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AI can make some cyberattacks faster and easier to carry out, especially reconnaissance and social engineering. That can give less-skilled threat actors more leverage, but it does not make every advanced operation accessible to novices. Organizations should strengthen identity and access controls, train staff to verify sensitive requests, govern workplace AI use, and bring in specialist expertise where needed.
How AI is changing the threat
The UK National Cyber Security Centre (NCSC) assessed that AI would almost certainly increase the volume and impact of cyberattacks over its two-year assessment period. It identified reconnaissance and social engineering as areas where AI can improve an attacker’s work, and said the technology lowers barriers for novice actors conducting access and information-gathering operations. The NCSC also cautioned that more sophisticated uses are likely to remain concentrated among actors with the necessary expertise, resources, and quality data. These are the NCSC’s dated assessment, not a guarantee that every attack will become more effective: NCSC assessment of AI’s impact on cyber threats.
Microsoft Threat Intelligence has documented malicious uses that include drafting phishing lures, translating content, summarizing stolen data, generating or debugging malware, and scaffolding scripts or infrastructure. In the activity it describes, human operators still control objectives, target selection, and deployment decisions. Microsoft characterizes experimentation with agentic AI as early and limited by reliability and operational risk; it has not observed such activity at scale: Microsoft Threat Intelligence on threat actors’ use of AI.
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Four ways organizations should respond
1. Apply zero-trust principles to identity and access
Use least privilege: give each employee, service, and workload only the access needed for its task, and review whether that access remains necessary. Require strong identity controls, scope permissions carefully, and limit access to sensitive systems rather than assuming that being on a corporate network makes a user trustworthy. These measures can reduce the damage an attacker can do with a compromised account and make lateral movement harder.
Unit 42 analyzed more than 680,000 cloud identities in 2026 and found that 99% had excessive permissions; some permissions had gone unused for 60 days or more. That is Unit 42’s analysis of cloud accounts, not a universal estimate for all organizations, but it illustrates why permission reviews and identity hygiene deserve attention: Unit 42’s 2026 incident response report.
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2. Train employees to verify high-risk requests
Awareness training should address how convincing, well-written messages can still be fraudulent, but training alone is not a reliable control. Establish a process for verifying sensitive requests through a separate, known channel before acting. Unit 42 specifically recommends out-of-band verification for requests such as wire transfers, credential resets, or remote hiring. For example, staff should use an independently verified phone number or an established internal process—not contact details supplied in the request itself.
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Unsanctioned AI use can expose sensitive information or create security and compliance risks. Set clear rules about which tools employees may use, what data they may enter, and which tasks require approval. Microsoft describes enterprise measures that include discovering AI-related risks, maintaining visibility into AI assets, logging activity, and governing access and data. Pair policy with practical visibility and controls so employees can use approved tools without putting protected information into unmanaged services.
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4. Work with AI and cybersecurity specialists where capability is limited
Organizations do not need to build every capability in-house. Security professionals can help assess AI-related risks, review identity and data controls, and fit new monitoring into existing response processes. Sherrod DeGrippo, Unit 42’s vice president of threat intelligence, told ZDNET, in an article republished by Yahoo Tech: “CISOs need to think about what their agentic AI strategy is, top to bottom.” Treat that as a prompt to plan for AI use across the organization, not as evidence that agentic attacks are already common.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to prioritize the work
Start with the controls that reduce the consequences of a likely compromise: review access to sensitive systems, close unnecessary permissions, and make sure known vulnerabilities are addressed. Then formalize verification for high-impact requests and set enforceable rules for employee AI use. When comparing possible controls or outside help, consider:
- Which risk or workflow the control addresses.
- How it limits access or exposure of sensitive data.
- Whether it fits existing identity, logging, and incident-response processes.
- How staff will monitor and validate that it works.
- What expertise and ongoing effort are required to operate it.
AI may increase the speed or reach of existing attack methods, but the available evidence does not show that it has made sophisticated cyber operations routine for novice attackers. A proportionate response combines prevention, identity and access discipline, verification, visibility into AI use, and specialist support where internal teams need it.
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