Will voters actually use AI chatbots for election information?
Explores how many voters plan to rely on AI chatbots versus traditional news sources for 2026 election information, and whether stated intent reflects actual behavior or real-world impact.
Change Research's survey of 1,892 respondents weighted to a registered-voter population, fielded May 5–10, 2026 and recruited through targeted digital ads and text-to-web SMS, asked Americans which sources they would use to learn about 2026 candidates. News articles led (68% very or somewhat likely), followed by friends, family, or colleagues (62%), candidate websites (57%), and social media (53%); 62% said they would rely on Google Search. Only 15% said they were likely to use an AI chatbot, and a majority (58%) said they were "very unlikely" to do so.
The survey's authors argue the headline number understates AI's reach in two ways: "even a small segment of active AI information-seekers is large enough to be decisive in close elections," and voters who search Google may see AI-generated summaries without seeking them out — passive exposure the survey cannot quantify. Chatbot-seeking is also unevenly distributed: voters under 35 are nearly three times as likely as those over 65 to say they'll consult a chatbot (21% vs. 8%), voters of color are likelier than white voters (21% vs. 12%), and men slightly outpace women (17% vs. 13%). On accuracy, 36% of all respondents say neither AI nor candidates are accurate sources, but trust tracks usage: 31% of under-35 voters and 37% of voters of color (nearly half of Black voters) rate AI-generated information as equally or more accurate than candidate-generated information.
This is self-reported intent to seek information, not a measured persuasion effect, which puts it in a different register from Can generative AI scale personality-targeted political persuasion?, which shows AI-personalized ads can move opinion at scale regardless of whether a voter sought them out, and from Can a simple warning reduce how much LLMs persuade people?, which measured actual belief change under experimental conditions rather than asking people what they plan to do.
The survey measures stated intent before the election, not November behavior, what chatbots actually tell voters who ask, or the accuracy of those answers; the online-recruited sample may also undercount voters without reliable digital access. The data support a narrower claim than "AI will decide the election": a demographically concentrated minority of self-identified chatbot users, layered on an unmeasured amount of passive exposure through AI search summaries, in a political landscape where effective AI persuasion has separately been shown to work at scale on receptive audiences.
Inquiring lines that read this note 8
This note is a source for these research framings, grouped by the broader line of inquiry each explores. Scan the bold lines of inquiry; follow any specific question forward.
How can AI systems reliably guide voters without introducing political bias?- Why do older voters show less willingness to consult AI for politics?
- How much does stated election information intent predict actual behavior?
- What accuracy do AI chatbots actually provide on election topics?
- Should election regulators require chatbots to refuse voting advice entirely?
- How often do chatbot news users actually return to original reporting?
- Do other AI assistants perform similarly on voter election questions?
- How many Dutch voters actually plan to use AI for voting advice?
- What makes voting-advice tools like Kieskompas more reliable than chatbots?
Related concepts in this collection 4
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Can generative AI scale personality-targeted political persuasion?
Does removing the human-writing bottleneck through generative AI make it feasible to target voters at scale based on individual psychological traits? This matters because it could reshape political microtargeting economics and capabilities.
contrasts self-reported low chatbot-seeking with AI's demonstrated capacity to persuade via targeted ads at scale
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Can a simple warning reduce how much LLMs persuade people?
This research explores whether telling people that language models can be prompted to persuade actually changes how they respond to persuasive AI conversation. Understanding user-side defenses against AI influence matters as these systems become more capable.
measures actual persuasion effects, where this note only reports self-reported intent and trust
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How many Dutch voters might seek AI voting advice?
Before the 2025 Dutch election, researchers surveyed willingness to consult AI chatbots for voting guidance. Understanding who considers this and how often matters for election integrity and information quality.
Evidence for: Dutch survey finds willingness also drops with age, corroborating the young-voter skew in US chatbot election-info use
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Why do young adults use chatbots most yet trust them least?
Pew's 2026 survey shows adults under 30 are the heaviest AI chatbot users but most pessimistic about its societal impact. Understanding this gap could reveal whether experience breeds skepticism or if other factors shape young adults' AI concerns.
Evidence for: Pew finds young adults use AI chatbots most overall, corroborating the age skew in election-chatbot usage
Related papers in this collection 8
Papers most semantically related to this note, ranked by cosine similarity in the embedding space.
- Who's Asking AI About the 2026 Election?
- Emerging uses of AI chatbots for news and what it means for journalism (Digital News Report 2026)
- AI and Elections: How Well Do AI Platforms Answer Voter Questions?
- Americans and AI 2026: Chatbots, smart devices and views on impact
- Digital News Report 2026
- How Teens Use and View AI
- Auditing Political Alignment in LLM Assistants: Engagement, Stance, and User Identity
- Dutch privacy watchdog warns against using AI chatbots for voting advice
Original note title
Change Research's survey finds 15% of voters plan to use an AI chatbot for 2026 election information — most likely among young voters and voters of color