We’re moving into a world where algorithms create content that is only consumed by other algorithms. Case in point: slop, the shoddy AI-generated junk that has been optimised for search engines and other means of content discovery. In edge cases, it’s not even intended for the human eye. Fake it till you make it?

This, and the degrading of the user experience, has serious consequences: it erodes consumer trust to the point that consumers hesitate to use the internet despite its convenience. Digital technology has a trust issue – again, we might add, as it has taken decades for the internet to gain the trust of consumers that it enjoyed in its heyday. Brands need to think about how they prove their authenticity. Acting genuinely in a world full of fakes is vital.

It’s a question of reality. If we can’t tell the difference between fake and real, how do we trust the real thing? Generative AI could be the straw that breaks the camel’s back. Fake news, pseudo products, fake reviews, fraudulent brands, websites, or pictures increasingly mislead people and thus spur their hesitation towards spending money online, or even engaging there in the first place.

For example, compare the user experience of a Google or Amazon search in the early days with today: what once was relatively clean and straightforward is now clogged with advertising, misleading or even totally false results. We can’t trust reviews anymore, nor can we expect to get what we ordered. Generative AI has made it easy to fake every part of the digital experience.

Brands are on the hook

GenAI is also increasingly used by criminals, like scammers, targeting people’s money and personal information. This leads consumers to hesitate before they buy, or sign-up. As Accenture’s Life Trends 2025 report puts it:

For years, organizations have been asking people to prove who they are. Now, brands are on the hook to do the same.

Brand safety has been an issue for years now. The fragmentation of channels has made it more and more difficult to maintain. The contamination of channels with slop, fakes, scams, and harm only adds to the burden. Again, brands need to control — and possibly own — the channels they use to communicate. Direct-to-consumer (DTC) has a clear advantage in this game.

For the platforms, this adds another layer of responsibility and liability. If they don’t want to lose the game, they need to step up and mitigate the issue. Otherwise, people and brands will vote with their feet, and governments will intervene with further regulation. Consumer safety is the flip side of the brand safety coin.

Can we expect the platforms to take action in this matter? If their track record so far is any indication, the chances are mixed at best. Google and Amazon, to get back to these examples, have deliberately worsened the user experience for the sake of profit. It is very likely that they will only take action when they are forced to do so or feel the cost of inaction in their wallets. It’s merely a question of time before we see if they can genuinely fake it till they make it with changes that enhance trust.

Regulation on the rise

Another, related issue we’ve discussed before is the use of content for training AI models. As with many platform matters, there is a blatant imbalance between operators and users. With regard to user consent, the report makes it very clear:

doing this via terms and conditions will not be enough. People must be afforded a fair opportunity to evaluate whether to allow the use of their personal data.

Creators, artists, media and individual people are already grappling with issues like consent, copyright and privacy. We expect to see legislation, regulation and protection increasing rapidly and unevenly in relation to AI use cases.

After California’s governor vetoed the AI safety bill, some people expected that AI would go unregulated in the US, giving Big Tech a huge advantage over European companies that need to comply with the EU AI Act. However, this advantage is likely limited. Sooner or later, AI will be regulated in the US as well. In order to access the European market, huge platforms will be forced to comply with EU regulations anyway.

The days of the internet as an unregulated industry are long over, and they won’t come back.

The same is true for the age of disruption, as a mindset and a business model. The era of fake and consumer hesitation demands a more cautious approach. It is a clear example of the “fake it till you make it” mindset reaching its limits. If anything, it’s Big Tech itself that is ripe for disruption. This oligopoly unites the most powerful organisations in the history of humankind.

A new business model for insurance

So far, generative AI hasn’t disrupted Big Tech but rather user experience, trust and authenticity on the web. In the words of the Life Trends 2025 report:

In a matter of months, what people thought they knew and trusted about how they consumed information, socialized and shopped online changed. Generative AI’s ability to facilitate hyper-personalized harm and harassment, deep-fakes and scams has quickly become a serious issue. Every day, people are experiencing a pause—questioning the authenticity of the information they’re reading, the products they’re seeing, the websites they visit, and the calls, texts and emails they’re receiving.

It will need the combined action of platforms, brands, customers (and customer support), as well as governments to reestablish trust. Interestingly enough, the authors also see a new business model for insurance companies:

If the volume of deep-fake scams continues, insurance companies may want think through new types of products, similar to the identity theft products launched years ago. A new insurance product against deep-fake scams and abuse could offer coverage for financial losses, legal fees and emotional distress, and could provide comprehensive protection and support for victims of digital fraud and harassment.

It’s not that modern capitalism lacks creativity when it comes to solving, or at least mitigating, the problems it has created.