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Modernizing IT Operations with AIOPS: A Comprehensive Guide

Rashid Qureshi Posted On May 5, 2025
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AIOps professional working at a computer with vibrant graphic user interface and coding tools in a modern office setting.

At Lumen, we operate one of the world’s largest and most connected networks. To manage this vast infrastructure efficiently, we leverage Artificial Intelligence for IT Operations (AIOps). AIOps uses AI and machine learning (ML) technologies to automate and enhance IT processes, enabling us to analyze large volumes of data, detect anomalies, predict issues and automate responses. This approach helps us maintain high levels of operational efficiency, reduce downtime and better serve our customers.

In this post, we outline our six-step AIOps framework, which is designed to modernize IT infrastructure operations. Drawing from our extensive implementation experience, we will provide insights into each step of the framework and explain how it can help your organization achieve similar benefits.

A Six-Step Strategy for Simplified Network Management

Deploying a large-scale IT network infrastructure involves challenges like managing fragmented data silos, ensuring security and compliance and integrating diverse systems. These obstacles are often compounded by the need for scalability, cost efficiency and skilled staff. To overcome these issues, many large enterprises turn to centralized management platforms with unified interfaces. These platforms are essential for providing operational efficiency, business agility and competitive advantages by streamlining processes and improving visibility across the entire IT environment.

Recognizing the complexities of today’s enterprise IT operations, Lumen developed a comprehensive framework for AIOps that highlights six essential steps necessary for an effective AIOps strategy, as illustrated in Figure 1.

A flowchart titled AIOps Strategy Development Steps consisting of six steps arranged horizontally from left to right, each step represented by an orange circle with a number inside it and accompanied by descriptive text: 1. Evaluate the current state of the operational environment, 2. Define business objectives and technical requirements, 3. Understand organizational and technical challenges, 4. Assemble a cross-functional team, 5. Develop architecture and automation process flow and 6. Implementation. The steps are connected by arrows indicating the sequence.Figure 1: AIOps strategy development steps

Step 1: Perform a current state analysis

Modernization projects often encounter challenges with current state documentation. These can include data governance, incident reporting, change management, CMDB (Change Management Database) data quality, applications, tools and integration. This is why it is crucial to comprehensively document processes, infrastructure and data.

You will also need to assess the current IT infrastructure, including hardware, software, applications, network configurations and cloud services, to understand its capabilities and limitations. Evaluate all data sources, including logs, metrics, events and performance data from various systems, as integrating data from all sources will be essential to achieving your desired outcomes.

Step 2: Align with your business objectives and technical requirements

After analyzing your IT infrastructure, it is important to align your findings with your business goals and technical needs to ensure focused and effective modernization.

Your primary objective should be to improve the overall customer experience for both employees and end customers, followed by secondary goals such as enhancing efficiency, reducing costs, decreasing mean time to resolution (MTTR), improving service quality, fostering agility and innovation, prioritizing strategic initiatives and automating compliance checks. Create a clearly defined and prioritized list of business objectives to serve as a guide for how technology can help you attain these goals. This strategy will strengthen business case development, encourage stakeholder alignment and assist in securing project funding.

Technical requirements are crucial for managing a complex IT environment built over many years with diverse hardware, software, applications and data. This environment centers on vast, fast-moving and varied data that is often underutilized for insights. We recommend that you start by assessing your current business processes and how they integrate with existing tools and applications.

Potential technical requirements can include:

  • Data lake architecture
  • Algorithm customization
  • Automated incident resolution
  • Human escalation workflows
  • Performance benchmarking
  • Vendor compatibility
  • Scalable data platform

With your business objectives and technical requirements clearly defined, the next step is to identify and address any organizational and technical challenges that could hinder your AIOps implementation.

Step 3: Define organizational and technical challenges

Large enterprises often encounter challenges such as misaligned workplace culture and resistance to change, along with complex ecosystems, a lack of skilled professionals, high initial investment costs, security and compliance complexity, and integration issues.

Signs of struggling IT operations can include poor data governance, data silos, alert fatigue, difficulty in root cause analysis, reactive issue resolution, skill gaps and integration and interoperability issues.

To transform operational support, you will need to thoroughly evaluate human resources and the skill sets needed for modernization. Your assessment will help you identify skill gaps and outline strategies for attracting new talent. Using the insights from your analysis, you can also create targeted training programs to reskill current employees and develop career pathways for operational staff, helping you achieve a balanced insourcing and outsourcing strategy.

