AI Is Accelerating. Is the Security Beneath It Ready for What Comes Next?

Artificial intelligence is moving from experimental technology to essential infrastructure at remarkable speed. Organisations are deploying AI across customer service, cybersecurity, finance, software development and operational decision-making, creating systems that process increasingly valuable information. 

Yet while attention is focused on what AI can do next, another question deserves consideration: is the security infrastructure supporting these systems being prepared for the technologies that will follow? 

Quantum computing represents one of the longer-term challenges. Although cryptographically relevant quantum computers do not yet exist, their potential impact on widely used public-key cryptography means security teams have reasons to prepare before the threat fully materialises. 

AI Makes Long-Term Security More Important 

AI systems can handle enormous quantities of information, from customer records and proprietary business data to intellectual property and confidential communications. Some of this information may remain sensitive for years. That creates a problem when combined with the possibility of “harvest now, decrypt later” attacks, where encrypted information is collected today and stored until future technology makes it possible to decrypt. 

Quantum computing could eventually make certain mathematical problems far easier to solve. In particular, sufficiently powerful quantum computers could threaten public-key cryptographic systems including RSA and elliptic curve cryptography, which are widely used for secure communications, digital signatures, and identity management. 

Preparing for Post-Quantum Security 

The response is not to abandon existing cybersecurity infrastructure overnight. Instead, organisations can begin preparing for a gradual transition towards post-quantum cryptography (PQC). 

Security teams exploring this area can find information from PQShield explaining how post-quantum cryptography works, why existing public-key algorithms face quantum-related risks, and how organisations can approach migration without unnecessarily disrupting current systems. 

PQC uses algorithms designed to resist attacks from both classical and quantum computers. Importantly, these algorithms do not require organisations to own quantum computers. They are intended to operate within conventional computing environments. 

Knowing What Needs Protecting 

One of the first challenges is discovering where cryptography exists across an organisation’s infrastructure. Cryptographic functions can be embedded within applications, cloud platforms, connected devices, authentication systems and third-party products. AI infrastructure adds another layer, particularly as models, datasets and services move between different environments. 

A cryptographic inventory can help security teams identify vulnerable algorithms and determine which systems should receive priority. Long-lived devices and highly sensitive data may require earlier attention than systems with short operational lifespans. 

Building Crypto-Agility Into Infrastructure 

Organisations should also consider crypto-agility: the ability to replace or update cryptographic components without redesigning entire systems. This matters because security standards will continue evolving. Hard-coding today’s solution into infrastructure could create another difficult migration when requirements change again. For organisations developing AI products now, building adaptability into their architecture may prove considerably easier than retrofitting it years later. 

Security Has to Look Beyond Today’s Threats 

AI development naturally encourages organisations to think about speed, capability, and competitive advantage. Security planning requires a longer horizon. Quantum computing will not suddenly make every cybersecurity measure obsolete. Symmetric encryption, for example, is less affected than vulnerable public-key approaches, particularly when suitable key lengths are used. 

The bigger issue is preparation. AI systems being designed today may remain in service for years, while the information they process could remain valuable even longer. 

As AI accelerates, security cannot focus exclusively on the threats that exist right now. Building adaptable, quantum-resilient foundations gives organisations a better chance of ensuring that today’s technological breakthroughs do not become tomorrow’s security liabilities.