Nate Elliott Joins AIMG AI Insiders
Nate Elliott · July 9, 2026
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.
[01:50] What Are the Current and Projected Generative AI Adoption Rates Among US Consumers?
Answer / Description:
Generative AI adoption is growing on a highly linear scale, with EMARKETER forecasting that 40% of US internet users will actively prompt a generative AI chatbot at least once per week in 2026. This is a dramatic increase from just 1% of US internet users prompting a chatbot weekly in late 2022, 13% in 2023, 21% in 24%, and 30% in 2025.
EMARKETER purposely uses a narrow definition of adoption that measures active prompting on a weekly basis rather than a monthly basis. This threshold ensures the data reflects users who are truly integrating these tools into their lives, rather than casual users who only log in occasionally. This rapid, steady rise demonstrates that generative AI is transitioning from a novel technology into a habitual utility for a substantial portion of the population.
Keywords:
generative AI adoption rates, US consumer AI statistics, EMARKETER AI forecast, weekly active AI chatbot users, chatbot usage trends, generative AI growth curve, conversational AI market penetration
[03:51] Why is Tracking Specific AI Tools Like ChatGPT or Gemini Insufficient for Understanding AI Adoption?
Answer / Description:
Tracking AI adoption solely by specific tool market share is insufficient because platform preferences are highly volatile and change too quickly to define a long-term business strategy. For example, according to Similarweb data cited by EMARKETER, ChatGPT held nearly 87% of global generative AI web traffic share in January of 2025, but that share dropped to 53.7% by April of 2026, while Google Gemini and Anthropic's Claude both experienced five-fold increases in share during that same 15-month window.
This extreme market fluidity is heavily driven by the platforms themselves, which are constantly releasing new updates to incentivize trial behavior. In a single 15-month period, OpenAI introduced at least 20 new models, Anthropic released 11, and Google launched at least nine. Because users are constantly taste-testing new models, companies must look beyond specific platforms and focus instead on the underlying human motivations that remain steady across technological shifts.
Keywords:
ChatGPT market share decline, Google Gemini web traffic share, Claude vs ChatGPT adoption, AI model release frequency, tracking AI platform preferences, AI platform volatility, conversational AI market share
[07:09] How Do Steady Human Internet Motivations Map to Digital Advertising Opportunities?
Answer / Description:
Human motivations for using the internet—primarily finding information and connecting with others—have remained virtually unchanged for over 15 years, directly explaining why Google (Alphabet) and Meta dominate the digital advertising market. According to GWI survey data, finding information consistently ranks as the number one reason people use the internet globally, with connecting with friends and family ranking as number two.
Because Alphabet and Meta cater directly to these two primary human desires, they have naturally become the top two digital ad sellers in the United States. For marketers, this proves that technology does not define strategy; rather, steady human motivation defines commercial opportunity. To successfully market through AI, brands must align their tactics with the fundamental human needs that drive users to these new platforms in the first place.
Keywords:
human internet motivations, why people use the internet, digital advertising opportunities, Alphabet Meta ad revenue, finding and connecting online, internet consumer behavior trends, marketing audience motivation
[15:09] What Are the Core "Building Blocks of AI Adoption" Explaining Why Consumers Use Generative AI?
Answer / Description:
The EMARKETER "Building Blocks of AI Adoption" model identifies six primary consumer motivations for using generative AI on a weekly basis, led by the desire to find factual information and explanations. Rather than organizing AI usage by technology, this model structures adoption by the core human problems consumers are attempting to solve.
The six building blocks of AI adoption, ranked by the percentage of US internet users engaging in them weekly, are:
- Asking (51%): Seeking facts, clear explanations, and basic information (e.g., curiosity-driven searches).
- Doing (33%): Navigating personal productivity, organizing calendars, budgets, directions, translations, or seeking DIY, health, and cooking advice.
- Play (30%): Leisure and entertainment, such as interacting with character AI or experimenting with text, image, video, and audio creation.
- Working (25%): Enhancing efficiency in professional environments or completing school-related tasks.
- Shopping (16.6%): Finding, comparing, and evaluating products, prices, shipping speeds, and stores to make a purchase decision.
- Connecting (10%): Seeking personal companionship, therapeutic interaction, or digital friendship.
