AI and the 2025 SIEM landscape: A guide for SOC leaders

Cybersecurity is experiencing an AI paradox. AI in the hands of adversaries helps them increase the scale and sophistication of their attacks. But AI in the hands of defenders is improving productivity, reducing mean time to detect (MTTD) and respond (MTTR), and bolstering overall security posture.

SIEM analyzes a wide set of data points and offers security teams a centralized view of their organization’s systems and overall security posture. Integrating AI tools into this process can refine, accelerate, and streamline data collection, workflow, and analysis.

When applied to SIEM workflows, AI is helping security teams relieve traditional burdens through the following capabilities:

• Faster analysis: AI in SIEM accelerates threat detection and response by automatically correlating vast amounts of security data, surfacing anomalous patterns, and enabling cybersecurity analysts to prioritize and investigate incidents faster.

• Alert distillation: AI reduces alert fatigue by filtering out false positives, prioritizing the most important threats based on risk levels and historical context.

• Workflow recommendations: AI generates suggestions for analysts on next steps during investigations, streamlining decision-making processes and generating context-rich summaries.

• SIEM content migration: AI facilitates the transition from legacy SIEMs to modern platforms by automating the conversion of existing detection rules and other content.

• Custom data integration: AI-driven tools can build custom data integrations in minutes as well as the necessary configuration to ingest data from any REST API. Seamless data ingestion now comes with minimal effort.

These capabilities drive security teams toward increased practitioner productivity, accelerated detection and response, and overall risk reduction.

SIEM solutions will ingest logs from applications, users, cloud workloads, networks, endpoints, and security software and hardware.

Normalization is the process of integrating diverse data sources into a common schema for standardized analysis.

A SIEM can streamline events across sources to detect patterns indicative of threats.

With real-time monitoring and alerting, security teams gain immediate visibility into suspicious activity, allowing for rapid incident response and containment. Alerts and notifications surface any anomalous patterns detected with an associated severity score for further triage and resolution.

SIEMs also provide robust reporting features to support regulatory compliance with frameworks like HIPAA, PCI-DSS, and GDPR. Dashboards offer real-time visibility into security data and incidents through customizable visualizations. These reporting tools not only help demonstrate adherence to standards but also enable continuous security posture assessment. They also help security teams meet regulatory requirements, such as GDPR, HIPAA, PCI-DSS, and ISO 27001.

A SIEM solution can be connected with tools like security orchestration, automation, and response (SOAR), cloud detection and response (CDR), endpoint detection and response (EDR), identity and access management (IAM), and threat intelligence platforms (TIP).

Facilitate alert triage, investigation, and remediation through built-in workflows or external SOAR platforms.

After collecting and normalizing logs that establish a baseline of normal organizational activity, SIEM correlation identifies anomalous patterns across events, which is key to detecting complex threats.

SIEM analyzes a wide set of data points and offers security teams a centralized view of the organization’s systems and overall security posture. Integrating AI tools into this process can refine, accelerate, and streamline data collection, workflow, and analysis.

Modern SIEM solutions are equipped with advanced features, such as: 

• AI-driven threat detection that uses machine learning models to identify sophisticated attacks 

• User behavior analytics (UBA) that establishes behavioral baselines for users and systems to identify anomalies indicating insider threats or account compromise

• Integration with SOAR platforms that allows for automated playbooks and response actions, accelerating incident resolution and reducing analyst workload 

• Integrations with XDR, endpoint, and cloud security that provide rapid response and threat mitigation

Older SIEMs can come with limitations, leading many teams to pursue SIEM replacement. These challenges include:

• High operational costs: Licensing, storage, and compute expenses can add up quickly with legacy SIEM vendors.

• Scalability issues: Older platforms can’t keep pace with modern data volumes and diverse IT environments.

• Integration hurdles: Legacy systems may not have readily available integrations with modern cloud-based security tools.

• False positives: A lack of context-aware analytics often results in an overwhelming volume of irrelevant alerts.

• Complexity: Configuration and tuning traditionally require specialized skills and extensive effort.

