According to a new Armis study, AI is at the top of the minds of the majority of IT leaders when it comes to the digital dangers that their companies might encounter.
Nearly three-quarters ( 74 % ) of respondents reported that pose a serious threat to their organization’s security. A similar share ( 73 % ) stated that they specifically feared that nation-state hackers ‘ AI might enable more sophisticated cyberattacks in the future.
The company polled more than 1800 worldwide IT decision-makers in its .
Russia’s use of AI in its cyberattacks strategies and China’s DeepSeek AI design are two cases of threats that are mentioned in the report.
Additionally, nearly two-thirds ( 64 % ) of IT leaders concur that generative AI ( GenAI ) poses a threat to smaller, non-state actors as near-peer cyber threats.
Nation-state players have been spotted using cyber-offensive AI in five effective ways, according to Armis Labs:
- Automated ransomware creation: AI-generated malicious code can automatically change to deceive itself.
- AI-driven hacking: AI-driven hacking increases the potency of social engineering schemes.
- Deepfake deception: AI-generated media deceives the general public and undermines trust in electronic communication.
- Automated system episodes: AI-powered tools consistently perform security checks and carry out attacks without the need for human intervention.
- AI attack advice: AI-based tools to identify the most likely locations to be attacked ( for example, vulnerability exploits ) without having detection in place
A Force for Good, as well as AI.
Despite those worries, 77 % of respondents also claimed that their organization had taken steps to prevent and stop AI-powered attacks.
Also, many of them are optimistic about AI’s ability to better defend themselves, aiding them in a number of crucial protective tasks, such as:
- Behavioural research: AI looks for patterns in user behavior to point out possible intrusions.
- Automated risk hunting: AI constantly searches for fresh attack vectors, indicators of offensive behavior, and indicators of sacrifice
- AI enables real-time adjustment of safety adjustments in response to emerging threats.
- Exploitation diagnosis: Machine learning algorithms identify application vulnerability exploitation.
- detection of techniques, tactics, and procedures ( TTPs ): Machine learning models can identify variations in typical system components that perform tasks other than normal ones.
- New system detection: When new operating technology ( OT ) systems, Internet of Things ( IoT ) applications and applications come online in a risky environment, machine learning models can detect this.
- Get assets with poor visibility and are not adequately protected by presence gap analysis.
- Defense advice: Identifying a menace and implementing a mitigation strategy based on relevant defensive capabilities
Anxiety of Geopolitics-related Escalating Cyber Tensions
Over 87 % of IT decision-makers are generally concerned about the effects of cyberattacks on their businesses, excluding AI. ” A significant change from previous information,” Armis said.
Just over half ( 54 % ) of IT leaders surveyed in 2024 stated they were concerned about the effects of cyberwarfare.
The Armis record notes that” a significant factor is the increase in political confusion, fueled by armed conflicts and a tectonic shift in the 2024 election cycle, in which every governing party in a developed country lost voting share.”
Finally, 75 % of IT officials surveyed say they anticipate that more and more institutions that support free press and independent thought will be targeted by cyberwarfare problems.