Diagram illustrating the transformation of AIOps operations support. On the left side, there is an upright pyramid divided into three tiers labeled Tier 3, Tier 2 and Tier 1 from top to bottom. On the right side, there is an inverted pyramid labeled with three roles: Automation Engineers, Network Engineers and NOC. Between the pyramids are three orange arrows pointing from left to right, labeled Organization Change, Support Structure and Skillset Modification. Text at the bottom of the image reads Operational Support Transformation.

Figure 2: AIOps operations support transformation

When considering how to modernize your IT operations, you may need to decide between building vs. buying. Both alternatives present distinct advantages and challenges. Given the complexities of managing extensive infrastructures, we recommend a customized solution that integrates technologies from multiple vendors to create a tailored AIOps solution.

Once you have  a clear understanding of organizational and technical challenges, a cross-functional team can help drive the AIOps implementation forward.

Step 4: Assemble a cross-functional team

A key advantage of modernizing IT operations is that it enables all teams to use one data source for event correlation, automation, predictive analysis and collaboration. Establishing a cross-functional team is essential for several reasons. It ensures alignment across all business areas, from IT operations to executive leadership, and fosters a shared commitment to common objectives.

By incorporating diverse teams such as network engineering, DevOps, data science, security and application development, you can capitalize on a broad spectrum of expertise and perspectives. Teams can use a centralized Platform-as-a-Service (PaaS) architecture throughout development, boosting collaboration and standardization across projects.

Well-defined roles and responsibilities, as illustrated in the RACI matrix (Figure 3), help encourage accountability and streamline communication.

Cross-functional RACI matrix for different roles or teams within an organization related to AI and operations. The table has two main columns labeled Role/Team and Responsibilities, followed by four additional columns labeled R, A, C and I. The rows under Role/Team list various teams such as IT Operations, Network Engineering, DevOps, Data Science AI/ML Team, Security, Application Development, Service Desk, Infrastructure Management, Project Management Office (PMO), Business Analysts, Finance, HR (Human Resources) and Executive Leadership. Each team is associated with specific responsibilities listed in the second column. The RACI columns indicate the roles of Responsible (R), Accountable (A), Consulted (C) and Informed (I) for each responsibility.

Responsible (R): Those who do the work to achieve the task. Accountable (A): Those who are ultimately answerable for completion of the task. Consulted (C): Those whose opinions are sought. Informed (I): Those who are kept up to date on progress.

Figure 3:  AIOps Cross-Functional RACI Matrix

With a cross-functional team in place, it is time to create unified AIOps architecture and process flows to support your strategy.

Step 5: Develop AIOps architecture and process flow

Creating a unified service assurance architecture (Figure 4) lays the groundwork for operations and enables multiple teams to join the AIOps cross-functional project.

A diagram showing a multi-layered pyramid chart representing a unified AIOps architecture with functionalities such as RPA, automation and cybersecurity intelligence integrated into ServiceNOW. The layers from bottom to top are infrastructure environments, monitoring sources, data collection, event backbone, correlation and enrichment, service management and user engagement. To the right of these layers is a list of functionalities provided by this architecture: RPA and automation, config orchestration, operations intelligence, cybersecurity intelligence, and governance and compliance. At the top left corner is ServiceNOW, indicating that this architecture integrates with ServiceNOW. An orange arrow and the words AIOps engine to the left of the pyramid vertically span service management and correlation and enrichment layers.

Figure 4: Unified service assurance architecture

Establishing a cross-functional team and a unified architecture will help you develop an automation process flow (Figure 5). This will assist in connecting people, processes and technology, enabling team members to understand existing processes, identify areas of isolation and skill deficits, and visualize the improved workflow. By conducting this exercise, you can streamline processes and eliminate redundancies, enabling you to make well-informed decisions and consider all aspects of your IT environment.

Flowchart titled AIOps Automation Process Flow consisting of eight interconnected steps, each represented by a colored box with text inside. The steps are: 1.Data Collection and Ingestion, 2.Data Processing and Normalization, 3. Machine Learning Model Deployment, 4.Event Correlation and Analysis, 5.Incident Detection and Alerting, 6.Automated Remediation, 7. Visualization and Reporting and 8. Continuous Learning and Improvement.

Figure 5: Automation process flow for AIOps

When the architecture and process is established, the final step of the framework involves rolling out the solution.

Step 6: Implement pilot and scale for success

A measured implementation approach is vital to adopt AIOps successfully. Start with a small, manageable pilot phase to assess feasibility and gather insights.  Gradually expand the use of AIOps to other areas of your IT operations, using results from the pilot project to optimize the solution.

