Political campaigns across the United States have entered a new digital era during the 2026 midterm elections. Generative artificial intelligence (AI) is no longer just an experimental technology. It is now being used as an active tool in political campaigns.From realistic fake audio recordings targeting candidates just hours before polling begins to automated tools that create and target AI-generated video ads, the technology is making it harder for voters to decide what information they can trust. Election monitors and political strategists are struggling to deal with an online environment where genuine campaign material is becoming increasingly difficult to separate from computer-generated content.Public concern about the impact of AI-generated media has reached high levels. A survey by the Bipartisan Policy Center found that 77 per cent of voters were deeply concerned about the use of artificial intelligence to spread false information or influence public opinion during this election cycle. The findings show that voters across the political spectrum share these concerns, with majorities from both major parties identifying deepfakes and automated persuasion as serious threats to fair elections.These concerns have also started changing campaign strategies. Axios reported last week that Democratic groups had launched a $4 million advertising campaign across four competitive House of Representatives districts. The campaign was designed to test whether voters support stricter rules for artificial intelligence.
Deepfakes blur the line between real and fake
One of the biggest changes in the 2026 midterms is how easily people can now create realistic fake content. In earlier election cycles, changing digital images or recordings required special technical skills and expensive computer systems. Today, widely available software allows campaign workers or outside groups to copy a politician’s voice or create convincing videos using simple written instructions.During the autumn campaign season, AI-generated content appeared in several closely contested races. Fake audio recordings designed to sound like candidates making controversial statements were shared through messaging apps. Some were released shortly before important debates, giving fact-checkers little time to check them before they spread further.Fake videos have also become part of negative political campaigns. Instead of using traditional edited footage, some AI-generated advertisements show completely fictional scenes. These videos may depict candidates taking part in unpopular activities or appearing alongside controversial public figures.The spread of such material has created more work for election officials and news organisations. Fact-checkers now have to spend time checking whether audio recordings and videos are genuine before examining the political claims they contain. This has slowed down political reporting and made it harder to respond quickly to misleading content.
Machine learning changes how campaigns target voters
Apart from creating public-facing fake content, political campaigns are also using machine-learning systems to improve how they reach voters. These tools analyse large amounts of information, including shopping habits, social media activity and past voting records. They can then create messages aimed at specific groups of people.Traditional political advertising usually targets broad groups based on factors such as age or location. AI tools can go much further by creating personalised messages for smaller groups and even individual voters. Algorithms can produce thousands of different versions of an advertisement in real time, changing the words, images and emotional tone to match what a particular voter is likely to respond to.This allows campaigns to test different messages and quickly identify which ones work best. Political teams can run hundreds of online advertisements at the same time and stop using ineffective versions within minutes. They can make these decisions by tracking how people respond to the advertisements.However, researchers warn that this type of automated targeting could increase political divisions. When different groups receive completely different political messages, voters may end up seeing very different versions of the same issue. This could create separate information bubbles and make it harder for people to understand opposing views.
Voters struggle to identify AI-generated content
The growing use of AI-generated material in political discussions has left many voters unsure about the information they see and hear. As fake videos become more realistic, signs that once exposed digital editing are becoming harder to spot. These included unusual lighting, strange eye movements and distorted background sounds.Election security experts warn that the growing gap between AI technology and tools designed to detect fake content has created another problem. It is known as the “liar’s dividend”. This happens when politicians or public figures can deny genuine but embarrassing recordings by falsely claiming that they were created using artificial intelligence.Research by the Bipartisan Policy Center shows that voter concerns go beyond the possibility of being fooled by realistic fake videos. People are also worried about the wider loss of trust in official information. When voters begin to believe that almost any recording could be fake, their confidence in genuine sources, including candidate speeches and official debates, can also fall.Major technology companies have introduced digital watermarks and automated systems to identify and label AI-generated content. However, these tools are not perfect. Altered videos and recordings can still spread on decentralised online platforms before detection systems identify them.
