From Risk to Revenue with Zero Trust AI

Written by Richard Beck, Director of Cyber Security, QA Ltd.

 

AI security governance is fast becoming the boardroom’s new obsession, and with good reason. From biased models and hallucinated outputs to intellectual property leakage and regulatory scrutiny, the risks of unchecked AI are multiplying by the day. The challenge ahead of us is how we innovate responsibly while ensuring trust, compliance, and control? The answer is Zero Trust architecture.

Now the term Zero Trust can be frustrating, you must see beyond vendor tech solutions. To me, Zero Trust begins with a single assumption. Your business exists in a hostile environment, and you must assume it will be compromised. Zero Trust is purpose built to address the realities of modern business. This includes securing hybrid and multi-cloud environments, reigning in shadow AI, protecting against supply chain attacks, insider threats, growing technical debt, and of course data breaches. Most importantly Zero Trust is a source for digital trust to fuel AI enabled business growth.

 

AI security will power AI growth

AI is becoming embedded deep into critical operations, from customer support to financial modeling. Many clients I speak to are already running models they didn’t build, trained on data they don’t fully control, and producing outputs that can directly impact revenue and their hard-earned reputation. The majority are concerned that without AI security, these AI supply chains become black boxes of security risk.

Zero Trust provides the architectural framework to govern these systems securely, without slowing down innovation. By enforcing strict identity controls, setting dynamic data access policies, and continuously verifying every connection. Now this can also apply to the emerging AI systems and services built with external tools and or in-house models.

 

Trust is the future currency of AI

As I mentioned, Zero Trust starts with the assumption that you exist in a hostile environment. Being on the wrong side of a hacking data compromise isn’t theoretical; it’s inevitable. As we in the security world say, it’s not if but when! In an AI growth economy, trust will be a source of competitive advantage.

The grip of AI regulators is loosening. The legislative landscape for AI security and governance globally is uncertain, with self-service opt-in and opt-out mechanisms being debated. All the while AI is no longer experimental, It’s operational. It’s making decisions, generating content, beginning to automate processes at scale, and innovating new business models. But as AI accelerates, so do the risks, from bias amplifying at machine speed, intellectual property leakage, actors seeking to weaponise generative models to bypass defences with adversarial AI.

Even if the regulators don’t mandate, your customers, and business partners will start to ask for evidence or proof that your AI systems are fair, secure, and accountable. ISO 42001, the global standard for AI management systems, will go a long way to demonstrate best practice AI governance. Evidenced by the AI giant Anthropic who becomes the first notable ISO 42001 certified business, but ISO 42001 will fall short on the critical technical implementation of AI security.

Adopting a Zero Trust architecture is how you can deliver evidence of continuously, automatically, at scale for AI security controls. This isn’t just about AI security hygiene. It’s about making AI viable for high-stakes, high-value business. Zero Trust can underpin AI security, enabling innovation within a proportionate AI security risk appetite.

 

Horizon planning turns risk into revenue

In my role as a cyber security industry leader, I like to look out beyond the horizon. I anticipate in the coming years; businesses that upskill and build cross functional AI security capability will capture market share. Why? Because they’ll be the only ones trusted to operate critical AI systems and services that touch sensitive sectors like healthcare, finance, defence, energy, and our citizen data in government, in complex global supply chains.

When I think about how to operationalise digital trust in our AI tech landscape, the obvious jump out to me. Zero Trust architecture supports automatically verifying every user, entity, device, model, and dataset through its training model lifecycle interacting within your AI ecosystem. Visibility of who, or what is accessing your data, where your models are sourcing their inputs, how outputs are being used in real-time decisions.

Protecting proprietary intelligence or whatever your ‘crown jewels’ are, for example, your data, your algorithms, your insights never leave your control. Not only does this protect revenue, but it also unlocks new revenue. By accelerating AI innovation, product use cases, reducing discovery timelines with the necessary oversight and AI security confidence to bring products and services to market faster.

Being able to respond to the security, regulatory compliance challenges of the future would need a crystal ball. However, we can be sure that as political administrations come and go, expect AI security controls to tighten again in the longer term as AI becomes a dominant force of global economic growth and national security.  Zero Trust architecture will be part of a future proofing alliance, automated evidence of AI security controls in near real time.

 

Zero Trust as the operating system of AI

As AI and autonomous agents begins making critical ethical decisions that determine life and death, AI security can’t be an afterthought. Zero Trust will become the operating system of secure AI, quietly enforcing the rules of engagement across global, dynamic, and adversarial environments. This is how the leaders of tomorrow should be preparing today. Don’t just bolt on security controls to survive audits. Accelerate ‘secure AI by design’ principles. Architect Zero Trust into the core of your AI strategy to move faster than competitors, and scale at pace, and innovate without fear.

AI security isn’t just a tech problem, nor is it only a defensive posture, it’s part of your AI strategic commercial advantage. It’s a business priority, and the businesses that get AI security right will thrive. I might be stating the obvious, but here’s the truth no one wants to say out loud, in my view, you can’t have AI enabled growth without AI security, and you can have resilient AI security with a Zero Trust architecture.

Take the Certificate of Competence in Zero Trust (CCZT) course from QA.

 

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About the Author

Richard is an experienced security professional, a former CISO turned educator, with over 15 years in operational security roles. Member of, and advisor to, industry and government cyber security bodies. A regular contributor for cyber insights, an industry collaborator, also finding time for speaker engagements. He is passionate about making a difference through education in his role at QA, that equips individuals from all backgrounds with tomorrow’s digital skills to maximise their potential and succeed in the workplace.

• Advisory board member Offensive Security (OffSec)
• Mentor for pre-seed funding cyber innovation accelerators
• DoD 8140 certification advisory committee
• Advisory partner committee ISC2
• Former vice chair and chair the government Communication Industry Information Exchange (CPNI / NPSA)
• Author, accredited and award winning National Cyber Security assured cyber training, and cyber programmes