• Learning curve: Many organizations struggle to find and retain qualified analysts to manage SIEM operations.

AI-driven SIEM solutions accelerate threat detection by analyzing vast amounts of data in real time. These solutions correlate that data against the latest threat intelligence to spot new threat types and surface high-risk anomalies that might otherwise go unnoticed.

AI propels investigations, reducing dwell time. It surfaces relevant insights from the deluge of data generated by today’s ecosystems, helping analysts get answers quickly. 

Manual response to alerts can leave organizations exposed as security teams scramble to balance conflicting priorities. AI-powered SIEM enables guided responses and automated workflows against different threats.

Automated creation of data integrations, detection rules, dashboards, and reports streamlines adherence to regulations by making it easier to ingest data from critical applications, systems, and infrastructure — no matter how custom or complex.

SOC teams supported by AI in their SIEM can surface the alerts that matter most, easily import custom data types, and guide workflow suggestions. By doing so, teams have more time to focus on strategic initiatives.

AI-driven SIEMs empower analysts to identify threats more efficiently by acting as a threat hunter’s sidekick — it’s at-the-ready for natural language inquiries into events, data, and context and presents findings quickly and intuitively.

Continuous monitoring in security proactively provides the real-time status of your data from across your attack surface. This practice eliminates blind spots, empowers practitioners, and reduces risks.

AI embedded into SIEM helps security teams mitigate threats faster during investigation and response, enhancing cyber resilience.

By streamlining the onboarding of custom data sources and creating detection rules, dashboards, and reports, AI-driven SIEMs help organizations remain compliant.

By flagging unusual behavior from users with elevated privileges, SIEMs help security teams detect insider threats.

The travel industry and transportation logistics systems rely on complex digital infrastructure.

Bolt now protects its super-app and users with Elastic Security on Elastic Cloud, delivering unified data protection and operational efficiency. 

With Elastic, Bolt boosted data protection, reduced maintenance overhead by 75%, and enhanced user confidence, safeguarding millions of journeys while accelerating its move to scalable, AI-powered security in the cloud.

The cybersecurity industry depends on advanced monitoring systems to stay ahead of evolving cyber threats.

For example, when managed security services provider Proficio wanted to optimize its threat detection and response, it turned to Elastic’s AI-driven SIEM solution. By integrating Elastic Security and Elastic AI Assistant, Proficio gained real-time visibility and automated threat detection. This enabled a 34% reduction in investigation time, improved response times by 75%, and decreased false positives, leading to significant operational efficiency gains. As a result, Proficio saw a 60% growth in its business while reducing investigation costs to less than half a cent per alert, saving an estimated $1 million over three years.

Universities rely on flexible, cost-efficient security systems to protect vast and complex networks.

When the University of York needed a more agile and cost-effective SIEM, it turned to Elastic Security. With Elastic’s AI-driven detection and response capabilities, the university reduced query times from hours to seconds, streamlined licensing costs, and enabled its small team to do more with built-in automations and generative AI (GenAI)-powered insights.

Aerospace and defense contractors must meet strict security and compliance standards without sacrificing speed or scale.

When the Sierra Nevada Corporation (SNC) needed to bring its security operations in-house and scale to ingest 10x more data, it chose Elastic’s AI-driven SIEM. With Elastic Security, SNC cut query times from minutes to seconds, launched a revenue-generating managed service, and accelerated threat detection with powerful automation and anomaly detection all on a unified platform built for growth.

Security is essential to create secure and seamless customer experiences. The Hut Group (THG) protects millions of ecommerce customers by centralizing security with Elastic Security for SIEM, cutting response times by 60% and triage time in half.

With automation, machine learning, and searchable snapshots in Elastic Security, THG slashed storage costs by 60%, enhanced fraud detection, and improved customer experiences.

Financial institutions can use AI-driven SIEM to detect account takeover attempts and mitigate them in real time with UBA.

Hospitals, clinics, and insurance companies can use SIEM for HIPAA compliance to detect unauthorized access to patient records.