AI Cybersecurity Threats Demand Stronger Security Strategy

AI cybersecurity threats are reshaping enterprise security as artificial intelligence transforms cybersecurity operations and IT infrastructure. While AI offers faster threat detection and automation, many organisations still struggle to adopt it securely and integrate it into existing security programs. According to Fortinet, businesses must build governance, visibility, and resilience into their AI strategy from the beginning instead of responding after risks emerge.

As AI cybersecurity threats continue to evolve, AI adoption also continues to accelerate across Australia following new government initiatives, including the Australian Public Service AI Plan 2025 (1) and the Australian Government’s updated Policy for the Responsible Use of AI in Government (2). These initiatives encourage greater AI adoption while strengthening governance and accountability. As organisations expand AI across the workplace, cybersecurity leaders face increasing pressure to balance innovation with security.

Glenn Maiden, Chief Security Officer and Director Threat Intelligence, Australia and New Zealand, Fortinet, said:

“AI adoption is moving faster than many organisations can govern it. Employees are already integrating AI tools into day-to-day workflows to improve productivity and automate tasks, while organisations are still building the policies, controls, and visibility needed to manage risk. Businesses need to align security strategies to their AI journey from the beginning, not after exposure has already increased.”

AI Cybersecurity Threats Are Reshaping Security Operations

Many organisations now focus on two connected priorities:

Using AI to strengthen cybersecurity operations.
Securing AI tools, models, and workloads across enterprise environments.

These priorities reflect AI’s growing presence across productivity platforms, cloud infrastructure, operational technology (OT), and security operations centres (SOCs).

Security teams increasingly rely on AI to detect threats, automate repetitive tasks, analyse telemetry, and assist with investigations. However, organisations achieve the greatest value when they integrate AI into existing security frameworks rather than deploying it as a standalone capability.

Glenn Maiden said:

“Organisations achieve the strongest outcomes when they use AI to reinforce existing security controls and processes rather than replace them. AI can help security teams improve visibility, automate investigation and response workflows, and reduce operational complexity, though governance and oversight remain critical.”

Agentic AI Expands AI Cybersecurity Threats and Automation

Agentic AI continues to increase automation across cybersecurity operations. Organisations now deploy AI assistants and autonomous agents to streamline workflows, coordinate activities, and improve operational efficiency.

These systems support:

Threat hunting
Security reporting
Data correlation
Incident response
Investigation workflows

By connecting intelligence across multiple security platforms, AI agents help security teams respond more quickly and consistently.

Integrated Visibility Improves AI Effectiveness

AI delivers stronger results when organisations maintain complete visibility across their environments. Fragmented infrastructure creates blind spots that reduce context and limit automated decision-making.

Integrated security architectures provide visibility across:

Users
Endpoints
Networks
Cloud workloads
Operational Technology (OT)

This broader visibility allows organisations to prioritise threats more accurately and apply security controls consistently.

Glenn Maiden said:

“AI is only as effective as the visibility and data behind it. Organisations operating across disconnected environments will struggle to apply AI consistently because blind spots reduce context and limit automation. Integrated platforms help organisations strengthen visibility, simplify operations, and apply security controls more consistently across hybrid environments.”

Shadow AI Increases AI Cybersecurity Threats

Shadow AI has become one of the biggest contributors to AI cybersecurity threats facing modern organisations.

Recent guidance from the Australian Signals Directorate (ASD) highlights growing concerns around AI data security, governance, and supply chain risk as AI adoption accelerates (3).

Fortinet’s 2026 Cybersecurity Skills Gap Global Research Report found that:

50% of organisations identify data privacy and information security as their primary concern when implementing AI.
45% worry about confidential data leaking through AI systems. (4)

Employees often use unapproved AI tools to improve productivity without understanding how those services process sensitive information. As a result, organisations increase their exposure to compliance, privacy, and cybersecurity risks.

AI Infrastructure Requires Stronger Protection

AI security extends beyond applications and users.

Many organisations now build private AI environments, deploy large language models (LLMs), and modernise data centre infrastructure to support AI workloads.

These environments require:

Network segmentation
Continuous visibility
Strong policy enforcement
Consistent governance

Without these controls, organisations expose sensitive information and weaken operational resilience.

Glenn Maiden said:

“Organisations need to know what AI services are being used, what data is moving into those systems, and whether governance controls are aligned with business risk. Security teams need visibility across networks, endpoints, cloud, and data centre infrastructure to apply consistent controls and reduce exposure as AI adoption grows.”

AI Cybersecurity Threats Are Moving at Machine Speed

Cybercriminals increasingly operate at machine speed.

Fortinet’s 2026 Global Threat Landscape Report found that AI now accelerates reconnaissance, weaponisation, and attack execution. In many cases, attackers exploit newly disclosed vulnerabilities within 24 hours after exploit code becomes available. (5)

Threat actors continue using AI and automation to increase the scale of:

Phishing campaigns
Social engineering attacks
Reconnaissance activities

Although many attack techniques remain familiar, AI dramatically increases their speed and volume. Consequently, organisations must improve visibility and shorten response times.

Reducing AI Cybersecurity Threats with Strong Cyber Hygiene

AI strengthens cybersecurity, but it cannot replace foundational security practices.

Organisations should continue to prioritise:

Complete asset visibility
Rapid patch management
Network segmentation
Identity and access controls
Continuous monitoring of cloud and OT environments

AI helps security teams detect anomalies sooner, prioritise risk more accurately, and automate appropriate response actions. Nevertheless, strong governance and disciplined cyber hygiene remain the foundation of cyber resilience.

Glenn Maiden said:

“AI is becoming part of the operational fabric of cybersecurity. The organisations seeing the strongest outcomes are the ones aligning AI adoption with governance, visibility, and execution. Security strategies need to evolve alongside AI usage so businesses can improve resilience, maintain trust, and reduce operational complexity as environments continue to expand.”

References

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