How AI Is Used in Covert Influence Operations

 ARTIFICIAL INTELLIGENCE · CYBERSECURITY & DIGITAL TRUST

How AI Is Being Used to Spread Political Influence: What OpenAI's Latest Report Reveals

How AI-generated content can support covert influence campaigns—and what readers, publishers, and platforms can do to protect trust online.

Published: October 12, 2026 · Topic: AI, misinformation, online influence and digital safety

Artificial intelligence has made it easier to write articles, translate messages, summarize information, and create content for different audiences. These capabilities can help journalists, researchers, and businesses work more efficiently. But the same tools can also be misused to make coordinated political influence campaigns easier to operate.

On October 8, 2026, OpenAI published a report describing two covert influence operations linked to Russia and Iran. According to the company, the operators used ChatGPT alongside traditional techniques to create content, support deceptive organizations, and promote geopolitical narratives without being transparent about who was behind them. OpenAI said it banned the associated account clusters.

The report raises a question that goes beyond one AI company: What happens when artificial intelligence makes it easier to manufacture the appearance of independent public opinion?

To understand the risk, it is important to examine what the operations reportedly did, where AI fitted into their activities, and what readers, publishers, and social platforms can learn from the findings.

What Are Covert Influence Operations?

A covert influence operation is an organized attempt to shape public opinion or political outcomes while concealing the real identity, intentions, or sponsorship of the people behind it.

Unlike an openly published political opinion, a covert campaign may disguise its source. It can use apparently independent commentators, fabricated experts, misleading organizations, or coordinated online accounts to make a particular message appear more widely accepted than it really is.

These operations existed long before generative AI. What has changed is the range of tasks AI can help people perform.

A small team can use AI to draft and revise articles, translate messages, generate social-media comments, and prepare internal reports. Human operators can then distribute the material through websites, social platforms, and other channels.

The technology does not need to invent an entirely new method of manipulation to make a difference. It can make parts of an existing operation easier to carry out.

The Two Operations Described by OpenAI

OpenAI gave the two campaigns the names Dark Clark and Bogus Bylines. Although both reportedly used AI to support influence activities, their methods were different.

1. Russia-linked operation: Dark Clark

OpenAI said it banned a cluster of accounts originating in Russia that used ChatGPT for activities targeting countries across Latin America. Much of the activity appeared intended to undermine Ukraine's reputation in the region, while some appeared connected to local political outcomes, particularly in Argentina and Bolivia.

The operators promoted a self-described research organization called the Social Research Center. They also used ChatGPT to prepare internal reports and create material associated with the campaign, including fabricated leaked documents and audio scripts. OpenAI said some of this material had circulated online.

2. Iran-linked operation: Bogus Bylines

OpenAI described a separate operation that used seven purported journalist identities to pitch long-form articles to online publications. Operators prompted ChatGPT in Persian and generated material in Persian and English, with much of the content focused on the conflict involving the United States and Iran.

The operation also generated batches of social-media comments. OpenAI identified almost 100 articles published or syndicated under the campaign's bylines across roughly a dozen online outlets worldwide.

These were separate operations, not one coordinated campaign jointly run by Russia and Iran. The distinction matters because their methods, target audiences, and reported impact differed.

How AI Helped the Campaigns Operate

The report describes AI as one tool within a larger workflow involving people, online platforms, websites, and conventional publishing methods.

1. Producing content in multiple languages

Writing a convincing article requires more than generating sentences. It may involve research, editing, translation, headline creation, and adapting the message to a particular audience.

AI can assist with these tasks. Operators can request drafts in different languages, revise the tone, or generate multiple versions of a message.

That can reduce the time needed to prepare content. It does not guarantee that the information is accurate, persuasive, or widely read.

2. Making coordinated comments look like ordinary discussion

OpenAI reported that the Iran-linked operation generated batches of comments responding to political and geopolitical posts. Some comments were published close together, while others were not found in public searches.

The company also described comments that appeared to praise or promote articles associated with the campaign.

This illustrates a particular risk: online readers often use comments and reactions as informal signals of public opinion. If coordinated activity creates the appearance of widespread agreement, people may misjudge how many independent individuals genuinely support a position.

However, the report does not establish that the campaigns successfully persuaded large numbers of people. Generating comments and changing public opinion are two different outcomes.

3. Building the appearance of independent authority

An article may look more credible when it appears on a recognizable publication or is attributed to someone presented as a journalist or expert.

The Iran-linked operation reportedly used multiple bylines to pitch articles to online outlets. The Russia-linked operation reportedly built a research organization with a public-facing presence.

These methods illustrate why the identity and independence of a source matter. A professional-looking website or a polished article is not, by itself, evidence that the people behind it are trustworthy.

4. Preparing internal reports

OpenAI said both operations used its models to prepare internal reports, with the Russia-linked campaign relying on this activity particularly heavily. Some reports contained misleading claims about the operators' own effectiveness or about work they could plausibly claim credit for.

This is an important detail. AI misuse is not limited to content published for the public. AI-generated reports can also be used internally to organize activities, summarize progress, or create an exaggerated impression of success.

A report produced with AI is not automatically reliable simply because it is structured and professionally written.

Did These Campaigns Actually Influence Public Opinion?

This is one of the most important questions—and one that requires careful wording.

OpenAI identified real content associated with the operations, including articles and some social-media activity. It also described evidence of material appearing across multiple platforms. But evidence that content was published does not establish that it changed people's beliefs or behavior.

The company noted limitations in assessing the true impact of the campaigns. Some operator-generated reports overstated their effectiveness, and engagement figures could be misleading.

It helps to distinguish four different stages:

Content created: An article, comment, or document has been generated.

Content distributed: The material appears on a website or social platform.

