Deepfakes as a trigger of a new economy

You used to prove your identity with a password. Now you need to prove you’re not synthetic.

The alarm bells started ringing in Hong Kong when an employee transferred $25 million to fraudsters during what appeared to be a routine video conference with colleagues and the CFO. The twist? Everyone on that call, except the victim, was a deepfake. This wasn’t just another fraud case; it was a watershed moment that exposed a fundamental crack in the foundation of digital society: our ability to distinguish real from synthetic has collapsed.

We’re not just dealing with a new type of fraud. We’re witnessing the breakdown of digital identity itself. We’re at an inflection point where the distinction between authentic and synthetic digital content may become permanently blurred. The institutions that depend on digital trust, banking, government, healthcare, and education are all adapting to this new reality.

But perhaps more fundamentally, we’re redefining what it means to be human in digital spaces. The question is no longer just “who are you?” but “are you real?”

The Death of “Know Your Customer”

For decades, identity verification followed a simple playbook: collect documents, verify information, maybe add a security question or SMS code. The underlying assumption was that humans interacting with systems were, well, human. That assumption is now extinct.

Deepfakes have dramatically undermined trust in digital media and digital identity verification, with profound implications for fraud and other social ills. The problem isn’t just that bad actors can now create convincing fake identities; it’s that the very concept of proving authenticity has become exponentially more complex.

Consider what “Know Your Customer” means today. Banks, governments, and businesses must now answer a question they never had to ask before: Is the person I’m interacting with actually a person?

The Scale of Synthetic Reality

The numbers tell a stark story. The UK government says a projected eight million deepfakes will be shared in 2025, up from 500,000 in 2023. But these statistics only capture what we can detect. The reality is likely far worse.

According to the 2024 Sensity State of Deepfakes report, the number of available tools for deepfake generation rose to more than 10,000 in 2024. Creating synthetic identities is no longer the domain of sophisticated hackers, it’s now easily accessible to everyone with a few clicks. Major platforms now offer deepfake-type generation as a standard feature, while fraud-as-a-service solutions have industrialized the production of synthetic identities.

This democratization of synthetic media creation has a chilling implication: we’re approaching a point where synthetic content may soon outnumber authentic content online. We’re not just fighting fraud; we’re fighting for the integrity of digital reality itself.

The Identity Crisis Across Sectors

The breakdown of digital trust isn’t theoretical, it’s happening now across every sector of the economy. Financial institutions are losing an average of $600,000 per voice deepfake incident, with 23% losing over $1 million. 87% of finance professionals admit they would make a payment if ‘called’ by their CEO/CFO, while the FBI has warned of malicious campaigns targeting senior government officials with AI-generated voice messages.

Perhaps most concerning, North Korean IT workers are now using deepfake technology for online job interviews to infiltrate US organizations, creating a new category of insider threat: employees who were never real to begin with.

Crossing the Valley

The battle between deepfake creation and detection has become the defining technological arms race of our time. According to research from the IEEE, with new deepfake generation methods emerging, detecting deepfakes will become increasingly challenging, and the accuracy and efficiency of current deepfake detection approaches will decline.

Traditional detection methods are failing. Early “true” deepfakes often included artifacts at the pixel level or above, spatial or visual inconsistencies such as differences in noise patterns, or color contrasts, which are indications of synthetically generated media. However, refinements in a technology that at its core is based on always learning means that the visual hallmarks of generative AI are being eliminated.

Many industry experts emphasize that the most sophisticated deepfakes are no longer obvious to the human eye and are good enough to fool some authentication systems. We’ve crossed the uncanny valley where synthetic humans are now indistinguishable from real ones.

The Economics of Authenticity

We’re witnessing the emergence of what could be called the “authenticity economy”: a fundamental shift where proving you’re real becomes a billable service. Market forecasts predict 9.9 billion deepfake checks by 2027, generating nearly $4.95 billion in revenue. These numbers represent the commodification of basic human existence in digital spaces.

The Monetization of Being Human

For the first time in history, being provably human has become a premium service. Every digital interaction now carries an authenticity tax—the cost of proving you’re not synthetic. According to Deloitte, as deepfakes proliferate, “credible content is expected to come at an increased cost for consumers, advertisers, and even creators.”

Consider what this means practically:

• Opening a bank account requires humanity verification alongside identity verification
• Video calls need real-time deepfake detection
• Social media platforms implement “verified human” badges
• Dating apps add biometric liveness checks to prove users aren’t AI-generated personas

The New Digital Divide

This authenticity economy is creating a troubling new digital divide based on who can afford to prove they’re human. Those with access to premium verification services, high-end smartphones with advanced biometric sensors, fast internet connections, and the ability to pay for sophisticated authentication tools, get seamless access to digital systems. Meanwhile, those without these resources face increasingly intrusive verification processes or find themselves locked out entirely.

