Verified Content Is Becoming the Currency of the AI Age

EBM EXPERT ANALYSiS- Eoin Shanley, Director of Product Management, DigiCert

Earlier this year the chief at the Bank of Italy was viewed on media platforms endorsing what looked like risky investments. Except he wasn’t. It was a deepfake and the bank was quick to share warnings of this. However, it remains a prime example of how AI-generated deepfake content isn’t just misleading customers and shareholders, it is actively undermining public trust in organisations and key institutions.

Faked content is now appearing authentic enough that it’s being shared by established organisations, making its way to the social feeds of users and potential customers. According to recent research, humans have a 50-50 chance of defecting faked content. This coin-toss probability is damaging relations between businesses and their end-users.

Misinformation has always been prevalent throughout history; it is an ironically human thing. However, a volatile geopolitical landscape combined with the modern ability to generate images, videos and signatures within seconds using generative- AI has meant the speed in which misinformation props up and spreads is devastating. People aren’t just misled; a sceptical culture is being created around the idea if anything can be believed at all.

 When hesitation becomes confusion, becomes ambiguity

We tend to frame the modern information crisis as a battle between “real” and “fake.” But that framing misses the deeper issue. Ambiguity.

When content looks authentic but can’t be verified, people hesitate. When multiple versions of a story circulate with equal visual credibility, trust erodes. Over time, this creates an environment where bad actors don’t even need to persuade, only to confuse.

This ambiguity can become fertile ground for manipulated narratives, impersonation and misleading claims that can damage even the strongest brand identity.

 The critical need for instant verification

AI-generated images, video and audio are may now good enough to pass casual scrutiny but, more importantly, they are cheap, fast and endlessly remixable. This lowers the barrier for sophisticated attackers and everyday opportunists chasing attention, clicks or profit.

This misinformation can affect nearly every aspect of a business. From consumers deciding whether a promotion is legitimate, to investors evaluating announcements to determine if they’re real. In this environment, asking people to be more sceptical is not a solution. Scepticism without verification simply leads to disengagement. Instead, people must instantly have verified proof of a content’s creator, whether it’s been altered and where it’s come from.

This is where the emerging concept of content trust becomes essential. Instead of trying to identify what’s fake after the fact, authenticity must be visible at the point of consumption.

Unlike platform-based verification, these credentials must be attached to the file itself. Whether reposted, screenshotted or shared across platforms outside the original publisher’s control, the content must be cryptographically signed and verified, providing tamper-evident provenance and transparency.

Trust as part of the DNA, not an add-on

For decades, the internet has relied on invisible trust mechanisms, such as certificates, encryption and identity verification, which quietly protect users without requiring them to understand the underlying technology. Digital content deserves the same treatment.

Retrospectively verifying whether a social media post is real once the internet has debated its legitimacy is not a viable way forward for businesses. Instead, cryptographic assurances must be embedded directly into content, allowing everyday users to distinguish between verified sources and unverified claims without becoming a debate.

Cryptographic protection and verification must also apply to a business’ AI systems. Every day, AI agents are being embedded into operational functions. Securing consumer trust in digital content is important. But equally so is maintaining trust internally. A rogue AI has the potential to disrupt every aspect of internal processes, undermining not only consumer confidence if data is mishandled, but also investor trust. As AI takes on a growing role as a digital workforce, every action must be clearly attributable and controlled. This demands a verifiable chain of custody for models to ensure they have not been tampered with, are running in trusted environments and are handling sensitive data securely. 

Breaking the cycle, from rebuilding to day one trust

In many ways, the internet has become its own worst enemy. It has grown too complex to project trust in a definable way. In an age where AI is used in almost every part of modern life, trust must become the cornerstone of valued content.

As deepfakes become more frequent, businesses have entered a vicious cycle of continuously having to rebuilt trust. To overcome this, organisations must proactively establish trust from day one by ensuring their own content is verified when viewed by end-users.

The reality is that the cryptographic frameworks that secure sensitive data, digital identity and websites must be applied to everyday content. Only then, can consumers feel confident in a business.