Understanding AI in IT Demands Transparency First
In today's rapidly evolving IT landscape, many organizations are grappling with the challenge of outdated asset management tools, leaving them flying blind in their own digital environments. This partial and often misleading asset inventory can have severe consequences when Artificial Intelligence (AI) models are deployed, leading to missed vulnerable devices, skewed performance insights, and failed automation scripts.
Before entrusting AI to manage IT infrastructure, it is crucial to first ensure that the infrastructure itself is visible. Unfortunately, many companies resort to using spreadsheets, legacy Configuration Management Databases (CMDBs), or vendor-specific discovery tools that do not communicate with each other, resulting in thousands of unknown, unmanaged, or orphaned assets.
To achieve true visibility in IT environments, multiple data sources must be combined, such as passive listening, API integrations, log analysis, endpoint telemetry, and network traffic. Eliminating orphaned and unmanaged assets from IT environments is a top priority to reduce operational and security risks.
Accurate asset data significantly improves AI observability in IT operations by providing a reliable, up-to-date, and structured foundation of what exists within the IT environment. This enables AI systems to understand the complete context—including devices, endpoints, workloads, users, cloud instances, and shadow IT—allowing for precise anomaly detection, dependency tracing, performance optimization, and proactive issue resolution.
There are key reasons why accurate asset data is critical for AI observability in IT operations. Enhanced visibility and context allow AI tools to detect vulnerable devices or potential points of failure, while proactive operational insights shift IT operations from reactive problem-solving to proactive management. Improved anomaly detection and predictive analytics, faster and more accurate decision-making, and support for intelligent automation are other significant benefits.
Real-time or near-real-time asset discovery should be the baseline for enterprise IT. Treating visibility as a foundational aspect, not an optional one, is essential for delivering on the promise of AI in IT. McKinsey reports that 72% of companies use AI in at least one function, but most still rely on outdated asset inventories. Building context for assets, including mapping them to their business functions, owners, dependencies, and lifecycle stages, is crucial.
The visibility challenge is a byproduct of the evolution of IT environments, which now span physical machines, virtualized workloads, multiple cloud platforms, Software as a Service (SaaS) apps, remote endpoints, edge devices, and containers. AI thrives on timely, structured, and trustworthy data that reflects current conditions, and in an IT context, this starts with understanding what's in the environment.
In conclusion, accurate asset data is the essential foundation for effective AI observability—without it, AI systems lack the necessary "visibility" and context to provide actionable insights, automate operations, and prevent disruptions in IT environments. As we move towards a more autonomous, predictive, and AI-assisted future in IT, it is crucial to start by illuminating the landscape we're asking AI to navigate.
- To ensure AI systems can effectively navigate and manage IT infrastructures, it's vital to first establish visibility through the use of modern data-and-cloud-computing technology that can consolidate various data sources such as passive listening, API integrations, log analysis, endpoint telemetry, and network traffic.
- In the evolving IT landscape, where IT environments now encompass physical machines, virtualized workloads, multiple cloud platforms, SaaS apps, remote endpoints, edge devices, and containers, the quality of asset data becomes critical for AI tools to provide accurate insights, automate operations, and prevent disruptions, thereby acting as the essential foundation for AI observability.
