The Impact of AI on Cybersecurity

AI Powered Attacks

Attackers are using AI to automate reconnaissance, refine phishing campaigns and generate highly convincing synthetic media. Currently, 48% of organisations surveyed cited AI‑automated attack chains as their greatest ransomware threat, while 85% expressed concern that traditional detection tools are becoming inadequate against AI‑enhanced attacks.

Attackers are experimenting with prompt injection, model manipulation and context aware phishing generated by large language models. Deepfake audio, video and documents allow impersonation of colleagues, suppliers or executives with unprecedented realism. Combined with compromised credentials, these techniques bypass both technical controls and human verification.

The expansion of AI agents in enterprise workflows introduces additional exposure. Poorly configured or overly permissive agents can be manipulated to perform unintended actions, interact with sensitive systems or trigger automation at scale. This new class of AI driven operational risk blends human error with machine autonomy, creating vulnerabilities that did not previously exist.

AI Powered Defence

Despite its misuse, AI remains a powerful defensive force. Security teams are increasingly relying on behavioural analytics, anomaly detection and AI assisted threat intelligence to counter rapidly evolving threats. Modern detection platforms correlate endpoint, identity, cloud and network signals to identify malicious activity earlier in the kill chain.

Research into behavioural and graph-based analysis demonstrates significant improvements in detecting novel ransomware and polymorphic malware. Runtime analysis, unsupervised learning and temporal correlation provide additional capability beyond traditional approaches.

In 2026, the organisations that succeed will be those that combine AI enhanced detection with skilled human expertise. An agent assisted SOC, built on rapid correlation and automated triage, provides defenders with a speed advantage that adversaries cannot easily overcome.

Security of AI Systems

As AI becomes embedded in business operations, organisations must treat it as part of their security critical estate. Poor governance, weak access controls or unmonitored usage can lead to data leakage, unauthorised automation or unpredictable agent behaviour.

Secure adoption requires clear policies for data inputs, strict controls over who can use specific AI tools, continuous monitoring of AI agent behaviour and comprehensive logging to support incident investigation. Without this discipline, AI introduces systemic vulnerabilities that attackers can exploit with growing ease.