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.
Bridging the Human-to-AI Identity Gap

Bridging the Human-to-AI Identity Gap

  • ARF COUNCIL REPORT
  • CROSS-PLATFORM MEASUREMENT COUNCIL

As generative search and agentic AI transform how consumers discover, evaluate and purchase products, traditional identity resolution and attribution systems are struggling to keep pace. This new paper by the Identity Resolution Working Group of the ARF Cross-Platform Measurement Council, introduces the concept of “Delegated Identity”—a framework designed to reconnect human intent with AI-driven actions in an increasingly AI-mediated marketplace. The report explores the emerging identity gap, evaluates industry readiness and outlines the challenges and opportunities facing marketers, identity providers and AI platforms.

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From AI Adoption to AI Accountability: What Comes Next for Advertisers

From AI Adoption to AI Accountability: What Comes Next for Advertisers

  • ARF; The Advertising Club of New York

Artificial intelligence is becoming deeply embedded in advertising and marketing, but adoption alone is no longer the story. In this guest article for The Advertising Club of New York, ARF Senior Director of Research & Insights Tracy Adams examines findings from the ARF's latest AI research, which reveals that while organizations are increasingly confident in AI-generated outputs, many are still developing the testing, governance and measurement practices needed to ensure those outputs deliver meaningful business value.

When AI Meets Representation: The Consumer Reality of Synthetic Diversity

When AI Meets Representation: The Consumer Reality of Synthetic Diversity

  • ARF; MSI

As brands increasingly use AI-generated people in advertising, a new MSI Working Paper explores how consumers respond when those synthetic models are used to increase racial representation. Across multiple experiments, the research finds that disclosure of AI-generated Black models can reduce brand evaluations by weakening perceptions of authenticity and commitment to diversity initiatives, while similar effects do not emerge for White models. The findings offer important guidance for marketers seeking to balance technological innovation with meaningful representation.

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Striking the Right Balance in AI-Personalized Advertising

Striking the Right Balance in AI-Personalized Advertising

  • JOURNAL OF ADVERTISING RESEARCH

Generative AI is opening new possibilities for hyper-personalized advertising, including the ability to create AI-generated faces that closely resemble individual consumers. But how similar is too similar? This Journal of Advertising Research study finds that while moderate facial resemblance can improve advertising effectiveness, excessive similarity may backfire. The research introduces a new framework for measuring facial similarity and identifies an optimal personalization threshold that maximizes purchase intentions while avoiding consumer discomfort and resistance.

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Beyond the Recommendation: How Prompt Language Changes How AI Frames Your Brand

Beyond the Recommendation: How Prompt Language Changes How AI Frames Your Brand

  • Psychology of Gen AI
  • ARF; MSI

Generative AI tools are not just recommending products—they are shaping how consumers perceive them. This latest issue in the Psychology of Gen AI series, the third phase of the seventh study on AI product recommendations, examines how small changes in prompt wording alter the explanations AI systems generate around the same brand. Using ChatGPT descriptions of Arm & Hammer Advance White toothpaste across multiple, shopping-related prompts, the study reveals how AI recommendations construct different product narratives, emphasize different benefits and even introduce different caveats depending on the consumer’s wording of their question.

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Attention in Context: What Real Campaigns Reveal About Media Performance

Attention in Context: What Real Campaigns Reveal About Media Performance

  • ARF Attention Measurement Validation Initiative

What does “attention” really mean in today’s fragmented media landscape—and does more attention actually drive better results? In phase three of the ARF Attention Measurement Validation Initiative, real-world campaign data reveals where attention metrics align, where they diverge and how they relate to brand lift. The findings challenge assumptions and offer a more nuanced view of how attention works across channels, platforms and outcomes.

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Finding Your Brand’s AI Niche: How Prompt Nuance Shapes Product Recommendations

Finding Your Brand’s AI Niche: How Prompt Nuance Shapes Product Recommendations

  • Psychology of Gen AI
  • ARF; MSI

As generative AI becomes a key part of how consumers discover and evaluate products, a new question emerges for marketers: how can they ensure their brands show up in AI-driven recommendations? This ARF and MSI experiment, the second phase of the seventh study in the Psychology of Gen AI series, reveals that even small changes in prompt wording can significantly influence which brands appear—helping non-market dominant brands carve out visibility by aligning with specific product attributes rather than competing broadly for “best” status.

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Better Creative, Fewer Tests: A New Framework for Efficient Self-Improving Systems

Better Creative, Fewer Tests: A New Framework for Efficient Self-Improving Systems

  • ARF; MSI

This MSI working paper introduces TextBO, a novel AI framework designed to improve marketing decisions more efficiently by minimizing costly evaluation cycles. By combining large language models with Bayesian optimization principles, the approach enables AI systems to iteratively refine outputs—such as ad creatives—while requiring fewer real-world tests. The result: faster learning, better-performing outcomes, and a more scalable path to AI-driven decision-making.

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How Deepfake Ads Shape Consumer Response

How Deepfake Ads Shape Consumer Response

  • ARF
  • JOURNAL OF ADVERTISING RESEARCH

New research reveals that virtual influencers, despite their growing popularity and flexibility, are less effective than human influencers in driving engagement and brand outcomes. The reason lies in consumer psychology: people perceive virtual influencers as less deserving of success, which reduces feelings of envy—an emotion that typically drives social media engagement. However, this disadvantage can be mitigated when virtual influencers are paired with futuristic, technology-focused brands, where their artificial nature feels more congruent.

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What AI Recommends—and Why: Inside the Logic of “Best” Product Choices

What AI Recommends—and Why: Inside the Logic of “Best” Product Choices

  • Psychology of Gen AI
  • ARF; MSI

As generative AI tools increasingly shape how consumers search, shop, compare and evaluate products, understanding how they make recommendations has become critical for marketers. This seventh experiment in our ongoing Psychology of Gen AI series, is the first phase in a study that examines how large language models (LLMs), like ChatGPT and Claude, determine what qualifies as the “best” product—and reveals that their recommendations are far from neutral. Instead, they tend to rely on narrow, repetitive sets of familiar brands and structured response patterns that may reinforce existing market leaders. The findings highlight important implications for brand visibility, competitive dynamics and how marketers should position their products in AI-driven environments.

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