The final conceptual architecture (Figure 6) serves as the foundation for the end-to-end implementation.

Diagram illustrating the architecture of an AIOps system, showing the flow from data sources to automation orchestration. From left to right are Data Sources (including Logs, Metrics, Telemetry, and Configuration Management Database (CMDB), Data Collection Normalization represented by a database icon, Anomaly Detection (ML) depicted with gear icons on a human head, Data Correlation Causation illustrated with a bar chart and magnifying glass, Visualization Alerts shown with a computer monitor and alert symbol and Automation Orchestration illustrated with a gear on an orange background. This final step is connected by arrows to actions labeled Restart Device, Update Config, iOS Upgrade, Open Ticket and Custom Action. A section at the bottom is labeled Enterprise Systems and includes NMS (Network Management System), ITSM (IT Service Management), SIEM (Security Information and Event Management), CRM (Customer Relationship Management) and ERP (Enterprise Resource Planning). Arrows indicate the data flow between these components and processes. Data enrichment occurs between the Data Collection Normalization and Enterprise Systems stages.

Figure 6: Conceptual AIOps architecture

Your organization will now be poised to leverage the full potential of AIOps. By following these steps, you can seamlessly integrate AI-driven operations into your IT infrastructure.

Transform Your IT Operations with AIOps from Lumen

Lumen offers both expertise and tools to further transform your IT operations. Through our skilled AIOps implementations, customers have experienced significant improvements in operational efficiency, cost savings and overall service quality.

  • Service assurance: In 2024, our orchestration program achieved approximately 300 automated workflows in production. This resulted in around two million successful workflow transactions and saved or avoided approximately 500,000 resource hours in OPEX.
  • Automated diagnostics: Our automated diagnostics solutions achieved a 30% ticket deflection rate in 2024, leading to approximately $6.1 million in OPEX avoidance.

Your organization can achieve similar outcomes by working with our skilled professional services team. We can design and deliver a range of end-to-end services and solutions, including:

  • AIOps planning workshop: We conduct comprehensive workshops to understand your unique needs and develop a tailored AIOps strategy.
  • Network and infrastructure assessment: Our experts assess your current network and infrastructure to identify areas for improvement and optimization.
  • Network and infrastructure observability strategy, design and implementation: We design and implement observability solutions that provide real-time insights into your network and infrastructure, enhancing visibility and control.
  • Device discovery, data collection and CMDB integration: We automate the discovery of devices, collect relevant data and integrate it into your Configuration Management Database (CMDB) for better asset management.
  • Integration with third-party monitoring and management tools: We will facilitate seamless integration with your existing platforms such as SolarWinds, Splunk, LogicMonitor, and others, thereby augmenting their functionalities through AIOps capabilities.
  • Workflow automation and integration with enterprise systems: We automate workflows and integrate them with your enterprise systems, streamlining operations and reducing manual effort.
  • Visualization and reporting: We provide advanced visualization and reporting solutions that offer actionable insights and facilitate data-driven decision-making.

When you partner with Lumen to plan, design and implement a unified infrastructure event intelligence platform powered by AI and ML, your organization will be equipped to handle the complexities of modern IT operations.

Ready to take the next step? Contact our skilled professional services team to learn more about AIOps services designed to help you achieve your IT goals.

LEARN MORE

This content is provided for informational purposes only and may require additional research and substantiation by the end user. In addition, the information is provided “as is” without any warranty or condition of any kind, either express or implied. Use of this information is at the end user’s own risk. Lumen does not warrant that the information will meet the end user’s requirements or that the implementation or usage of this information will result in the desired outcome of the end user. All third-party company and product or service names referenced in this article are for identification purposes only and do not imply endorsement or affiliation with Lumen. This document represents Lumen products and offerings as of the date of issue. Services not available everywhere. Lumen may change or cancel products and services or substitute similar products and services at its sole discretion without notice. ©2025 Lumen Technologies. All Rights Reserved.

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Artificial Intelligence (AI)Infrastructure Management


Author

Rashid Qureshi

Rashid is a strategic technology advisor with Lumen Digital, boasting over 25 years in solutions architecture and digital transformation. He specializes in global networking, cloud strategy, cybersecurity, IoT and AI-driven automation, collaborating with Fortune 500 companies in the energy, manufacturing, retail, fintech and public sectors. Passionate about innovation, Rashid leverages emerging technologies to enhance efficiency and create secure, scalable environments. He enjoys exploring new places, outdoor adventures and diverse cuisine.

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