Artificial intelligence (AI) is rapidly evolving beyond its traditional role as a support tool. While earlier AI systems primarily generated content, analyzed data or assisted with decision-making, a new generation of technology—known as agentic AI—is capable of independently planning, executing and adapting complex tasks with minimal human involvement.
This advancement has significant implications for cybersecurity. As AI systems become more autonomous, cybercriminals can leverage these capabilities to conduct attacks faster, more efficiently and at a much larger scale. At the same time, many cybersecurity frameworks were designed to defend against human-driven threats, creating new challenges for organizations as the threat landscape continues to evolve.
What Is Agentic AI?
Agentic AI refers to systems that can make decisions, take action and adapt their behaviour with limited human oversight. Unlike traditional generative AI, which responds to prompts and produces outputs, agentic AI is designed to actively pursue objectives and adjust its approach based on results.
These systems often combine multiple technologies, including large language models, software tools, automated workflows and feedback mechanisms that allow them to learn from outcomes and refine future actions.
In a cybersecurity context, this means AI can move beyond assisting threat actors and begin performing many attack-related tasks independently.
How Cybercriminals Are Using Agentic AI
The rise of agentic AI is creating new opportunities for cybercriminals to automate and scale malicious activities.
Faster network infiltration
Agentic AI can rapidly analyze network environments, identify vulnerabilities and attempt to gain access to sensitive systems. Once inside a network, it may be able to move between systems, escalate privileges and locate valuable data with limited human direction.
More sophisticated phishing attacks
Traditional phishing campaigns often rely on generic messaging sent to large numbers of recipients. Agentic AI can create highly personalized attacks by gathering information from public sources and tailoring communications to individual targets. These messages can become increasingly convincing and effective.
Manipulating AI systems through data poisoning
Cybercriminals may attempt to influence AI-driven processes by introducing false or misleading information into a system’s data or memory. Over time, this can alter how AI tools behave and potentially lead to fraudulent transactions, incorrect decisions or compromised operations.
Launching attacks at a greater scale
Agentic AI allows threat actors to automate multiple attack activities simultaneously. This increased speed and volume can make incidents more difficult to detect, contain and respond to before damage occurs.
Why Traditional Defences May Not Be Enough
Many cybersecurity controls were developed to identify known threats and respond to attacks initiated by human actors. Agentic AI changes this dynamic by enabling attacks that can adapt, learn and operate continuously.
As a result, organizations may find that traditional security measures alone are no longer sufficient. Defending against AI-driven threats requires a more proactive approach focused on monitoring behaviour, limiting access and strengthening resilience across the organization.
Steps Organizations Can Take
To prepare for increasingly autonomous cyber threats, businesses should consider several key risk management strategies.
Strengthen network segmentation
Dividing networks into smaller, isolated environments can help limit attackers’ movement and reduce the potential impact of a breach. Combining this approach with zero-trust principles ensures that all users and systems are continuously verified before gaining access.
Adopt behaviour-based threat detection
Traditional antivirus solutions remain important, but organizations should also implement tools that monitor for unusual activity and behavioural anomalies. These systems can help identify emerging threats that may not match known attack signatures.
Review AI tool permissions regularly
Organizations using internal AI systems should ensure those tools have access only to the resources required to perform their intended functions. Limiting permissions reduces the risk of misuse or exploitation.
Update incident response plans
AI-driven attacks can unfold much faster than traditional cyber incidents. Incident response plans should be reviewed regularly and tested through exercises that include scenarios involving compromised or manipulated AI systems.
Evaluate cyber insurance coverage
As AI-related risks continue to evolve, organizations should review their cyber insurance policies to understand how AI-enabled incidents are covered and whether additional coverage is necessary.
Agentic AI represents a significant shift in the cybersecurity landscape. While these technologies offer substantial benefits across many industries, they also provide cybercriminals with powerful new tools that can increase the speed, scale and sophistication of attacks.
Organizations that proactively strengthen their cybersecurity frameworks, update response strategies and address emerging AI-related exposures will be better positioned to manage risk and maintain resilience in an increasingly automated threat environment.
For more guidance on cyber risk management and emerging technology exposures, contact our team today.