Future States & AI

Read the latest and most impactful research on future states and emerging technologies for innovating research methods here. All the research listed comes from the ARF or one of its subsidiaries: The Journal of Advertising Research (JAR), the Marketing Science Institute (MSI) or the Coalition for Innovative Media Measurement (CIMM). Feel free to bookmark this page, as it will be updated periodically.
How Generative AI Is Reshaping Discovery, Attention and Advertising Exposure

How Generative AI Is Reshaping Discovery, Attention and Advertising Exposure

  • ARF

Large language models (LLMs) are rapidly becoming a new gateway to online information, potentially disrupting traditional search engines, websites and advertising markets. Using detailed clickstream data from 2022–2023, this study examines how adopting LLM tools changes consumers’ online behavior. The authors find that LLM adoption gradually reduces traditional search activity and the browsing of smaller websites, while also lowering display advertising exposure. These results suggest that generative AI may reshape how users access information online and alter the distribution of attention and advertising revenue across digital platforms.

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Improving AI-Driven Marketing Content Using LLM-Generated Knowledge

Improving AI-Driven Marketing Content Using LLM-Generated Knowledge

  • ARF, MSI

As generative AI becomes a central tool for producing marketing content, firms increasingly rely on fine-tuning models using engagement data, such as A/B test results. This MSI working paper argues that optimizing only for “what works” risks reward hacking, clickbait and poor generalization. The authors propose a knowledge-guided alignment framework in which large language models (LLMs) generate and validate hypotheses about why content performs well, and then use this knowledge to guide fine-tuning. Using more than 23,000 A/B-tested news headlines, the study shows that knowledge-guided AI produces higher engagement, avoids clickbait and generalizes better—especially in low-data settings.

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When Language Becomes Targeting: How Gender Cues Shape AI Recommendations

When Language Becomes Targeting: How Gender Cues Shape AI Recommendations

  • ARF

As generative AI tools increasingly influence product discovery and decision-making, subtle cues in user language can shape what consumers are shown—and how options are framed. This research examines how implicit and explicit gender signals affect AI-generated product recommendations, revealing systematic differences in categories, brand repetition, descriptive language and price information. The findings raise important questions for advertisers and researchers about bias, brand visibility and the growing cultural role of AI in shaping consumer norms.

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When Style Becomes Signal: How Gendered Language Shapes Generative AI Output

When Style Becomes Signal: How Gendered Language Shapes Generative AI Output

  • ARF

As generative AI tools become embedded in advertising and marketing research workflows, questions about bias increasingly extend beyond outputs to the interaction itself. This study examines whether gendered patterns can enter AI through subtle differences in how prompts are phrased. By systematically varying linguistic styles using psychologically grounded traits, the research shows that implicit, style-based, gender cues shape AI prompt construction more strongly than explicit, gender labels, with important implications for how bias may propagate upstream in AI-assisted marketing and research applications.

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Privacy, Trust & AI: How U.S. Consumers Are Rewriting the Rules of Advertising

Privacy, Trust & AI: How U.S. Consumers Are Rewriting the Rules of Advertising

  • ARF Original Research

The ARF’s latest privacy study shows that U.S. consumers are more informed, more trusting and more engaged with artificial intelligence than ever before—yet still cautious about how it and other technologies use their data. Drawing on responses from more than 1,200 adults, the 2025 study reveals rising openness to data sharing when clear benefits exist, persistent skepticism toward certain targeting practices and growing expectations for transparency, especially around AI. For advertising researchers, the findings highlight a shifting privacy landscape where relevance, trust and first-party data strategies are increasingly intertwined.

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Why Synthetic Respondents Flatten Consumer Sentiment

Why Synthetic Respondents Flatten Consumer Sentiment

  • ARF; MSI; CIMM
  • Psychology of GenAI

A new ARF Psych of GenAI experiment reveals that large language models apply a rigid, rule-driven logic when evaluating privacy scenarios—even when humans typically shift their reasoning based on framing, emotion and social context. Unlike consumers, who blend intuition, feeling and social perspective into their judgments, GPT-4o relied on a single internal rule across all testing conditions: data use is acceptable only with explicit consent. This consistency offers value for certain analytic tasks but exposes limits for advertising research that depends on emotional nuance and context-sensitive consumer insight.

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When AI Takes the Survey: Evaluating LLMs as a New Tool for Consumer Insight

When AI Takes the Survey: Evaluating LLMs as a New Tool for Consumer Insight

  • ARF
  • MSI

The study in this MSI working paper evaluates whether large language models (LLMs) can serve as a reliable source of consumer preference data—potentially transforming how market research is conducted. Using conjoint-style survey questions, the researchers compared LLM-generated choices with human responses to estimate willingness-to-pay (WTP) for a variety of product attributes. They find that LLMs often approximate human preferences surprisingly well, especially when fine-tuned with prior survey data, though important limitations remain. For marketers, the research highlights both the promise and the boundaries of using AI-generated insights to accelerate testing, concept screening and early-stage innovation work

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Navigating the New Search Frontier: How AI Is Reshaping Discovery, Research and Shopping

Navigating the New Search Frontier: How AI Is Reshaping Discovery, Research and Shopping

  • ARF
  • Knowledge at Hand | CMO Brief

Artificial intelligence is rapidly changing how consumers discover, research and evaluate products, creating a hybrid search ecosystem where traditional engines like Google remain dominant while GenAI tools increasingly shape mid-funnel decision-making. Shoppers turn to AI for clarity, comparison and confidence, yet still validate information before purchase, altering the structure of the journey and the expectations placed on brands. As AI-driven search and shopping become more influential, the implications for marketers and retailers are profound, demanding new approaches to trust, data accuracy, discoverability and optimization for agent-driven environments. This Knowledge at Hand and CMO Brief reports show how AI is reorganizing the consumer path to purchase and what this means for the future of brand visibility and retail marketing. Non-members can access this content for a limited time after registering for a free account. Click on the  “Login to Access,” then “Create an Account.”

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Traversing Data Silos: A Practical Framework for Identity Crosswalks in Advertising

Traversing Data Silos: A Practical Framework for Identity Crosswalks in Advertising

  • ARF | Cross-Platform Council
  • ARF ORIGINAL RESEARCH

Advertisers rely on identity crosswalks as a critical tool for linking identifiers across data sets and platforms without exposing personal information. This white paper from the Identity Resolution Working Group of the Cross-Platform Measurement Council provides a brief practical introduction to crosswalks and how to implement them effectively. It outlines common operational models, covers use cases for brands, agencies and publishers, and addresses accuracy, privacy and match rate considerations. The guide offers advertising researchers and data practitioners clear, actionable steps for navigating the complex identity landscape.

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When AI Meets the Marketplace: How Generative Models Reshape Creative Supply and Demand

When AI Meets the Marketplace: How Generative Models Reshape Creative Supply and Demand

  • ARF
  • MSI

Generative AI is transforming creative marketplaces by rapidly expanding the supply of content while simultaneously displacing traditional producers. Using a unique natural experiment and econometric modeling, this research explores how AI technologies alter equilibrium in image marketplaces—where it boosts variety and quality but also creates challenges for non-AI producers and policymakers.

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