Why AI Security Platforms Are Non-Negotiable in 2026

Artificial Intelligence is the operational engine driving modern enterprise. But as the integration of custom-built AI applications and third-party AI services accelerates, so too do the complex vulnerabilities associated with them. We’re entering an era where traditional cybersecurity perimeters are no longer sufficient to protect sensitive data from the unique mechanics of machine learning and large language models (LLMs).

At Mondas, we recognise that navigating this new frontier requires more than just awareness, it demands best-in-class tools, informed expertise, and a proactive approach to information security.

Internal Violations vs. Malicious Attacks

It’s natural to consider threats as external actors orchestrating sophisticated breaches. While those threats remain a constant reality, the most immediate danger to your AI ecosystem might actually be sitting inside your organisation.

According to findings earlier in the year from 🔗Gartner, at least 80% of unauthorised AI transactions will be due to internal violations of enterprise policies rather than malicious external attacks. These violations typically stem from:

This phenomenon is largely driven by “shadow AI” which is the unsanctioned use of AI tools by employees seeking productivity boosts without IT oversight.

AI Security Platforms

To combat the growing risks of data leakage, prompt injection, and AI system misuse, organisations must evolve their defensive postures. Gartner projects that by 2028, more than 50% of enterprises will use AI security platforms to secure their AI usage.

These platforms are designed specifically to understand the nuances of AI interactions. They don’t just monitor network traffic; they analyse the contextual intent of prompts, validate the safety of training data, and enforce strict governance policies across all AI touchpoints.

For further context on how global authorities are approaching these systemic risks, we highly recommend reading the 🔗NCSC’s Guidelines for Secure AI System Development, which outlines the imperative of building a ‘secure by design’ framework.

CrowdStrike AIDR

At Mondas, our thought leadership is grounded in leveraging the very best tools the industry has to offer. A prime example of this next-generation defence is the 🔗CrowdStrike Artificial Intelligence Detection and Response (AIDR) platform.

We recently showcased this with a live demo, available to view in our webinar with Ignition (CrowdStrike): 🔗https://attendee.gotowebinar.com/recording/2891995313253014531

By integrating platforms like CrowdStrike AIDR into your security architecture, you gain visibility into how AI is being consumed across your network. It allows security teams to:

• Identify and categorise instances of shadow AI.
• Detect and neutralise prompt injection attacks in real-time.
• Enforce granular policies to prevent accidental data leakage by internal users.
• Protect custom-built AI applications from adversarial manipulation.

As the adoption of AI continues to scale, relying on legacy security software will leave critical blind spots. Embracing dedicated AI security platforms is the only definitive way to harness the power of artificial intelligence whilst safeguarding your organisation’s most valuable assets.

Mondas specialise in securing the AI frontier. If you’re struggling with the issues outlined in this article, or need expert guidance on mitigating the risks of shadow AI, contact us today to speak with our security specialists.

Article brought to you by Lance Nevill is the Cyber Security Director at Mondas, with a wealth of experience in threat intelligence, information security, and enterprise risk management. Connect with Lance on LinkedIn: 🔗Lance Nevill

Article First Published July 2, 2026