Generative AI is transforming the digital world — creating content, code, designs, and even mimicking human voices and behaviour. While this evolution brings tremendous value to businesses, there’s a dark side emerging fast. In 2025, these advanced tools are not only empowering productivity but also arming cybercriminals with sophisticated attack capabilities.
For CISOs (Chief Information Security Officers), this presents a new set of risks that go far beyond traditional cybersecurity challenges. From deepfake fraud to AI-enhanced phishing campaigns, generative AI poses complex, high-impact threats that every security leader must address.
What Is Generative AI?
Generative AI refers to artificial intelligence systems capable of creating content such as images, text, audio, video, and code. Examples include ChatGPT, DALL·E, Midjourney, and Google’s Gemini. These tools are trained on vast datasets and use machine learning to generate realistic outputs based on user prompts.
While generative AI is revolutionising sectors like healthcare, media, and software development, it is also giving cybercriminals powerful tools to deceive, manipulate, and breach systems with alarming efficiency.
The Growing Threat Landscape in 2025
1. Deepfake Attacks
Deepfakes are AI-generated audio or video content that convincingly mimics real individuals. In 2025, deepfake technology has become incredibly realistic and accessible. Attackers now use it to impersonate CEOs or public figures in video calls and voice recordings, often tricking employees into transferring funds or revealing sensitive data.
Real-world risk: A finance officer in a London-based firm receives a video call from a “CEO” instructing a money transfer — and it’s entirely fake.
2. AI-Powered Phishing Campaigns
Generative AI enables cybercriminals to craft near-perfect phishing emails and messages. Unlike older scams riddled with spelling errors, these messages now sound natural, personalised, and timely.
Example: An employee receives a well-written message from “IT support” warning of a security breach and requesting login credentials — the message is AI-generated and indistinguishable from a legitimate one.
3. Synthetic Identity Fraud
Generative AI can be used to create entirely fictitious but believable identities. These synthetic profiles are then used to apply for loans, open accounts, or infiltrate organisational networks.
Why it matters: Businesses may unknowingly onboard a fake identity as a vendor, contractor, or employee.
4. Automated Malware Creation
Tools like code-generating AI models can assist attackers in building and modifying malware. While responsible AI tools like ChatGPT restrict harmful use, open-source models and dark web variations do not.
Risk Factor: Attackers can generate polymorphic malware that changes its code structure on each execution, making it harder to detect using traditional antivirus systems.
5. Misinformation and Reputation Damage
Generative AI makes it easier to spread fake news, images, or videos about an organisation. In politically sensitive or regulated sectors like finance or healthcare, a single false claim can cause irreparable damage.
CISO Insight: Crisis response plans must now include protocols for handling AI-generated misinformation.
Implications for CISOs and Security Teams
As the use of generative AI in cybercrime grows, CISOs must expand their threat models to include these new attack vectors. Traditional defences such as firewalls, antivirus, and intrusion detection systems are no longer enough.
Key CISO Priorities in 2025:
- Update Security Awareness Training
Employees must be trained to recognise deepfakes, AI-generated emails, and suspicious content that may appear legitimate. - Invest in AI-Detection Tools
Emerging technologies can detect deepfakes, synthetic audio, and unusual patterns in communication. - Reinforce Identity Verification Protocols
Implement multifactor authentication, voice recognition, and video call validation tools for critical tasks. - Review Third-Party Risk Management
Ensure all vendors and partners are assessed for generative AI vulnerabilities. - Develop AI-Specific Incident Response Plans
Include generative AI threat response scenarios in tabletop exercises and incident playbooks.
Regulatory and Legal Considerations
In the UK and across Europe, data privacy regulations are beginning to account for AI-related risks. However, legislation is still catching up with the rapid development of generative tools.
CISOs should:
- Monitor developments in AI regulation, such as the EU AI Act.
- Ensure data used in AI applications aligns with GDPR and local compliance requirements.
- Work with legal teams to understand liabilities if deepfake or synthetic content is used to attack their organisation or customers.
Generative AI Used by Defenders: A Double-Edged Sword
It’s important to note that while attackers use generative AI maliciously, defenders can leverage it too. From automated threat detection to intelligent response systems, AI helps boost security operations.
However, overreliance on these tools can lead to blind spots if not monitored carefully. CISOs must maintain human oversight and apply strict governance around their internal use of generative AI.
Final Thoughts
In 2025, the dark side of generative AI is not just theoretical — it’s already here. CISOs must urgently adapt their cybersecurity strategies to this new frontier of threats. The rise of deepfakes, synthetic identities, and AI-assisted attacks requires a rethink of trust, verification, and defence mechanisms across organisations.
Whether operating from London or elsewhere in the UK, businesses must act now. The speed, scale, and realism of AI-generated threats will only grow — and those who ignore them risk being caught unprepared.
Need Help Understanding Generative AI Risks in Your Organisation?
Talk to the Cybersecurity experts at Gradeon Limited — helping UK businesses stay compliant, secure, and ahead of emerging threats.
