Nate Elliott Joins AIMG AI Insiders
Nate Elliott · AI Marketers Guild · July 9, 2026
Nate Elliott Joins AIMG AI Insiders
How are consumers truly integrating generative AI into their daily routines? In this session, EMARKETER’s Nate Elliott presents research findings based on a comprehensive survey of 1,500 US consumers, illuminating how people use AI for search, shopping, trip planning, comparison, and wider decision-making.
The discussion goes beyond basic usage trends, examining the nuances of AI adoption and highlighting key challenges brands should consider, especially as trust, perceived usefulness, and questions of personal control play an increasingly pivotal role in how consumers interact with new technologies.
Key moments
[01:25] How Fast Is Generative AI Chatbot Adoption Growing Among US Internet Users?
Generative AI chatbot adoption among US internet users is experiencing rapid, near-linear growth, with EMARKETER forecasting that 40% of US internet users will actively prompt a generative AI chatbot at least once per week by 2026. This represents an enormous increase from just 1% of users in late 2022, 13% in 2023, 21% in 2024, and 30% in 2025.
Nate Elliott explains that EMARKETER purposefully utilizes a strict, narrow definition of adoption. This metric only counts active usage—defined as a user navigating to an LLM tool and inputting a prompt at least weekly—rather than passive exposure to AI-generated content. Elliott warns that if marketers focus only on massive, top-line adoption figures, they will miss critical details regarding who these users are and what specific problems they are attempting to solve.
[04:14] Why Does Generative AI Chatbot Market Share Shift So Rapidly?
Generative AI chatbot market share shifts rapidly because the continuous release of new models encourages constant consumer "taste-testing," preventing any single platform from securing permanent user loyalty. According to Similarweb web traffic data, ChatGPT's global market share plummeted from approximately 87% in January 2025 to 53.7% in April 2026, while competitors Gemini and Claude saw their shares grow more than fivefold during the same 15-month window.
Nate Elliott attributes this high volatility to the breakneck pace of model releases by major tech companies. Between January 2025 and April 2026, OpenAI introduced at least 20 new models, Anthropic released 11, and Google launched at least nine, excluding standard updates and refreshes. This constant stream of product upgrades makes tool-based tracking an unreliable metric on its own for defining long-term marketing strategies.
[07:09] Why Should Marketers Focus on Consumer Motivations Rather Than AI Technology Trends?
Marketers must focus on consumer motivations because core human needs remain highly stable over decades, whereas specific technologies and platform preferences change quickly. Data from GWI reveals that the top two reasons people use the internet—finding information and connecting with friends and family—have remained completely unchanged for over 15 years, proving that human intent is a much more reliable foundation for strategy than technology.
Nate Elliott cautions that executive mandates to "get us on ChatGPT" are no more strategically sound than historical demands to "get us on Facebook," "get us on the iPhone," or "get us on AOL" without a clear strategic goal. He notes that the top two digital ad sellers, Alphabet and Meta, dominate the industry because their core products (Google Search and Facebook/Instagram) directly satisfy the primary human desires to find information and connect with others.
[15:36] What Are the Six Core Motivations in the "Building Blocks of AI Adoption" Model?
The "Building Blocks of AI Adoption" is an analytical framework developed by EMARKETER that categorizes consumer AI usage into six distinct human motivations: Asking, Doing, Playing, Working, Shopping, and Connecting. Of these, "Asking" (seeking facts or explanations) is the most dominant behavior, with more than 51% of surveyed US internet users prompting an AI for this reason at least once a week.
The rest of the hierarchy includes:
- Doing (33.3% weekly usage): Seeking personal productivity help, such as health, travel, financial, or DIY advice, translation, and scheduling.
- Playing (30% weekly usage): Using AI for hobbies, entertainment, character interaction, and creative asset generation (text, image, audio, or video).
- Working (25% weekly usage): Utilizing AI to accomplish professional tasks or schoolwork.
- Shopping (16.6% weekly usage): Comparing product prices, shipping speeds, and specs to make purchase decisions.
- Connecting (10% weekly usage): Turning to AI as a companion, friend, or therapeutic outlet to combat isolation.
