efficient,and privacy-compliant marketing strategies.The future of AI in advertising relies on interoperability,responsible AI adoption,and industry-wide collaboration,ensuring AI-powered solu

86、tions evolve alongside changing regulations and technology.STATE OF DATA 2025:Additional AI Recommendations 11 PlanningAI-Driven Media Planning&Forecasting.Build solutions that examines multiple scenarios(channels,budgets)so agencies,brands and publishers can forecast outcomes before launch.Flexible

87、 Data Integration for Targeting.Offer flexible APIs or modules that combine first-party,second-party,and contextual data,enabling granular,privacy-compliant audience targeting and synthetic persona creation.AI-Powered Market Intelligence&Trend Analysis.Embed market intelligence tools that analyze hi

88、storical performance,current market trends,and competitive activity.This real-time insight empowers agencies and brands to refine channel strategies,budget allocations and/or revenue forecasts.Interactive AI Planning Dashboards.Develop interactive dashboards that allow cross-functional teams to simu

89、late multiple scenarios.Visualize potential outcomes,and allow stakeholders to collaboratively fine-tune strategies.ActivationSeamless Cross-Platform Integration.Create plug-and-play integration with DSPs,SSPs,social platforms,ad servers,ad verification solutions,and CRM systems,ensuring seamless da

90、ta flows for bid,pacing,and targeting updates.AI-Driven Budget&Bid Optimization.Implement AI models that autonomously optimize budgets and bidding strategies based on in-flight performance metrics,letting brands,agencies and/or publishers pivot quickly as market conditions change.Additionally,dynami

91、cally adjust pacing,targeting,and spend allocation to maximize performance in evolving market conditions.Intelligent Anomaly Detection&Auto-Correction.Track campaign KPIs,promptly flagging any irregularities or performance dips.Enable self-correcting mechanisms provide automated alerts for brands,ag

92、encies,and publishers swiftly resolve issues.AnalyticsUnified Attribution&Market Mix Modeling.Combine multi-touch attribution with market mix modeling in one platform,so agencies and brands can see real-time channel interactions wiand longer-terms impact without switching tools.Incrementality Measur

93、ement.Automate holdout or synthetic control group comparisons,providing a straightforward view of campaign incremental lift and ROI across devices and environments.Integrated Cross-Channel Measurement Dashboards.Consolidate data for multi-touch attribution and market mix modeling into a single,intui

94、tive interface.Enable agencies and brands to visualize channel interactions,incremental lift,and ROI in real time.Adaptive AI-Powered Model Refinement.Continuously refine measurement models based on both historical and live campaign data.Provide an adaptive approach that includes attribution,forecas

95、ting,and recommendations.AD TECHRecommended AI Applications and Use CasesSTATE OF DATA 2025:Additional AI Recommendations 12About our sponsorsPlatinum SponsorOneTrusts mission is to enable the responsible use of data and AI.Our platform simplifies the collection of data with consent and preferences,

96、automates the governance of data with integrated risk management across privacy,security,IT/tech,third-party,and AI risk,and activates the responsible use of data by applying and enforcing data policies across the entire data estate and lifecycle.OneTrust supports seamless collaboration between data

97、 teams and risk teams to drive rapid and trusted innovation.Recognized as a market pioneer and leader,OneTrust boasts over 300 patents and serves more than 14,000 customers globally,ranging from industry giants to small businesses.For more information,visit .Premier Sponsor Dotdash Meredith(DDM)is t

98、he largest print and digital publisher in America.Nearly 200 million people trust us each month to help them make decisions,take action,and find inspiration.Dotdash Merediths over 40 iconic brands include PEOPLE,Better Homes&Gardens,Verywell,Food&Wine,Travel+Leisure,Allrecipes,REAL SIMPLE,Investoped

99、ia,and Southern Living.Dotdash Meredith is based in New York City and is an operating business of IAC(NASDAQ:IAC).STATE OF DATA 2025:Evolution of AI for Media Campaigns13Further resources from IAB and IAB Tech LabIAB Generative AI Playbook for Advertising provides an overview of AI models,dives into

100、 key use cases including content creation,campaign optimization,and measurement,and offers frameworks and checklists for evaluating tools and ensuring responsible implementation and use.Legal Issues and Business Considerations When Using Generative AI in Digital Advertising examines the opportunitie

101、s and risks of creating,training,and implementing generative AI in digital advertising,focusing on legal,ethical,and operational challenges such as intellectual property concerns,bias,misinformation,and brand safety.The following guidelines,insights,and playbooks are resources to help the digital ad

102、 industry expand their knowledge of AI and adapt to its evolving impact.IAB AI Use Cases and Best Practices for Marketing explores how AI enhances digital marketing through audience targeting,creative optimization,privacy compliance,and automation,providing best practices and real-world use cases fo

103、r agencies,brands,and technologists.Understanding Bias in AI for Marketing provides a comprehensive guide on identifying,mitigating,and managing bias in AI-powered marketing and advertising systems,emphasizing the importance of transparency,accountability,and ethical AI practices across the AI syste

104、m lifecycle.IABs State of Data Hub features previous editions of the State of Data report and other,in-depth analyses of key trends,insights,and strategies shaping the future of data-driven advertising.Gain expert perspectives on critical topics such as privacy regulations,AI integration,and the evo

105、lving data ecosystem.IABs State of Data 2025 Report provides the first-ever industry benchmarks on AI usage,adoption rates,and perceptions as well as challenges,opportunities,and future needs within the media campaign lifecycle.STATE OF DATA 2025:Evolution of AI for Media CampaignsThe Interactive Ad

106、vertising Bureau empowers the media and marketing industries to thrive in the digital economy.Its membership comprises more than 700 leading media companies,brands,agencies,and the technology firms responsible for selling,delivering,and optimizing digital ad marketing campaigns.The trade group field

107、s critical research on interactive advertising,while also educating brands,agencies,and the wider business community on the importance of digital marketing.In affiliation with the IAB Tech Lab,IAB develops technical standards and solutions.IAB is committed to professional development and elevating t

108、he knowledge,skills,expertise,and diversity of the workforce across the industry.Through the work of its public policy office in Washington,D.C.,the trade association advocates for its members and promotes the value of the interactive advertising industry to legislators and policymakers.Founded in 1

109、996,IAB is headquartered in New York City.IABs Measurement,Addressability&Data(MAD)Center Board of Directors aims to provide essential industry guidance and education on solutions and changes in underlying technology and privacy regulations.The MAD Center specializes in measurement and attribution,a

110、ddressability,advances in retail media,and privacy concerns,providing a comprehensive approach to digital media challenges.Board members set the agenda and direction for IAB and the industry,approve and prioritize key initiatives,influence industry best practices,receive priority access to IAB exper

111、ts,research,and tools,and participate in exclusive events and meetings.About IABAbout IABs Measurement,Addressability&Data Center14IAB MAD Center Board Member CompaniesAcxiomAmazon AdsAudigentBayerBeacon Media GroupButler/TillCanvas WorldwidedentsuDotdash MeredithDoubleVerifyGlassViewGoogleHavas MediaHorizon MediaInfillionIntegral Ad ScienceLiveIntentMars United CommerceMetaNielsenNomologyPinterestPublicis MediaQuigley SimpsonReal ChemistryRoundelSpectrum ScienceThe Trade DeskTikTokTransUnionUSIMVisit OrlandoYahoo