Are Businesses Prioritizing AI in Cybersecurity?

A recent survey by Check Point reveals a cautious yet promising approach to AI in cybersecurity, highlighting the industry's regulatory hurdles and implementation challenges.

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  • [Image source: Krishna Prasad/MITSMR Middle East]

    Artificial Intelligence (AI) and Machine Learning (ML) are crucial to the future of cyber security and cloud security. But how are these technologies integrated into cyber security functions? 

    Adoption is slow; however, AI is almost considered a critical priority for future cybersecurity efforts.

    According to the Check Point 2024 Cloud Security report, 91% of organizations prioritize adopting AI and highlight vulnerability assessment and threat detection as the key benefits. However, 61% of respondents also acknowledged that their organization is in the planning or development phases of adopting AI and ML for cybersecurity.

    The survey reveals an industry proceeding cautiously. Only 24% described efforts as “maturing” or “advanced,” and 15% have yet to implement these technologies. This cautious approach highlights the industry’s ongoing evaluation of AI’s benefits and risks and the development of best practices that comply with evolving regulations.

    The survey results show a preference for certain applications when examining specific AI-enhanced cybersecurity functions. Malware detection leads to 35%, followed by user behavior analysis and supply chain security. Conversely, fewer organizations use AI for security posture management or adversarial AI research. 

    A significant barrier to faster AI adoption is the complex and shifting regulatory landscape. Businesses are cautious, striving to maintain compliance amid evolving laws and government guidance on AI and cybersecurity. The resource-intensive nature of regulatory compliance adds another layer of complexity, slowing down the adoption process.

    As the regulatory landscape evolves, businesses must navigate these changes carefully to harness AI’s full potential in securing their digital futures.

    According to the report, about 48% of respondents recognize AI’s role in automating repetitive tasks and enhancing anomaly and malware detection as holding the most potential. Reinforcement learning for dynamic security posture management also shows promise, with 41% seeing potential in this area, although only 18% currently use AI.

    Respondents identified several key benefits of integrating AI into cybersecurity operations, including vulnerability assessment and threat detection. However, cost efficiency was a less popular response, likely due to the high costs associated with regulatory compliance and AI implementation.

    The survey revealed concerns and uncertainties regarding AI’s impact on the cybersecurity workforce. While 49% of respondents noted that new skills are required, and 35% observed redefined job roles, there was a split regarding workforce size changes due to AI, with 33% reporting a reduction and 29% noting an increase. This indicates that while AI promises greater efficiency, its implementation is still a work in progress, often requiring additional hires to integrate the new technology.



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