ServiceOps: Unleashing a new AI agent to reduce change failures in complex systems

Agentic AI promises to transform enterprise IT work. For CIOs and IT leaders, this means improved operational efficiency, data-driven decision making and accelerated innovation. Agentic AI’s ability to assess changing conditions in service operations (ServiceOps) and proactively recommend steps to reduce change failures sets the technology apart from traditional AI and automation tools.

But before we explore the potential impact of agentic AI on ServiceOps, let’s look at the change approval process in most large enterprises. Traditionally, the manager from the change advisory board (CAB) coordinates the teams and stakeholders, makes final decisions to approve or reject proposed changes, and directs the implementation of changes.

However, the DevOps teams that release new features constantly within the same organization don’t go through the traditional change approval process. DevOps may push thousands of changes daily, and the CAB process is simply too slow. DevOps teams follow their own practices of using continuous integration and continuous deployment (CI/CD) tools to automatically merge code changes and automate testing steps to deploy changes more frequently and reliably.

The lack of a single approach to delivering changes increases the risk of introducing bugs or performance issues in production. When change occurs, organizations often lack the visibility and understanding of the change’s impact on the organization’s IT ecosystem.

With the complexity of modern business operations and the accelerated pace of change driven by DevOps, organizations face a growing demand for a simpler way for IT service and operations teams to balance speed and risk.

Agentic AI and the new AI agent

Some of the most exciting capabilities of agentic AI are its ability to interact with a wide variety of tools and data, generating insights, and executing tasks in a proactive manner. Imagine an AI agent specifically designed to guide change management and DevOps teams to deploy system and software changes more rapidly and reliably. The AI agent proactively identifies risky changes by analyzing operations and service management data together, providing a change risk score, summarizing the insights, and recommending best actions — all in one place. With this information, teams can ask the AI agent additional questions such as “Should I approve the change?” or “Can I look at similar changes?” Using an AI agent, the CAB and DevOps teams get the answers needed to confidently determine the next best actions.

For example, when a database upgrade is requested, the Change Risk Advisor AI agent within BMC Helix AIOps gathers historical operations and service data relevant to the database service, helping IT teams understand the risk of deploying the change. The Change Risk Advisor AI agent combs through past situations or problems and assesses the current service health status to recommend the best actions.

If further due diligence is recommended, change management or DevOps teams can interact with the AI agent to ask further questions like “Who is the change owner?” or “Can I look at change collision?” Visibility into the real-time deployment landscape and additional context around the change enables both the CAB and DevOps teams to collaborate and apply better actions that reduce change failures.

GenAI and agentic AI: The future of ServiceOps

Generative AI (GenAI) and agentic AI play a powerful role in ServiceOps. When used to complement predictive and causal AI, service and operations teams can use AI-based risk assessment for changes. BMC ServiceOps offers a new operating model for accelerating change while predicting and managing risk across the enterprise.

By integrating data and workflows between ITSM and AIOps tools, the BMC HelixGPT Change Risk Advisor agentic AI agent enables smarter, data-driven decision making. With agentic AI, CAB and DevOps teams get:

  • Insights and recommendations throughout the entire change process
  • Proactive change risk predictions for all changes
  • Reduced outages caused by high-risk changes
  • Accelerated change deployment without change anxiety
  • Higher success rates by lowering change failures

Moving forward

We’re in a new era of AI service operations and management. BMC Helix is already paving the path for successful outcomes with BMC HelixGPT, an agentic system integrated into the BMC Helix Platform that powers ServiceOps.

Discover how agentic AI can simplify change management and transform ServiceOps into a proactive force that improves business results in your organization. Visit here for more information or contact BMC.



Source link

Leave a Comment