[22:07] How Do Generational and Demographic Differences Influence Consumer AI Usage?
Generational and demographic factors heavily influence the depth and frequency of AI usage, with Gen Z and Millennials leading in active, multi-use adoption, while older, rural, and lower-income cohorts show much shallower engagement. Notably, parents of children under 18 are twice as likely to use AI weekly, and high-spending online shoppers are three times more likely to use AI specifically for shopping compared to average users.
Nate Elliott details how Gen Z and Millennials exhibit nearly identical, deep behaviors across almost all AI motivations, despite Gen Z's vocal, public criticisms of AI. Conversely, while Gen X's overall adoption rate is close to that of younger generations, their usage is far shallower, meaning they are less than half as likely as Gen Z or Millennials to use AI for working, doing, or connecting. Additionally, wealth and urban geography show a direct positive correlation with active AI usage.
[26:47] What Strategic Framework Can Marketers Use to Integrate AI Into Their Campaigns?
Marketers can successfully integrate AI into their campaigns by answering three critical strategic questions in sequence: "How many of our customers use AI?", "Why do our customers use AI?", and "Which AI tools do our customers use?" Prioritizing the "Why" (customer motivation) over the specific technology allows brands to identify unique marketing and branding opportunities.
Nate Elliott explains that determining the percentage of your target audience that actively prompts AI tells you if AI is a viable marketing channel for that segment. Next, uncovering their specific motivations—such as using AI for "doing" (personal productivity) rather than "shopping"—helps brands position themselves as solutions during the consumer's research journey. Finally, understanding the specific tools and features your audience prefers guides the tactical implementation of the campaign.
[31:11] What Explains the Deep Cognitive Dissonance and Negative Public Sentiment Surrounding AI?
The cognitive dissonance surrounding AI stems from consumers heavily utilizing the technology while simultaneously holding strong negative attitudes about its impact on jobs, regulation, and personal creativity. Academic systems have also contributed to this friction by framing AI usage primarily as "cheating," which discourages students from leveraging these tools for productive, real-world workflows.
Nate Elliott notes that surveyed consumers overwhelmingly express negative feelings about AI, believing it does not improve productivity or creativity, and calling for stricter regulation. This negativity is amplified by corporate executives publicly and falsely blaming AI for mass layoffs. Despite this pushback, actual usage continues to rise, mirroring previous historical technological adoptions like social media, where public concern and actual daily engagement grew in tandem.
[36:32] Why Is Reddit Becoming a Vital Platform for Generative Engine Optimization (GEO)?
Reddit is becoming a critical platform for Generative Engine Optimization (GEO) because it serves as the most fundamentally social, community-driven space online where consumers discuss topics in their native, unvarnished environments. Large Language Models heavily scrape Reddit's niche communities for factual answers and authentic human opinions, prompting brands to target the platform more actively.
Historically, brands and agency analysts overlooked Reddit as a primary social media platform. However, in the AI and GEO era, Reddit’s highly categorized "subreddit" structure makes it incredibly valuable as a data source for AI search engines and answer engines. This shift has forced major consumer brands, such as Coca-Cola, to aggressively establish presences on Reddit to ensure their products are favorably represented within the data sets feeding AI retrieval models.
[38:51] How Do Geography and Income Disparities Limit Consumer AI Usage and Accessibility?
Geography and income levels create a distinct divide in active AI usage, with a straight-line decline in chatbot adoption as you move from wealthy urban areas to suburban and lower-income rural communities. In any given week, the vast majority of average US citizens do not actively choose to prompt AI chatbots, even though they routinely encounter passive AI integrations like Google's AI Overviews or Amazon's review summaries.
When asked if governments should intervene to bridge this digital divide—for instance, by teaching low-income citizens how to use AI to maximize SNAP benefits or navigate healthcare systems—Nate Elliott suggests this responsibility will likely fall on local digital literacy initiatives. Commercial AI platforms have little financial incentive to focus on low-income demographics, as these users are unlikely to pay premium monthly subscription fees or serve as lucrative targets for digital advertisers.