Online brand abuse used to be a craft. Small groups of skilled scammers, that would spend a week targeting individual brands with phishing sites, a handful of counterfeit listings or a wave of emails. It would be painful for the brand on the receiving end, but contained, and answerable to the same playbooks that brand protection teams have used for the better part of two decades.

That world is gone.

In the last twenty-four months, generative AI has stripped cost, expertise, and friction out of brand abuse. What used to take a small team a week now takes one operator an afternoon. Phishing kits assemble themselves. Storefront generators spin up convincing counterfeit shops in minutes. Deepfakes impersonate executives well enough to fool finance teams.

This isn’t a surprise to anyone. We could all see that AI was making brand abuse faster and cheaper, and doing things that happened before, but quicker. The difference now is scale. Where before AI was being used as a tool to make better fakes, now it’s running almost the entire system. Before, each vector of attack was quick, but isolated. Now a single person, with an off-the-self set of prompts, can be an entire phishing war, all automated, cross-platform, scalable and responsive.

This is not an incremental escalation. It is an industrialization.

The Brand Protection Numbers are Startling

Aggregated industry research now points to roughly 87% of global organizations reporting AI-enabled cyberattacks in 2025, with around 85% citing deepfake-driven threats specifically (AllAboutAI). Phishing volume has climbed more than 4,150% since ChatGPT’s launch (SlashNext, reported by SOCRadar). Microsoft’s 2025 Digital Defence Report finds that AI-generated phishing is roughly 4.5 times more effective than human-written messages: a 54% click-through rate versus 12%. DomainTools tracks more than 1,000 newly malicious websites going live every day, with spikes touching 2,500. And IBM’s 2025 Cost of a Data Breach Report places the average global breach at 4.44 million.

They’re big numbers, scary ones even. And they reflect something that hasn’t changed. Attack leads and defence follows.

Why Old-school Brand Protection is Failing

For most enterprises, brand protection is still organized around three assumptions: that monitoring catches threats, that takedowns resolve them, and that each channel is its own problem to solve. None of those assumptions hold anymore.

Monitoring is not understanding, because a queue of forty thousand alerts is just noise. Detection is not protection, as by the time something is flagged, customers are already losing money. And enforcement is not resolution. You can take down a hundred fake storefronts in a week and the same actor will spin up another thousand before your team reaches the bottom of the list.

The problem is volume. Where scammers used to be something you did, now it’s product off a shelf that anyone can do, and that means brand teams are now being outpaced roughly fifty to one by automated abuse. No human-scale workflow can close that gap. And point solutions – one tool for domains, another for social, another for marketplaces – only make it worse.

Intelligence-led Brand Protection

The brands that win the next decade of this fight will not be the ones that monitor better. They will be the ones that think smarter. That requires four shifts.

The first is predictive detection. Instead of reacting to live abuse, identify the infrastructure being set up to enable it, such as domains being registered in clusters, social profiles being prepared, content being generated against your brand at scale, and disrupt it before it activates. Machine learning helps here, but the real change is spotting the intent of what’s being created, not just the content. It’s about seeing the patterns that predict a building threat, and not the threat itself.

The second is cross-channel intelligence. A single threat actor today touches domains, paid search, social media, messaging apps, marketplaces, and increasingly the dark web. Treating each as a separate silo is missing the forest for the trees. The signals only make sense when taken as a whole.

The third is risk-based prioritization. Not every infringement is worth chasing, and not every takedown moves the needle. Your efforts should follow the business impact: revenue at risk, customer harm, executive exposure, and regulatory consequence.

Finally, there is strategic enforcement. Tactical takedowns will always be part of the work, but the goal has to be dismantling campaigns and suppressing the actors behind them, not chasing every individual artifact. That means bundling enforcement across channels and partners, and treating each engagement as part of a longer campaign against the actor, not a one-off case.

What You Should Do for Brand Protection in 2026

Brand abuse has industrialized. Defence has to industrialize with it. For most enterprises, that means breaking down internal silos between brand, legal, security, and digital risk; prioritizing on risk rather than volume; bundling enforcement across channels; and quantifying business impact in numbers a CFO recognizes. It also means a reframing. Moving from “brand protection” to “brand risk management” which belongs where it should sit: alongside cyber and financial risk on the executive agenda.

At BrandShelter, this is the work we are focused on with the brands we partner with. Not better monitoring. Better thinking, plugged into intelligence and enforcement that can actually keep up with what we are now facing.

We used to fight scammers. Now we fight systems.

If you are rethinking your brand protection strategy for 2026 and want to compare notes, I would be glad to continue the conversation. Connect with me on LinkedIn.

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