Quantum and AI Are Breaking Trust Everywhere at Once

The Connected Economy has relied on a few supposedly stable assumptions as it scaled. One of the most crucial was that if systems could authenticate users, encrypt communications and validate transactions, trust would scale alongside connectivity.

That assumption is now failing in real time. A Friday (May 22) report from the Financial Times reiterated that the crypto industry’s concerns around “Q-Day,” or the moment quantum computing becomes capable of breaking the widely used encryption standards public blockchain systems rely on, have moved from distant speculation to active strategic planning. PYMNTS has long been tracking the momentum behind quantum capabilities, as well as their impact beyond just the digital asset space.

The same forces destabilizing digital assets are separately rippling across sectors as seemingly unrelated as trucking logistics networks, eCommerce platforms, industrial supply chains, financial institutions and enterprise software ecosystems. The infrastructure designed to establish trust online, from passwords and digital certificates to vendor onboarding systems and payment rails, is increasingly vulnerable to industrialized fraud, AI-enabled impersonation and next-generation cryptographic threats.

The attack surface has widened dramatically, while the distinction between human and machine behavior has become harder to verify. As generative AI accelerates impersonation capabilities and cybercriminal operations become increasingly automated, what once looked like isolated cybersecurity problems have converged into something larger: a systemic erosion of trust itself.

Read more: AI Is Cracking Open Banking Before Quantum Gets the Chance

The Great Trust Breakdown

The foundational layer of digital trust has long rested on cryptography. Encryption secures banking transactions, software updates, logistics records, medical systems, cloud platforms and blockchain infrastructure. Yet the rise of quantum computing threatens to undermine many of the mathematical assumptions underpinning that security. As a result, the connected economy is entering an era in which verification and not connectivity could determine competitive resilience.

The smokestack economy faces another dimension of the problem. Industrial systems often rely on aging infrastructure with embedded cryptographic standards that are difficult to upgrade. Factories, energy systems and transportation networks may carry operational technology lifecycles measured in decades rather than years. That creates a dangerous lag between available innovation and its implementation.

And if quantum computing threatens machine trust, generative AI is destabilizing human trust. The rapid proliferation of AI-generated voice cloning, synthetic identities and hyper-personalized phishing campaigns is transforming fraud from a largely opportunistic activity into a scalable industrial operation. Attackers no longer need sophisticated malware to compromise organizations. Increasingly, they simply need to convincingly imitate trusted participants within a system.

Findings in PYMNTS Intelligence’s new report in collaboration with Trulioo, “Scale Amplification: How Revenue Amplifies Agent-Driven Identity,” show that large enterprises are increasingly the ones contending with today’s rising wave of AI-generated cyberattacks. Larger firms, with their larger footprints, can be more susceptible to the AI-powered spoofing of identity documents thanks to the industrialization of deepfakes and automated data scraping capabilities by adversarial cyber actors.

The challenge is especially severe because modern businesses increasingly depend on third-party integrations and decentralized ecosystems. Every API connection, contractor login, cloud vendor or logistics partner extends the perimeter of trust beyond organizational boundaries.

See also: APIs Are Making Bank Data Harder to Protect

Verifiable Trust Becomes the Next Competitive Advantage

The incentives that fueled growth, such as reducing verification requirements, simplifying user access, and accelerating participation, are increasingly colliding with security realities. The digitization of procurement, logistics coordination and supplier management has created enormous efficiency gains while also introducing cascading vulnerabilities.

Manufacturing firms are confronting rising threats involving counterfeit components, manipulated invoices and compromised supplier credentials. Logistics providers face ransomware attacks targeting freight management systems and warehouse operations. Retailers must contend with fraudulent distributors and inventory diversion schemes. These are no longer isolated cyber incidents. They represent systemic risks to operational continuity.

What is emerging across sectors is a transition away from implicit trust toward continuous verification. Zero-trust architecture, decentralized identity systems, post-quantum cryptography, hardware-backed authentication and AI-driven anomaly detection are all components of the same broader shift: trust must become measurable rather than assumed.

PYMNTS has covered how, instead of relying on one-time authentication events, organizations increasingly require continuous trust assessment based on device integrity, behavioral patterns, geolocation, transaction history, enterprise permissions and contextual risk signals. Identity becomes less about proving who a user is once and more about continuously validating whether an interaction remains trustworthy over time.

After all, in the connected economy, trust is no longer a background assumption. It is becoming the central operating system of commerce itself.