"AI in elections" refers to the use of generative or algorithmic AI systems to influence electoral outcomes, voter behavior, or democratic discourse. By 2026, generative AI is a standing feature of political communication in major democracies, and the policy response is fragmented across multiple regulators with no comprehensive US federal statute. Lines of authority are split among the Federal Election Commission (paid political advertising), the Federal Communications Commission (broadcast and robocalls), state election laws (deepfake-in-campaign statutes), private platform rules (Meta, Google, TikTok), and the EU Digital Services Act.
Scope
The category covers several distinct uses of AI in the electoral context:
- Synthetic political media — AI-generated audio, video, or images depicting candidates or events.
- Generative content at scale — AI-produced social-media posts, emails, ads, or comments.
- AI-enabled microtargeting — algorithmic audience segmentation and message customization.
- Robocall and voice-clone scams — AI-synthesized voices impersonating candidates or officials.
- Election integrity systems — AI tools deployed by platforms or governments to detect disinformation, identify coordinated inauthentic behavior, or manage content moderation.
- AI-driven voter interaction — chatbots answering election-related queries.
Structural dimensions
Three distinctions in existing law and platform practice shape how AI in elections is governed.
The first is paid versus organic speech. US election law distinguishes paid political advertising (the FEC regulates disclosure; platforms apply ad policies) from organic content (largely unregulated). AI narrows this distinction, because organic content generated cheaply at scale can carry the strategic weight of a paid campaign, and existing frameworks largely do not reach organic AI content.
The second is platform versus state. Private platforms (Meta, Google/YouTube, TikTok, X) maintain their own political-content and AI-content rules, often more restrictive than any applicable law. In the US, the effective regulator of AI political content is therefore private, an arrangement that allows rules to change faster than statutes but also allows them to be withdrawn, as Meta's 2024 retreat from election-integrity infrastructure illustrated.
The third is domestic versus foreign-origin. Detection and attribution of AI-generated political content is difficult. The Russia/China/Iran disinformation frame still applies, but AI tooling erodes the cues, such as translation errors and image inconsistencies, that human reviewers historically relied on.
Documented incidents
Biden New Hampshire robocall (January 2024)
An AI-synthesized voice impersonating President Biden made robocalls to New Hampshire voters before the state's 2024 primary, instructing Democrats to "save your vote" for November rather than vote in the primary. The consultant responsible, Steve Kramer, working with a Democratic challenger campaign, was later indicted. The FCC imposed fines and, in a February 2024 ruling, declared AI-voice robocalls illegal under the Telephone Consumer Protection Act (TCPA). The incident is the most-cited case of voice-clone disinformation in US elections and directly drove FCC rulemaking. Voice cloning is the primary technical mechanism behind documented election-interference incidents, including this robocall and the Slovak Šimečka audio (AI Voice Cloning).
California local election influence attempt (June 2026)
On July 13, 2026, California local election officials said AI was used in an attempt to influence a June 2026 election, as officials and researchers described AI as giving election conspiracy theories a new playbook heading into the 2026 midterms (Source: politico.com).
Systematic testing of chatbots and generators
The first systematic published test of how consumer AI systems handle election disinformation is the Brennan Center for Justice expert brief "Does AI Fight or Fuel Election Disinformation?", published August 11, 2026 by Abdiaziz Ahmed, Alex Brunet, Mark Krass, Lawrence Norden, Marcelo Agudo, Owen Doyle and David Evan Harris, based on tests run between February and August 2026 (Source: brennancenter.org; techpolicy.press).
On the question of whether chatbots repeat conspiracy theories, the finding is uniformly negative: every one of the six systems tested — ChatGPT, Gemini, Grok, Claude, Perplexity and DeepSeek — disputed every election conspiracy theory put to it, including under repeated questioning from users posing as sympathetic to those theories. The accuracy findings are weaker. Half of all responses contained an inaccuracy or a bad citation, one in three contained a factual error, and one in three contained broken links or misleading citations.
