You Might Be Ready for AI, but Is Your Security?

Kyle Hill argues that for transformational AI projects to succeed, they must be built on solid foundations

What was once a promising new technology is now a business essential. Artificial intelligence (AI) has moved from the sidelines to the mainstream, becoming a key driver of business efficiency and competitive advantage. For many, the focus has shifted from exploration to integration.

Government initiatives, such as the UK’s AI Opportunities Action Plan, are further accelerating adoption. But the rush to deploy the technology may be blinding many businesses to the importance of securing these systems. Just 37% of IT leaders prioritise security when implementing AI.

The question leaders need to ask themselves today is how their business can embrace AI’s opportunities while managing its risks responsibly.

The hidden risks of unsecured AI

AI introduces a new class of vulnerabilities that traditional cybersecurity models weren’t designed to address. As the technology evolves, it requires continuous oversight to ensure that what it learns doesn’t expose the business to new threats.

Risks such as data leakage and model manipulation can have significant operational and reputational consequences. The complexity of AI supply chains – including third-party models, cloud integrations, and open-source components – means that weaknesses often exist beyond the organisation’s direct control.

“Reframe security not as a barrier to innovation, but as the foundation for it”

But it’s not just suppliers that pose threats. One of the greatest risks comes from within: many employees don’t know how to use AI securely. This can lead to accidental misuse. For example, without guidance on safe usage, they may inadvertently input sensitive data into AI tools, creating security and compliance risks.

Visibility and accountability are critical. It’s not enough to secure the underlying infrastructure; businesses need a clear view of where data flows and who is responsible for securing AI. Without that insight, AI can become a black box that is almost impossible to defend.

What should organisations do?

How can organisations embrace AI’s potential responsibly? The answer lies in reframing security not as a barrier to innovation, but as the foundation for it. Consider the following:

1: Understand security posture

Secure AI begins with visibility. Organisations should examine training data, AI models, APIs, and integration points across the business. By doing this, IT leaders will be aware of potential vulnerabilities. This kind of 360-degree insight enables them to prevent minor issues from escalating into operational or reputational crises.

2: Embed security into strategy, not just systems

In-depth understanding will also enable teams to elevate secure AI to a strategic priority. AI adoption is now a board-level initiative, and AI security requires the same level of attention. When security is integrated into AI strategy from the outset, it becomes an enabler of innovation rather than a last-minute compliance exercise.

3: Build a culture of secure AI innovation

A shift in organisational mindset is equally critical. Security and innovation are not mutually exclusive. Instead, security enables responsible experimentation. When teams understand that risk management is embedded into every stage of AI development, they can innovate confidently without compromising safety.

“One of the greatest risks comes from within: many employees don’t know how to use AI securely”

Employee training is just as necessary. Even the most robust AI systems are vulnerable if staff are unaware of responsible usage practices. Training should cover secure data handling, interpreting AI outputs responsibly, and recognising AI-generated threats. Employees, empowered with knowledge, become active defenders rather than potential sources of vulnerability.

4: Don’t see security as a one-off priority

Security shouldn’t just be considered at the start of AI implementation; it should be a top priority every step of the way. From design and development to deployment and monitoring, continuous vigilance ensures that AI systems remain resilient as the technology evolves.

Together, these steps form a blueprint for secure AI adoption. Security becomes a platform for trusted and confident innovation, supporting long-term value creation while minimising exposure to breaches or operational disruption.

The future of secure AI

For organisations to adopt AI successfully, it must be built on secure foundations. It’s no longer enough to simply see the value in AI; businesses need to understand how to realise it responsibly. Those that embed cybersecurity into every stage of the AI journey, from ideation to deployment, can harness its potential while minimising risk.

By integrating risk management into strategy and fostering a culture of responsible use, businesses can drive growth, efficiency, and resilience, turning AI into a trusted engine of transformation.