As artificial intelligence (AI) and machine learning (ML) continue to transform entire industries, organizations increasingly need robust governance and visibility into these powerful technologies. While traditional Configuration Management Databases (CMDBs) often tracked servers, network equipment, and application software, they did not always capture the nuanced nature of AI/ML components, such as specialized hardware or cloud-based inference services. Recognizing this gap, ServiceNow recently introduced new CMDB classes specifically designed to reflect the evolving AI and ML ecosystem. By taking advantage of these updates, your organization can establish a clearer picture of how AI-driven workloads operate - and ensure they are aligned with your broader IT service management goals.
Historically, CMDBs were built around physical servers and software installations. However, AI/ML workloads introduce complexities that go well beyond standard compute resources. Models rely on large datasets, specialized processing units, and sometimes ephemeral cloud-based services that make traditional asset tracking feel inadequate. This can lead to fragmented visibility, ambiguous ownership, and inefficient change management processes when dealing with AI systems.
ServiceNow’s latest CMDB enhancements address these challenges head-on. By adding specialized classes that capture the unique attributes of AI/ML applications and hardware, the CMDB now does a better job of describing modern workloads and their underlying relationships. Rather than treating AI resources as standard servers or generic software, these new classes enable organizations to track the exact nature of AI/ML processing—right down to the GPU details or cloud-based function endpoints.
One of the most significant developments in ServiceNow’s CMDB is the introduction of classes that speak directly to AI and ML environments. Each class focuses on a different facet of AI/ML operations, ensuring a comprehensive way to document—and manage—your intelligent services.
To obtain these class updates, visit the ServiceNow Store for the latest “CMDB CI Class Models” (v1.68.0 or newer)
The new classes not only make it easier to describe AI/ML assets in the CMDB but also provide more meaningful relationships between these assets. This is especially valuable for:
To fully leverage ServiceNow’s updated CMDB, start by identifying the AI/ML resources currently in your organization. Map out who owns each piece of the puzzle—hardware, models, data pipelines, and cloud services—and then align these items with the new classes. If, for example, your data scientists rely heavily on GPU-accelerated clusters, make sure all relevant GPU details (e.g., memory, core count) are captured under cmdb_ci_gpu. If your application uses AWS or Azure-based AI services, catalog those endpoints under cmdb_ci_function_ai to maintain a record of where cloud-based inference is happening.
Automation is often key to keeping this information fresh. As AI/ML environments evolve, new containers spin up, GPUs get redeployed, and subscription tiers for cloud services change. Consider using ServiceNow Discovery or custom integrations to automatically sync updates back into the CMDB. This reduces the administrative burden on your teams and helps ensure that the CMDB remains an accurate reflection of reality.
Equally important is weaving AI/ML configuration management into your existing governance and operational processes. Anytime a production model changes, or a new GPU is purchased, relevant stakeholders—such as data science leads or finance managers—should be notified. By making these steps part of your day-to-day workflows, you’ll avoid the common pitfall of treating the CMDB as an afterthought, updated sporadically and inevitably falling out of date.
ServiceNow’s new CMDB classes are not just a tactical tool for better asset tracking; they also serve as a strategic foundation for navigating the AI-powered future. As your organization’s AI footprint expands to encompass advanced analytics, natural language processing, and edge computing use cases, having a well-structured CMDB ensures that you’re not caught off-guard by complexity.
You’ll be able to answer critical questions - such as how data compliance obligations differ by AI environment or where to allocate budget for GPU upgrades - and you’ll do so with accurate, real-time information. By grounding these decisions in a CMDB that reflects AI and ML as first-class resources, you’ll foster collaboration between IT teams, data scientists, and business leaders who all rely on consistent data to guide their actions.
With ServiceNow’s latest CMDB updates, organizations can bridge the gap between traditional configuration management and the specialized demands of AI/ML. By accurately tracking these new classes of CIs, you create a unified environment where all stakeholders can see the dependencies, costs, and compliance implications tied to AI initiatives. More importantly, you lay the groundwork for responsible, scalable growth in the face of what is likely to be an even more AI-centric future.
If your organization wants to harness the full power of AI while maintaining clarity and control, embracing these CMDB enhancements is an essential next step. Until you're ready though, you can revolutionize your traditional CMDB management practices using AI. Our CMDB AI Advisor app on the ServiceNow Store provides real-time snapshots and intelligent historical analysis into your infrastructure. Gain instant insights into configuration items and their statuses, empowering your team to make informed decisions and maintain peak system performance.