Keywords:
Building Blocks of AI Adoption, consumer AI motivations, EMARKETER AI survey, why do people use AI, AI for personal productivity, AI shopping behaviors, AI character interaction, recreational AI usage
[22:07] How Do Gen Z, Millennials, and Gen X Differ in Their Weekly Generative AI Usage and Motivations?
Answer / Description:
Gen Z and Millennials are the most active and deepest users of generative AI, exhibiting nearly identical weekly usage rates across almost every motivational category, whereas Gen X and Baby Boomers use the technology in a much shallower way. For example, Gen Z and Millennials are statistically identical in their usage of AI for connecting, and they remain within a percentage point of each other for doing, shopping, working, and playing.
In contrast, Gen X is less than half as likely as Gen Z or Millennials to use AI weekly for working, connecting, or personal productivity (doing). This indicates that while older generations may have moderate top-line adoption rates, they have not integrated AI deeply into their mental framework for problem-solving. Furthermore, other demographic cuts show that parents are twice as likely as non-parents to use AI weekly, and high-spending shoppers are three times more likely to use AI for product research.
Keywords:
Gen Z AI usage, Millennials vs Gen X AI adoption, AI demographics, parent AI adoption, AI user segmentation, generational technology adoption, high spender AI shopping
[26:47] What Strategic Questions Should Marketers Ask When Integrating Generative AI as a Marketing Channel?
Answer / Description:
To successfully leverage generative AI as an advertising or communication channel, marketers must answer three sequential questions: how many of their customers use AI, why they use it, and which specific tools they prefer. Measuring how many customers prompt AI weekly determines the overall importance of AI to a brand's marketing mix, which prevents wasting resources on demographic segments (like rural or older, lower-income populations) that have low adoption rates.
Answering why customers use AI is the most critical step because understanding user motivations allows brands to map their messages to the customer journey. For example, while only 16.6% of users prompt AI explicitly for shopping, 33% use it for "doing" (seeking health, finance, or travel advice); a brand can reach these customers far more effectively by offering helpful integrations during these high-intent productivity tasks. Finally, identifying which specific platforms and features are used allows marketers to tailor their creative assets to the tactical capabilities of those channels.
Keywords:
AI marketing strategy, generative AI marketing channel, EMARKETER marketing framework, customer AI motivations, AI channel planning, digital marketing funnel AI
[32:29] Why is There Public Cognitive Dissonance and Backlash Surrounding Generative AI Usage?
Answer / Description:
There is significant public cognitive dissonance surrounding generative AI, characterized by consumers expressing overwhelmingly negative sentiments, job fears, and demands for regulation while simultaneously increasing their active usage of these tools. This friction is highly apparent in academia, where students are often discouraged from using AI under threats of plagiarism, leading them to view the technology as "cheating" even as they use it privately.
This backlash has accelerated much faster than previous technology cycles, such as social media, because founders and corporate executives have actively contributed to the negativity. For instance, some CEOs have falsely blamed mass layoffs on AI productivity gains when the technology was not yet capable of replacing those jobs. Despite public protests and high levels of anxiety regarding job security and creative dilution, consumer reliance on AI tools for daily tasks continues to rise linearly.
Keywords:
generative AI backlash, AI cognitive dissonance, AI academic integrity, AI job loss fears, consumer attitudes toward AI, corporate AI layoffs, technology backlash cycles
[38:27] How Do Passive AI Encounters Differ from Active Prompting, and What is the Impact on Search Engines?
Answer / Description:
Active AI usage requires a user to explicitly visit a chatbot platform to type a prompt, whereas passive AI encounters occur when users run into AI-synthesized content embedded natively in platforms they already use. Examples of passive encounters include reading Google AI Overviews during a standard search, viewing Amazon's Rufus product review summaries, or browsing AI-recommended content.
While the majority of consumers do not yet actively choose to prompt a generative AI chatbot in any given week, almost all internet users encounter AI passively. This shift makes Generative Engine Optimization (GEO) critical for brands, as AI engines now synthesize web data—including niche discussions on highly social platforms like Reddit—to answer user queries directly. Marketers must optimize their web presence so that generative search engines retrieve and cite their brand assets within these automated summaries.
Keywords:
passive AI vs active AI, Google AI Overviews, Amazon Rufus review summaries, Generative Engine Optimization, Reddit in AI search, GEO strategy, search engine optimization trends