Is Using AI and Bots to Boost Streams a Crime?

Using AI, Automation, and Bots to Gain an Advantage: Where the Line Becomes Fraud

I spent years as a federal prosecutor assessing when aggressive business practices crossed the line into criminal fraud. Most cases did not turn on whether the tools were new or sophisticated. They turned on intent, misrepresentation, and harm. That framework is now being applied to AI, automation, and digital platforms, often exposing the tension between legacy legal doctrine and emerging technology.

The recent prosecution arising out of alleged large-scale manipulation of music streaming platforms illustrates the point. According to reporting in Rolling Stone, the government alleges that AI-generated tracks were paired with automated bot networks to fabricate billions of streams and generate millions of dollars in royalty payments. The focus of the case is not whether AI-generated music is legitimate. It is whether automated activity was intentionally disguised as real listener behavior in order to trigger payments that would not otherwise have been made.

From a prosecutorial perspective, that distinction matters. Federal fraud statutes have always been technology-agnostic. Wire fraud does not necessarily require a fake document or a spoken lie. It requires a scheme to deceive and the use of interstate wires to obtain money or property. If a system relies on engagement signals to allocate revenue, and those signals are knowingly falsified, prosecutors will view that as a classic fraud theory executed through modern means.

This approach is not confined to music. Courts and regulators have pursued similar theories in cases involving automated advertising fraud, fake reviews used to inflate product rankings, algorithmic ticket scalping, and market manipulation driven by automated trading strategies. The Department of Justice has charged defendants in cases involving bot-driven advertising schemes under traditional wire fraud theories. For example, in this case, DOJ charged three foreign nationals with orchestrating a hack to steal over one billion email addresses which were monetized through large-scale spam campaigns. Regulators have pursued similar theories in cases involving automated advertising fraud, fake reviews used to inflate product rankings, algorithmic ticket scalping, and market manipulation driven by automated trading strategies. The conduct varies. The legal question does not. Was the system intentionally fed false information, and did that deception cause someone else to part with money?

International enforcement trends reinforce this direction. In 2024, a Danish court convicted an individual for fraudulently profiting from artificial music streams, explicitly rejecting the argument that the conduct was merely a violation of platform rules. Similar enforcement theories have appeared in cases involving online advertising fraud and fake engagement. The Federal Trade Commission has brought actions involving fake reviews and deceptive online endorsements, emphasizing that fabricated engagement misleads consumers and distorts markets.

Where defendants still have real defenses

At the same time, not every use of automation that benefits a user is criminal, and prosecutors know that. Fraud cases rise and fall on proof of intent and deception, and those elements are harder to establish in digital ecosystems than headlines suggest.

First, intent is rarely as obvious as charging documents imply. Many creators and businesses use automation to distribute content, test systems, or amplify reach. If a defendant believed the activity was permitted, tolerated, or functionally indistinguishable from accepted industry practices, proving criminal intent becomes difficult.

Second, platform conduct matters. Digital platforms are not passive victims. They design systems that reward scale, velocity, and engagement, often while acknowledging that non-human activity exists within their ecosystems. A defense lawyer will argue that a platform that knowingly operates in that environment and benefits from inflated activity cannot easily claim it was deceived in the way fraud law requires.

Third, there is a meaningful distinction between contractual enforcement and criminal liability. Terms of service violations are ubiquitous online. Historically, those violations have been addressed through account termination, clawbacks, or civil litigation. Expanding criminal fraud statutes to cover conduct traditionally policed through contracts raises legitimate concerns about over-criminalization.

Fourth, causation and loss are not academic issues. In streaming, advertising, and algorithmic marketplaces, revenue is pooled, calculated, and distributed through complex formulas. Demonstrating that specific automated actions caused specific financial losses to identifiable victims is evidentiary work, not rhetoric. Defendants will press that point.

Finally, fair notice remains a live issue. AI-assisted creation and automated engagement tools have outpaced clear regulatory guidance. Applying decades-old statutes to novel behavior invites arguments that the law did not clearly prohibit the conduct at the time it occurred.

Victims Matter

None of this minimizes the harm that manipulation can cause. From the victim’s perspective, fabricated engagement is not a technicality. It distorts markets that depend on trust.

In music streaming, royalty pools are finite. Artificial streams dilute payouts to legitimate artists, particularly independents who rely on algorithmic discovery to reach listeners. In advertising and e-commerce, fake engagement forces businesses to pay for exposure that never reflected genuine consumer interest and misleads consumers about popularity and quality.

From an enforcement standpoint, these harms are precisely why fraud law exists. The statute is not designed to punish innovation. It is designed to protect economic systems from being undermined by deception, regardless of whether that deception is carried out with forged invoices or automated scripts.

Conclusion

This is not an abstract debate for technologists or lawyers. It is a practical issue for musicians, influencers, marketers, and anyone whose livelihood depends on digital metrics.

The current wave of cases does not criminalize AI, automation, or growth strategy. It applies familiar fraud principles to modern platforms that monetize attention at scale. Using technology to gain an advantage is not illegal. Using technology to fabricate the signals on which money changes hands can be.

For creators and strategists, the takeaway is straightforward. If a tactic depends on making a platform, advertiser, or audience believe something is happening that is not, it carries risk. That risk is no longer limited to account bans or clawbacks. In certain circumstances, it now includes civil liability and criminal exposure.

For those harmed by artificial engagement, enforcement is not about resisting innovation. It is about preserving trust in systems that distribute money, opportunity, and visibility based on perceived demand. Courts are unlikely to be persuaded that deception becomes acceptable simply because it is automated.

Anyone building an audience or a business online should understand where that line is being drawn. The law may be slow, but it is not confused about the difference between advantage and fraud when real money is involved.