91% of respondents see AI adoption as a priority, with vulnerability assessment and threat detection highlighted as key benefits. However, only 61% of respondents acknowledged that their organizations are in the planning or development stages of adopting AI and machine learning for cybersecurity. The survey results revealed a lack of awareness of the critical role of internal controls and governance policies when it comes to AI
Artificial Intelligence and Machine Learning (AI and ML) are an important part of the future of cybersecurity and cloud security. But how integrated are these technologies into cybersecurity functions currently? A recent survey conducted by Check Point and Cybersecurity Insider asked hundreds of professionals from various industries how they have used AI so far, how much of a priority it is for their companies, and how it has impacted their workforce.
Where does AI stand in cybersecurity now?
Several questions in the survey asked respondents about the status of AI in their organizations' cybersecurity plans as of today, including the extent to which it has been fully implemented and how that implementation is going. Their responses paint a picture of an industry that is moving slowly and cautiously, and perhaps not moving toward AI as some might expect. It appears that organizations are still evaluating the benefits and risks associated with AI and machine learning tools, and companies are moving carefully to establish strict best practices that comply with relevant regulations.
When asked to describe their organization’s adoption of AI and machine learning in cybersecurity, 61% of respondents described it as either in the “planning” or “development” stages – a significantly larger number than the 24% who rated it as “mature” or “advanced.” ” Additionally, 15% of those surveyed said their organizations had not applied AI and machine learning to their cybersecurity efforts at all. It is clear that while the benefits of AI in cybersecurity efforts are convincing many companies to start exploring its potential, few companies have fully embraced it at this point.
Another question in the survey became more specific, asking respondents “What (cloud) cybersecurity functions in your organization are currently being enhanced by AI and machine learning?” The answers are clear, with malware detection leading the way at 35%, followed by user behavior analysis and supply chain security. Further down the list, there are fewer organizations looking to use AI for security posture management or adversarial AI research. Beyond answers to the previously discussed question about the general state of AI, the data shows that individual applications of AI and machine learning in cybersecurity are still far from universal.
One reason AI adoption is not accelerating at a faster pace is the challenge of navigating a rapidly changing regulatory landscape. In these early days, laws and government guidance around AI and cybersecurity are still evolving. Businesses cannot afford to take risks when it comes to compliance and keeping up with these rapid changes can be complex and require significant resources.
How are organizations moving towards AI in cybersecurity?
Despite the slow and cautious adoption of AI in cybersecurity so far, it is almost universally seen as an important priority going forward, with 91% rating it as a priority for their organizations, and only 9% of survey respondents saying it is a low priority or not. A priority at all.
Respondents clearly see AI as promising to automate repetitive tasks and improve anomaly and malware detection, with 48% identifying this as the area with the most potential. Additionally, 41% view reinforcement learning for dynamic security posture management using AI as promising, which is especially interesting when compared to only 18% who currently use AI for this function. The excitement is palpable – but there are challenges in realizing this potential.
In addition to specific applications, participants were asked to identify what they considered to be the biggest benefits of integrating AI into cybersecurity operations. The most common answers included vulnerability assessment and threat detection, but cost efficiency was the least popular answer, at only 21%. Most likely, due to the prohibitive challenge of regulatory compliance and the cost of implementation, AI is not currently viewed as an important money-saving tool for most respondents.
Concerns and conflicting positions about artificial intelligence in cybersecurity
Additional questions in the survey provided insight into professional concerns and lack of clarity around some of the fundamentals of AI and cybersecurity. On the topic of the impact of AI on the cybersecurity workforce, it is clear that this is still an open question with no clear answers yet. 49% identified the new skills required by artificial intelligence, and 35% indicated redefining job roles. While 33% said the size of their workforce has decreased as a result of AI, 29% said the size of their workforce has actually increased. Applying AI to cybersecurity is clearly a work in progress, and although increased efficiency is a promise that may come true in the future, for now many companies have to hire more people to integrate new technology.
It is worth noting that there was a significant split in responses to the question: Do you agree with the following statement: “Our organization would be comfortable using generative AI without implementing any internal data quality controls and governance policies”? While 44% disagreed or strongly disagreed with this statement, 37% said they would agree or strongly agree. It is very rare to see such a large split on a question like this in a professional poll, and this split seems to indicate a lack of consensus – or perhaps simply a lack of awareness regarding the importance of internal controls and governance policies when it comes to AI. .
Checkpoint perspective
It is clear that AI plays a critical role in enhancing cybersecurity measures and asset protection, especially when integrated with our product suite, allowing us to automate repetitive tasks, improve threat detection and response, and provide significant value to customers. This technology will define the future of cybersecurity, and Check Point is positioned to help companies get the most out of it.
It is important to note that successful AI implementation requires thoughtful integration and governance. To see the combination of increased efficiency and accuracy that AI can deliver, our customers must carefully consider how they integrate AI into their existing systems and processes. Appropriate governance mechanisms are critical to ensuring that AI is used responsibly and effectively. Strategic consulting services will be in demand in the future for clients looking to implement AI in their businesses in the safest and most effective way.
Check Point Security Consulting leverages this expertise along with independent frameworks, such as NIST CSF, SABSA and Zero Trust Architecture, to provide consulting and assessment services to the company's global client community. He learns more.
