In an age when deception is scaling faster than building trust, deepfakes are no longer simply a technological curiosity.
Generative AI has become more accessible, convincing fake video, audio and imagery can be created faster, more cheaply and with less technical expertise than ever before. In 2026, AI is not just driving productivity, it is industrialising brand abuse.
For brand leaders, the challenge goes beyond simply monitoring and removing counterfeits and fakes from marketplaces and websites. Boosted by AI tools, bad actors can launch multichannel, coordinated attacks in minutes. In this environment, what is real and what is fake becomes increasingly difficult to detect.
The risk is not simply that someone copies a logo or creates a counterfeit product listing. A bad actor can now create convincing content that appears to show a celebrity endorsing a product, an executive making a statement, or a trusted brand promoting an offer that isn’t genuine.
The result is a new kind of brand threat: content that looks authentic, sounds authentic and can be distributed at scale – but it isn’t.
What is deepfake?
Deepfakes are synthetic or manipulated audio, video or imagery created using artificial intelligence. The technology can be used to alter existing content or generate entirely new material that appears to depict a real person saying or doing something that never happened.
Computers study thousands of real pictures or voice clips of a person. Then, the AI uses those patterns to build a convincing copy that moves, speaks, or looks real. The technology itself is not inherently malicious. Like many generative AI tools, it has legitimate applications across entertainment, marketing, education and other industries.
The problem arises when those capabilities are used to deceive.
How the Business Model of Brand Abuse has Changed
To start with, Gen AI and automation have driven bad actors’ costs close to nothing. They don’t need infrastructure, ideas or marketing budget. They simply need to track where consumer demand is, imitate the brand in question, piggyback their marketing campaigns and meet the rise in demand. Modern scammers operate smartly, like a business, and track their ROI and adapt accordingly.
Why deepfakes matter to brands
The traditional brand protection conversation has centred on familiar forms of infringement: counterfeit products, trademark misuse, copyright infringement, unauthorised sellers and fake websites.
These threats remain important. But deepfake introduces a whole different challenge because the content itself can become the vehicle for brand impersonation.
Consider a consumer scrolling through social media.
- They see a familiar celebrity apparently recommending a product.
- The video looks professional. The voice sounds genuine.
- The branding is consistent.
- There is a link to a website offering a significant discount.
For the consumer, there may be very little obvious indication that anything is wrong.
That creates several potential risks for the genuine brand:
- Reputation: consumers may associate the brand with poor-quality or fraudulent products.
- Trust: customers may become less confident in legitimate communications and promotions.
- Revenue: consumers who purchase from fraudulent sellers may never reach the genuine brand.
- Consumer safety: counterfeit products can be unsafe, particularly in sectors such as health, beauty, toys and consumer goods.
- Marketing integrity: legitimate campaigns can be copied, manipulated or repurposed to support fraudulent activity.
The issue therefore extends beyond intellectual property misuse. It becomes a question of whether consumers can trust what they are seeing and hearing online. Without trust, even genuine brands lose brand equity.
Plus, legislation is still catching up with the deepfake threat. Laws in the UK, US and Europe now address intimate image abuse and mandate greater transparency, yet the wider risks of impersonation, brand harm and misinformation still fall largely outside their reach.
Download this guide on the different regional legislations for deep fakes to find out more.
A fraudster can take legitimate brand images or video, combine them with synthetic audio or imagery, and create content suggesting that the individual is endorsing something they have never even seen.
The same principle applies to company executives. A fabricated video or audio clip appearing to come from a CEO could be used to promote an offer, communicate false product information or direct customers towards an unauthorised website.
The technology therefore allows bad actors to exploit something brands have spent years building: trust and credibility.
Overcoming the challenge of detection
Deepfakes create a particularly difficult monitoring challenge because traditional approaches may not always be sufficient.
- A simple keyword search may not identify a manipulated video.
- A brand name may not appear in the accompanying text.
- An image may have been altered significantly enough to evade basic image matching.
- And a fraudulent account may use the identity of an individual rather than the company’s name.
This makes multi-layered monitoring increasingly important, with the objective to make brand abuse economically unattractive. The way to do this is to categorise and score the infringements based on risk exposure for example. As the technology learns from identifying patterns, monitoring can be scaled wider which enables brand protection analysts to identify potential networks where the risks are greater.
What can brands do?
There is no single solution to the deepfake problem. Instead, businesses should consider how their existing brand protection strategy can adapt to an environment where synthetic content can be generated quickly and distributed widely.
Know what needs protecting
Your brand is more than your registered word mark or logo.
Consider the people, products, imagery, campaigns, slogans and other distinctive assets that consumers associate with your business.
The more recognisable an asset is, the more valuable it may become to someone attempting to impersonate the brand.
Monitor beyond marketplaces
Brand monitoring should not stop at counterfeit product listings.
Social media, domains, search engines, paid advertising, websites and other digital channels can all play a role in an impersonation campaign.
A 360-degree view of how a brand is being used and misused online gives businesses greater visibility of emerging threats.
Establish clear escalation processes
Detection is only useful if it leads to enforcement action.
Teams should understand what happens when suspicious content is identified, who assesses it, what evidence needs to be collected, and which platform or legal route should be used for enforcement.
The faster a business can move from detection to evidence to enforcement, the better positioned it is to limit potential harm.
Protect the customer, not just the IP
A deepfake can be damaging even where the underlying IP infringement is difficult to establish immediately.
If a fraudulent video is directing consumers towards a scam website, for example, the immediate concern may be customer safety and trust.
Brand protection should therefore sit alongside wider business functions including legal, cybersecurity, fraud, communications and customer service.
AI is making brand abuse faster, cheaper and harder to detect — meaning brands must protect not just their products and IP, but the trust and credibility behind them.
The future of brand protection
Generative AI is not creating an entirely new category of brand risk. In many cases, it is making existing forms of online abuse faster, cheaper and more convincing. That distinction is what matters.
Businesses do not necessarily need to reinvent their entire brand protection strategy. They need to make sure that their existing approach can operate at the speed and scale of the modern digital threat landscape.
The brands best placed to respond will be those that understand where their biggest risks lie, maintain strong IP defences, monitor the channels where their customers are active and have the expertise and integrated processes needed to act quickly.
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