Content reaches people: Real readers encounter, view, or engage with the material.

Beliefs or behavior change: Evidence is needed to show that the campaign actually influenced people.

Each stage requires different evidence. A large number of generated comments does not prove that many people read them, and high view counts do not necessarily prove that anyone was persuaded.

This distinction is essential when evaluating claims about AI-driven propaganda.

Why This Matters for News Websites and Publishers

The report has implications beyond political campaigns. It raises questions about how online publications verify contributors, evaluate submissions, and protect readers from deceptive sourcing.

Consider a hypothetical local publication that receives a well-written opinion article from a contributor with an impressive biography. The article contains plausible arguments and appears relevant to a current event.

If the publication checks only the writing quality and topic, it may overlook a more important question: is the contributor who they claim to be, and is there a hidden organization behind the submission?

The lesson is not that AI-written content should automatically be rejected. AI can be a legitimate writing and research assistant. The concern is deceptive authorship, undisclosed coordination, and misleading claims about where information comes from.

Publishers can reduce these risks by:

Verifying the identity and relevant background of contributors.

Checking factual claims against independent, reliable sources.

Investigating suspicious submission patterns or repeated bylines.

Applying consistent disclosure and editorial standards.

Reviewing unusual spikes in engagement or coordinated commenting.

Keeping records of editorial decisions and corrections.

For smaller publications, these measures may be particularly important because they may have fewer resources for extensive verification.

How Readers Can Recognize Possible Influence Campaigns

There is no single sign that proves an article or social-media account is part of a covert operation. A real person can post frequently, a genuine journalist may use a pen name, and legitimate users can agree with one another.

The goal is to look for several signals together and verify them before drawing conclusions.

Check the author and publication

Does the author have a verifiable history of work? Does the publication explain its editorial standards and ownership? Search for the author's name and check whether independent sources support the biography.

Compare independent coverage

Look for reliable reporting from sources that are not simply repeating the same article. If a major claim appears in only one obscure source, treat it as unverified until stronger evidence emerges.

Look for coordination, not just volume

Many comments posted within a short period, repeated wording, or accounts that promote the same small group of sites may warrant closer examination. None of these signs alone proves deception.

Verify the evidence behind the claim

Look for original documents, named sources, direct statements, and context. A confident tone, a professional design, or an AI detector's score cannot establish that a claim is true.

A useful rule is simple: verify the source and evidence before sharing emotionally charged political content. Do not accuse an individual or organization of being part of an influence campaign based only on suspicious writing or an AI-detection tool.

What Can AI Companies Do About This?

OpenAI said it banned the account clusters associated with the two operations and shared information with relevant authorities or industry partners where appropriate. The company also publishes investigations into malicious uses of its services.

Account enforcement can interrupt activity on a particular service, but it cannot eliminate the broader problem. Operators may use other writing tools, different accounts, or conventional methods.

A more complete response involves several layers:

AI providers: Detect abusive patterns, enforce usage policies, investigate suspicious activity, and share relevant threat intelligence.

Social platforms: Identify coordinated inauthentic behavior and limit deceptive amplification.

Publishers: Verify contributors, sources, and factual claims.

Researchers and civil society: Study how campaigns spread and assess their actual impact.

Readers: Check evidence, compare sources, and avoid amplifying unverified claims.

AI can also help defenders analyze large volumes of content and identify patterns. The same technology that creates new risks can support detection and investigation, provided the systems are designed and used responsibly.

Does This Mean AI Itself Is the Problem?

Not necessarily.

The cases described by OpenAI illustrate the misuse of AI by people and organizations. They do not show that all AI-generated political content is deceptive, or that every person using AI to write an article has a hidden agenda.

Journalists can use AI to summarize documents. Researchers can use it to translate material. Independent publishers can use it to improve accessibility and editing. Those uses can be legitimate when the work is checked and the source is represented honestly.

The central distinction is between using AI to communicate information and using AI as part of a system designed to deceive people about who is speaking, what evidence supports a claim, or how much independent support a viewpoint has.

That distinction matters more than whether a sentence was written by a human or generated with a machine.

The Future of AI and Information Trust

Generative AI lowers the effort needed to produce polished text in multiple languages and formats. But trustworthy journalism and public discussion depend on much more than writing fluency. They depend on accurate evidence, transparent sourcing, genuine independence, and accountability for mistakes.

The October 8 report is a reminder that influence operations can combine new tools with familiar forms of deception. AI may help produce and organize content, but people still build the campaigns, choose the messages, and decide where to distribute them.

For readers, the answer is not to distrust everything online. It is to become more deliberate about what deserves trust. For publishers, it means strengthening editorial verification without treating every use of AI as misconduct. For AI companies, it means continuing to detect abuse while acknowledging that enforcement on one service cannot solve a problem that spans the wider internet.

In an age when convincing content can be produced quickly, credibility will depend less on how professional a message looks and more on whether its source, evidence, and purpose can withstand scrutiny.

The next time an article or social-media post strongly confirms what you already believe, pause for a moment. Who created it? What evidence supports it? And can an independent source verify the same claim?

Those questions remain powerful safeguards—even as the technology used to create information changes.

Sources and Further Reading

OpenAI — Primary source: Disrupting AI-enabled “false front” operations — October 8, 2026. The company's detailed account of the Russia-linked Dark Clark and Iran-linked Bogus Bylines operations.

OpenAI: Disrupting malicious uses of AI — A collection of investigations into the misuse of AI services.

The Washington Post: A Florida newspaper ran an op-ed that was part of an Iranian AI influence campaign — Independent reporting on one example of AI-generated material reaching a publication.

OpenAI: Disrupting a new covert influence campaign from Russia — A separate case study that provides additional context on how AI-generated content can support deceptive online organizations.