On generation rather than answering, the results diverge by system. Asked to draft a full set of image-generation prompts for fabricated election claims, most chatbots refused; Grok produced the complete set, with its chain of thought recording that "election misinformation not listed as disallowed activity." Safeguards also applied inconsistently across tiers of the same product: Meta AI's versions returned contradicting acceptances and denials to the same prompt 67 percent of the time, ChatGPT 28 percent, Grok 22 percent and Gemini 10 percent, while Runway Gen-4 and Flux.2 never differed between versions because neither version rejected a single prompt.
On detection, asked to classify 14 AI-generated images, Gemini and Meta AI correctly identified most as synthetic while ChatGPT, Grok, Claude and Perplexity each identified four or fewer. Reruns after California's AI Transparency Act took effect on August 2, 2026 showed little improvement except for Gemini, which had switched to reading embedded provenance data — a result that ties detection performance to the provenance-metadata track rather than to image forensics.
AI as a campaign issue
Separate from AI's use in political communication is its emergence as a subject of it. Shira Ovide, Clara Ence Morse and Kevin Schaul published an analysis of candidate campaign websites on August 14, 2026 finding that more candidates in the 2026 US midterm races mention artificial intelligence or data centers than mention Israel or manufacturing (Source: washingtonpost.com). Only the article's opening was retrievable and the underlying counts were not, so the comparison is recorded as the authors state it without the supporting figures. The finding pairs AI with data centers as a single campaign topic, which is consistent with the local-siting disputes tracked on Data Center Siting / AI Power Politics rather than with the model-safety debate.
Regulatory response
FEC regulation of AI in political ads
The Federal Election Commission launched rulemaking on "AI deepfakes in political advertising" in 2023–2024 but declined to issue a rule in August 2024, on the grounds that existing anti-fraud provisions were sufficient and that it lacked authority to regulate AI content specifically. The result is that there is no federal paid-political-ad-specific AI rule. The FEC's position has been criticized as an abdication; defenders argue the Commission lacks statutory authority and First Amendment clearance.
FCC robocall rules
The FCC, which regulates telecommunications under the TCPA, acted after the Biden robocall. A February 2024 Declaratory Ruling held that AI-generated voices in robocalls constitute "artificial voice" under the TCPA, subjecting them to the statute's prior-express-consent requirement and opening the door to civil penalties. The FCC has subsequently proposed rules on AI disclosure in political robocalls and texts.
Election-security coordination (2026 cycle)
On July 13, 2026, Rep. Mike Lawler (R-NY) urged CISA to coordinate with the Federal Election Commission and the Justice Department on mitigating AI-enabled threats to the 2026 election cycle (Source: insideaipolicy.com).
Sen. Adam Schiff and Rep. Ro Khanna reintroduced the AI Ads Act on Monday, July 27, 2026 — a measure addressing the gap the FEC declined to fill in 2024. The available reporting names the sponsors and the reintroduction date but does not set out the bill's provisions or its number (Source: nextgov.com).
State deepfake political ad laws
By 2026, a majority of US states have enacted deepfake political ad statutes, typically requiring disclosure that synthetic media is AI-generated, often with a window (for example, 60 or 90 days before an election) during which undisclosed synthetic depictions of candidates are actionable. Texas, California, Washington, Minnesota, and Michigan have among the most developed regimes. The statutes vary on whether they require disclosure or prohibit use outright; whether they apply only to candidate campaigns or also to PACs and independent expenditures; whether they provide a private right of action (some do, most do not); and First Amendment vulnerability, with most statutes narrowly tailored to avoid constitutional challenge but a handful enjoined.
Platform election integrity policies
Major platforms adopted election-AI rules in 2023–2024, followed by partial retreat:
- OpenAI published election integrity principles in January 2024, barring use of its tools to build applications that discourage voting or misrepresent the voting process, and updated ChatGPT to direct election queries to CanIVote.org in the US.
- Anthropic published an election-integrity blog post in 2024, committing to Acceptable Use Policy enforcement against voter suppression, candidate impersonation, and disinformation production, and piloted the Prompt Shield election-query safeguard.
