FAQ on generative AI: How consumer adoption is steering marketing in 2026 – eMarketer

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Generative AI has moved from experimental technology to mainstream business tool. In the US alone, 133 million people will use generative AI in 2026, according to EMARKETER. For marketers, the technology touches every stage of the workflow: Audience targeting, creative production, measurement, and search optimization. This FAQ covers how consumers and marketers are adapting to generative AI, the risks that accompany its growth, and what strategies brands should prioritize in 2026.
Generative AI refers to artificial intelligence systems that create new content (text, images, video, code, and audio) from patterns learned during training on large datasets. Unlike traditional AI built for classification or prediction, generative AI produces original outputs in response to user prompts.
The technology powers consumer tools like OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude, along with creative platforms such as Adobe Firefly, Midjourney, and Runway. ChatGPT alone draws more than 900 million weekly users, per The Information as cited by EMARKETER. For marketers, generative AI applies across the workflow: Audience segmentation, ad creative, content production, measurement, and search optimization.
EMARKETER estimates 121.1 million people in the US used generative AI in 2025, representing 35.8% of the population. That figure will grow 9.8% to 133.0 million in 2026, reaching 39.2% of the population, according to an EMARKETER forecast.
Adoption has accelerated since ChatGPT’s November 2022 launch. Consumer use now extends beyond text chatbots to image generators, AI-powered search tools, and voice assistants with generative capabilities. The 9.8% year-over-year growth indicates the market is transitioning from rapid early adoption to steady mainstream expansion, with nearly 2 in 5 Americans now using the technology regularly.
Some 79% of marketers plan to increase spending on genAI creator content in 2026, up from 70% in 2023, per the Influencer Marketing Factory as cited by EMARKETER. The technology is embedded across core marketing functions:
Consumer sentiment is trending positive but comes with clear reservations. Some 68% of consumers view generative AI favorably, up from 62% in 2024. Marketers are even more bullish, with 75% holding a positive view, up from 68% the prior year, per Kantar’s Media Reactions 2025 report as cited by EMARKETER.
Those gains come with caveats:
The pattern suggests growing acceptance of the technology alongside persistent skepticism about how brands deploy it.
Some 60% of US ad industry professionals cite accuracy and transparency concerns as a top barrier to AI adoption in media campaigns, according to IAB data cited by EMARKETER. The risks fall into several categories:
Governance gaps. Only 37% of marketers include AI governance clauses in vendor contracts, per the IAB State of Data 2026 report as cited by EMARKETER. This leaves most organizations without formal safeguards for AI-related vendor relationships.
Generative AI is creating a new discovery layer separate from traditional search. Only 8% of ChatGPT citations come from Google’s top 10 search results, and just 8.6% of Gemini citations do, per Ahrefs data as cited by EMARKETER. Perplexity draws more heavily from search, with 28.6% of citations from first-page Google links.
The sources AI chatbots favor differ from traditional search rankings. Reddit accounts for 40.1% of all generative AI citations worldwide, followed by Wikipedia at 26.3% and YouTube at 23.5%, per Semrush data as cited by EMARKETER. AI currently represents 3.3% of total digital discovery time. This shift has created a new discipline called generative engine optimization (GEO), focused on making brand content citable by AI systems.
Generative AI creates content from user prompts: Text, images, video, and code. Agentic AI goes further by executing multi-step workflows autonomously, making decisions without constant human input. While generative AI responds to a single request, agentic AI chains together tasks to achieve a broader goal.
In advertising, generative AI handles discrete tasks like writing ad copy or generating image variants. Agentic AI will automate end-to-end campaign workflows, from audience identification through bidding to performance reporting, according to EMARKETER. Performance reporting and customer journey operations rank among the most common agentic AI applications for marketers, per Coleman Parkes Research and SAS as cited by EMARKETER. New protocols such as the Advertising Context Protocol (AdCP) are emerging to standardize how AI agents interact across ad systems.
The advertising industry has shifted “from fear to fluency” with generative AI in creative workflows, according to EMARKETER. Major brands and agencies are integrating the technology into production pipelines:
Generative AI also enables auto-generated ad variants linked to real-time performance signals, per EMARKETER, a capability manual production cannot match at scale.
Some 75% of buy-side leaders say marketing measurement currently underperforms expectations, per the IAB State of Data 2026 report as cited by EMARKETER. AI is positioned to close that gap. The IAB projects AI will unlock $26.3 billion in media investment by improving targeting, measurement, and optimization.
Three priorities should anchor a 2026 generative AI strategy:
 
We prepared this article with the assistance of generative AI tools and stand behind its accuracy, quality, and originality.
EMARKETER forecast data was current at publication and may have changed. EMARKETER clients have access to up-to-date forecast data. To explore EMARKETER solutions, click here.
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