Organizations face persistent visibility gaps across cloud, hybrid, IT, and OT environments, leading to exploitable vulnerabilities.
Data silos and lack of cross-team collaboration hinder effective security operations, with 52% citing data silos as a major concern.
Budget pressures intensify as organizations must fund AI initiatives without increased resources, creating a "perfect storm" for cost control.
Shadow AI emerges as different departments independently pursue AI solutions, increasing the need for governance and standardization.
AI governance, standards, and frameworks are becoming critical to manage proliferation and ensure responsible use.
Nearly 60% of SOC leaders spend more time managing fragmented security tools than responding to threats.
Alert overload and low signal fidelity cause analyst fatigue and slow threat response, with almost half struggling to triage alerts.
Data management gaps, including silos and inconsistent access, slow investigations and increase breach risk.
Vendor complexity and outsourcing can create additional inefficiencies in incident response.
Burnout and "quiet quitting" among security teams are rising due to high workloads and alert fatigue.
AI is increasingly used to improve efficiency in alert triage, response, and onboarding new security talent.
Domain-specific AI is favored over generalized tools, but challenges like hallucinations and the need for skilled oversight remain.
Organizations are preparing for a shift toward autonomous agents handling triage and investigation, changing required skill sets.
Future security roles will focus more on governance, compliance, and building relevant detections rather than basic triage.
Regulatory compliance and supply chain security are growing priorities as threats and requirements increase.
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Splunk is a technology company that specializes in data analysis and monitoring. Their platform allows organizations to collect, analyze, and gain valuable insights from large amounts of data generated across various sources. Splunk's software enables businesses to search, monitor, and visualize data in real time. This in turn helps them to detect and address potential issues, improve operational efficiency, and enhance cybersecurity. With a focus on data-driven decision-making, Splunk's solutions cater to a host of different customers within various fields, including IT, security, finance, healthcare, and more.
Splunk was founded in 2003 with the idea to help organizations and businesses effectively utilize their machine-generated data. Originally focused on IT monitoring, Splunk quickly expanded its capabilities to become a leading provider of data analytics and monitoring solutions. By enabling businesses to derive actionable insights from their data, Splunk gained popularity and grew its customer base across industries. Over the years, Splunk has continued to innovate and enhance its platform, incorporating advanced analytics, machine learning, and artificial intelligence.
Splunk offers a comprehensive and scalable platform that helps organizations make sense of vast and diverse data sources. At the core of Splunk's platform is its data indexing and search technology, which allows users to collect, index, and analyze machine-generated data from various sources in real time. This data can be sourced from applications, servers, network devices, sensors, and more. Splunk's platform also provides advanced analytics capabilities, including machine learning and AI, to enable users to uncover hidden patterns, detect anomalies, and gain valuable insights from their data. Through their platform, Splunk enables organizations to turn their data into actionable intelligence, improve operational efficiency, and drive informed decision-making. Some notable customers and users of Splunk’s platform include names such as ManpowerGroup and Carrefour.
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