FINAL WORD
developments in AI technology are taking its efficiency to the next level .
AI is evolving at an unparalleled pace , and this is driving momentum within its adoption . Despite the initial buzz around the technology , it is vital that organisations remain mindful of how they deploy AI and the regulations around its use .
To ensure AI use cases align with their strategic business goals , Chief Information Security Officers , CISOs must consider how they can find and resolve incidents whilst distinguishing transformation from hype . They need to keep tabs on the most noteworthy developments in the technology , including natural language processing , NLP , and how this can be effectively utilised to augment the analyst experience , rather than replace human roles .
AI holds the potential to boost efficiency in cybersecurity by helping security teams to detect attacks , and even preventing them from occurring . On top of mitigating attacks , the technology enables organisations to address some of the core cybersecurity challenges that threaten their business continuity including critical gaps in their resources and capabilities .
Implementing AI within a security strategy is a multi-layered process that depends on several key aspects . Machine Learning , ML , including User and Entity Behaviour Analytics , detects behaviour patterns and automation assists with response and remediation . Human analysts also continue to be essential in driving the entire process with their unique ability to provide the oversight and context that computer systems still lack .
Once organisations have established this foundation , they can start streamlining more efficient processes and maximising their cybersecurity investments . AI enhanced security solutions can enable organisations to achieve better business outcomes by :
Deploying a SIEM with integrated AI capabilities enables security teams to automate routine tasks , freeing up analysts ’ workloads and alleviating pressures felt by the cybersecurity skills gap . Activities including detecting vulnerabilities , monitoring network traffic , and installing security patches that were previously handled by the security team can be managed efficiently by AI-powered security tools .
A SIEM platform can differentiate between actual threats and normal behaviour . This results in fewer false positives , allowing security teams to focus on genuine threats .
Security teams can accelerate analyst workflows with AI-driven automation , delivering customised threat timelines , impact analysis , and natural language search for faster responses and decisions . Analysts benefit from advanced tools that assign risk scores , prioritising the highestrisk threats quickly and automatically . This ensures that the most pressing threats can be dealt with swiftly before they can cause irrevocable damage .
By consolidating log data from disparate systems , AI enhanced SIEM tools provide a centralised workflow that allows for real-time visibility across the environment . Deploying a powerful solution that combines ML , machine data intelligence , and search analytics helps reduce visibility gaps to ensure cyberthreats are not missed . In turn , analysts benefit from an easier way to collect and manage large sets of data , all in one place . On top of mitigating cyberattacks , SIEM platforms can also leverage AI to streamline the compliance process . AI tools enable organisations to reduce the burden of assuring and demonstrating regulatory compliance , deploy prebuilt reports for audit and management review , and detect compliance violations automatically and in real time . This reduces the effort spent on setup and correlating multiple , identical alarms across frameworks .
Achieving successful outcomes will require organisations to align their AI strategy with their business and security objectives . By combining AIdriven security solutions with human insights , organisations can build futureready processes to effectively address their biggest challenges and maximise SOC efficiency . •
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