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Cyber

Navigating AI risk 

by Mark Rowe

In the rapid evolution of the digital enterprise, 2026 has become the year where the promise of Artificial Intelligence met the reality of the cyber front line, writes Bob Bailkoski, CEO of the tech firm Logicalis.

For many IT leaders, the initial excitement surrounding AI has been replaced by a sobering realisation that the technology is maturing faster than our ability to secure it.

The pressure to innovate, while defending against increasingly sophisticated threats, is stretching security teams to their limits. The sentiment is so significant that, according to the 2026 Logicalis CIO report, nearly half of CIOs globally admit they often wish AI had never been invented. This isn’t just tech fatigue, it is a candid admission that AI has rewritten the risk landscape, emerging as both a critical tool for progress as well as a primary vector for attack.

The new tier of cyber risk

For years, malware, ransomware, and phishing have dominated the C-suite’s security concerns. In 2026, AI has joined ranks alongside the big three. As AI-powered threats outpace traditional defences, the arms race between attackers and defenders has moved from theoretical to operational. We are seeing that the tools intended to drive efficiency are being repurposed to find vulnerabilities at machine speed, creating a defensive gap that manual intervention can no longer close.

The danger isn’t just external. One of the most significant risks identified by IT leaders is the emergence of Shadow AI – the unsanctioned use of AI tools by employees without IT oversight. With improper AI use, employees can jeopardise data security and create entirely new security blind spots within the business. Without clear visibility into AI usage, governance is a phantom concept.

Baking in a blueprint

Despite the high stakes, there remains a disconnect between recognising risk and implementing safeguards. To move from a state of reactive anxiety to proactive resilience, governance must be baked in from the start of every AI initiative, rather than bolted on as an afterthought when a breach occurs. CIOs should consider:

Demystifying AI: One of the biggest risks is not knowing how AI reaches its conclusions. By using mechanisms that clearly explain why AI made a specific decision, something only 40% of companies currently do, leaders can be confident the technology remains fair, accurate, and fully compliant.
Gaining visibility: You cannot secure what you cannot see. To stop shadow AI in its tracks, companies need to know what tools are in use and keep detailed logs of what data is going in and out of organisation. Security teams can easily spot a data leak or a malicious prompt, rather than discovering the damage months later.
Treating AI like an unverified guest: Just as you wouldn’t hand a building pass to a stranger, you shouldn’t give an AI agent unrestricted access to your company data. This means blocking AI tools from automatically changing core business files, testing new apps in isolated digital environments, and requiring strict approval before any AI can share sensitive information.

While internal upskilling and new certification programs are part of the long-term answer, 44% of IT leaders are now bringing in managed services to close immediate skills gaps. This highlights a fundamental change in the executive brief; the role is no longer about maintaining every piece of infrastructure in-house. It is about knowing how and when to leverage external specialists to protect the business.

The answer to security pressures is not to halt AI adoption, but to change how we execute it. This challenging period should serve as an opportunity to establish real operational discipline around emerging tech, ensuring transparency and control are present from day one.

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