- Google restricted Gemini from answering most election-related queries in 2024, a move criticized as over-cautious but which reduced the error surface.
- Meta retrenched in 2024–2025, dissolving much of its election-integrity team and relaxing political-content rules; civil society has cataloged the retreat as a major regression.
- X (Twitter) under Musk rolled back most of the pre-2022 election integrity infrastructure.
EU Digital Services Act
The EU AI Act interacts here with the Digital Services Act (DSA), which predates it. The DSA requires very large online platforms (VLOPs) and search engines (VLOSEs) to conduct systemic-risk assessments covering electoral processes and civic discourse, to publish risk-mitigation measures, and to permit independent audit. The European Commission used DSA powers in 2024 to open formal proceedings against TikTok (over its handling of Romanian elections) and X (over content moderation and advertising transparency). As of 2026, the DSA is the most active regulatory instrument in AI-elections governance globally, outpacing US federal action.
Microtargeting
AI-driven audience segmentation allows political campaigns to produce and deliver custom messaging at scale. Empirical research (Kalla and Broockman 2018) suggests microtargeting's direct persuasion effects are modest, but AI reduces the marginal cost of message production toward zero, shifting the equilibrium even if per-message effects are small. The EU's Political Advertising Regulation, applicable from October 2025, restricts AI-powered microtargeting in political ads, requiring explicit consent for sensitive-data-based targeting, which is the most restrictive such measure currently in force.
Policy responses at a glance
| Domain | Instrument | Status |
|---|---|---|
| Paid political ads | FEC rule | Declined, 2024 |
| Robocalls | FCC TCPA ruling | Active, Feb 2024 |
| Deepfake disclosure | State statutes | Majority of states by 2026 |
| Platform rules | Private ToS + policy | Active but variable; Meta retreating |
| EU systemic risk | DSA Articles 34–35 | Active enforcement |
| EU microtargeting | Political Ads Regulation | In force Oct 2025 |
| International | No harmonized regime | — |
Debates and positions
Coverage of AI in elections has been split between accounts that emphasize direct manipulation through synthetic media and accounts that emphasize broader erosion of trust. Nathaniel Persily's essay "Misunderstanding AI's Democracy Problem" in The Digitalist Papers argues against deepfake-election panic, locating the more durable harm in trust erosion rather than direct persuasion, a framing connected to the liar's dividend concept. Taiwan's Information Integrity Alignment Assembly (March 2024) has been cited as a case study of a participatory approach to AI-elections governance (Taiwan Ministry of Digital Affairs (moda)).
Relationships
- instance-of: AI governance via sectoral regulation
- related: AI and Content Moderation — adjacent concept of AI-in-platform-governance
- related: AI and Authoritarianism — election-integrity concerns in authoritarian-leaning regimes
- related: AI and the First Amendment — constitutional constraints on deepfake statutes
- related: EU AI Act (Regulation 2024/1689) — AI Act intersects with DSA on elections
- related: Techno-Federalism: How Regulatory Fragmentation Shapes the U.S.-China AI Race — state-level fragmentation of deepfake regimes
- related: AI and Surveillance — microtargeting as surveillance infrastructure
- related: AI Compliance Industry / Regulatory Fragmentation — multi-regulator, multi-jurisdiction burden
- related: Liar's Dividend — primary election-democracy concept; trust erosion versus direct persuasion
- related: AI Content Provenance — embedded provenance data as the mechanism behind the one detection improvement measured after California SB 942 took effect
- related: The Digitalist Papers (Stanford, Volumes 1–2) — Persily's "Misunderstanding AI's Democracy Problem" essay critiques deepfake-election panic
- related: Taiwan Ministry of Digital Affairs (moda) — Taiwan Information Integrity Alignment Assembly (March 2024) as case study of participatory approach to AI-elections governance
- related: AI Voice Cloning — voice cloning is the primary technical mechanism behind the documented election-interference incidents (NH Biden robocall, Slovak Šimečka audio)