Organizations recognize the benefits of generative AI (GenAI) yet need help to implement the infrastructure necessary to deploy it, according to The Future of AI in IT Operations: Benefits and Challenges, a new report commissioned by ScienceLogic and conducted by Vanson Bourne.
Almost all organizations (99.7%) recognize generative AI/ML's potential to address IT monitoring, alerting, and response challenges, yet only 45% are actively exploring its implementation.
The report also found that 45% struggle to maintain up-to-date GenAI knowledge bases, while 40% face challenges ensuring database quality, likely due to incomplete IT estate monitoring.
The increasing complexity of IT environments and data proliferation is outpacing human capacity, necessitating a shift towards automated, intelligent capabilities that enhance visibility, streamline issue identification, and accelerate resolution times. This automation allows IT teams to focus on delivering cutting-edge business services in a competitive landscape while paving the way for GenAI implementation. These advanced AI systems provide context-aware insights and actionable recommendations, enabling proactive issue prevention and resource optimization. However, effective GenAI deployment relies on first successfully leveraging traditional AI/ML for IT operations (AIOps), forming a foundation for more advanced AI-driven innovations.
Additional report findings include:
Effective IT monitoring, a foundational component of AIOps, remains a challenge across organizations
■ 50% of organizations use multiple, disparate tools to monitor resources, resulting in data silos, longer incident response times, and a fragmented user experience.
■ 47% of surveyed organizations are unable to map all of their on-premises, cloud, and edge devices into a single business view, despite monitoring a large range of IT systems and services.
■ 39% of organizations are prioritizing the consolidation of IT monitoring tools, as creating a consolidated monitoring environment becomes a key strategic focus.
Organizations need comprehensive observability and clear data management to automate using AI/ML
■ 38% cite inability to monitor all IT resources as a barrier to AIOps adoption, highlighting the importance of a holistic IT estate view for effective AI implementation.
■ 39% struggle to automate complex repair workflows due to lack of critical context, exacerbating visibility challenges across the IT estate.
■ 50% acknowledge security concerns as a barrier to AIOps adoption, potentially addressable through proper data management and governance policies.
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