The costs ripple through the entire system. Voice deepfake detection services can cost organizations hundreds of thousands annually, expenses that inevitably get passed down to consumers through higher fees and service charges. Premium “privacy-preserving authenticity” services using advanced technologies like zero-knowledge proofs and homomorphic encryption come at even higher costs, creating multiple tiers of digital identity verification where the wealthy get both better security and better privacy protection.

For individuals, the barrier isn’t just financial, it’s technological. Sophisticated biometric verification systems require newer devices with advanced cameras and sensors that may be inaccessible to lower-income users. As authenticity verification becomes mandatory for everything from banking to employment, those without access to cutting-edge technology risk being systematically excluded from digital society.

Platform Transformation and Market Segmentation

The authenticity economy is reshaping platform business models. Social media companies now invest heavily in synthetic content detection. Dating apps are adding verification features alongside traditional matchmaking. Professional networking platforms like LinkedIn have instituted verification processes to combat fake profiles, while organizations integrate specialized services like Reality Defender or Pindrop for virtual meetings.

This represents a fundamental change in value creation online. While platforms have long monetized attention and data, the next frontier could be in monetizing trust and authenticity. As deepfakes proliferate, guaranteeing real human interactions will become a competitive differentiator and premium pricing source.

An entire industrial ecosystem has emerged around authenticity verification. More than 40 vendors now provide deepfake detection technologies, from established biometrics companies to specialized startups. The market has already segmented into niches: real-time voice verification, video meeting authentication, biometric onboarding, content authenticity for media, and identity proofing for employment.

Economic Implications and Global Fragmentation

The authenticity economy is creating new categories of risk and opportunity. Insurers have extended cyber policies with AI-specific endorsements covering deepfake fraud. While credit agencies currently focus on synthetic fraud detection, broad-based “authenticity scores” integrating provenance metrics may emerge. The infrastructure investments parallel the internet’s early networking requirements.

Different regions approach regulation differently. The EU’s AI Act mandates identifying AI-generated content, creating jurisdiction-specific compliance costs. China emphasizes content labeling, while the US focuses on fraud prevention and national security. This regulatory fragmentation creates complex global cost structures and balkanizes the authenticity economy—where being verifiably human costs different amounts based on geography.

As synthetic content proliferates, authentic content may command “authenticity premiums.” Verified human photography, performances, and writing could become luxury goods in a world flooded with synthetic alternatives. The cost and scarcity of provable authenticity could drive its value exponentially higher.

Rebuilding Digital Trust

The deepfake crisis has forced us to confront uncomfortable truths about digital identity and rethink how trust works online. The solution isn’t just better detection technology, it’s fundamentally reimagining digital identity systems.

Trust is No Longer Transitive: In the past, if you trusted a platform, you could trust the identities on it. That assumption is dead. Every interaction must now be independently verified.

Authentication Must Be Continuous: Static identity verification is insufficient. Peter Eisert, head of Vision & Imaging Technologies at Humboldt University, notes that current deepfake detectors are frame-by-frame based, whereas they should be attuned to “inconsistency over time.” We need systems that continuously verify authenticity throughout interactions.

The Privacy-Security Trade-off: The more we need to verify authenticity, the more personal data we must share: biometric templates, behavioral patterns, device fingerprints. This creates a fundamental tension where proving you’re human requires surrendering privacy to verification systems.

The path forward requires systems that:

1. Assume Synthesis by Default: Rather than assuming content is authentic unless proven otherwise, systems must start from the assumption that all digital media is potentially synthetic.
2. Implement Multimodal Verification: Single-modality deepfake detectors are increasingly fragile. Long-term resilience requires multimodal fusion and real-world signal integrity checks.
3. Build Temporal Consistency: Identity verification must examine patterns over time, not just single moments of interaction.
4. Create Cryptographic Provenance: We need systems that can cryptographically prove the origin and authenticity of digital content from the moment of creation.

The Future of Human-Digital Interaction

The deepfake crisis represents more than a technological challenge, it’s a crisis of epistemic confidence in the digital age. As we build new systems to verify authenticity, we’re essentially creating the infrastructure for a post-trust digital society, where verification rather than faith becomes the foundation of all online interaction.

The UK government has declared efforts to mitigate the growing threat from AI-generated deepfakes as an “urgent national priority” and “arguably the greatest challenge of the online age.” The challenge isn’t just technological, it’s civilizational. We’re rebuilding the foundations of digital trust from the ground up.

The companies and institutions that recognize this shift early and build comprehensive authenticity verification into their systems will thrive. Those that continue to operate on pre-deepfake assumptions about digital trust will find themselves increasingly vulnerable.

The question isn’t whether we’ll adapt to this new reality. We already are. The question is whether we’ll do it thoughtfully, preserving the values of privacy, accessibility, and human agency that we want to carry into this new digital age.

In the end, the deepfake crisis may force us to become more intentional about what it means to be authentically human, both online and off. And perhaps that’s a conversation we needed to have all along.