Our AI by Design series explored responsible approaches to developing artificial intelligence (AI) systems. Now, it’s time to get practical about leveraging this exciting technology to transform our daily operations. Our upcoming blog series identifies three types of AI adoption—diagnostic, assistive, and automated—and helps you determine where these distinct applications fit into your workflow.
Using Machine Learning Tools to Diagnose Issues in Your Environment
Reactions to the launch of ChatGPT in 2022 might have convinced some that artificial intelligence was brand new, but diagnostic AI has been helping tech pros manage their IT infrastructures for decades. Here are some everyday use cases:
- Anomaly Detection: Diagnostic AI can monitor systems in real time to spot unusual patterns or behaviors. For example, if a server suddenly uses more resources than usual, the AI can flag this as an anomaly, prompting further investigation.
- Root Cause Analysis: When something goes wrong, such as a server outage or application failure, diagnostic AI analyzes various data points to identify the underlying cause and determine why it happened.
- Incident Management: When issues arise, diagnostic AI can assist in triaging incidents by prioritizing which problems need immediate attention based on their impact and urgency.
- Predictive Maintenance: By analyzing historical data, diagnostic AI is able to predict when a piece of equipment might fail. This allows IT teams to conduct maintenance before a crash occurs, reducing downtime and increasing system reliability.
- Capacity Planning: AI tools can assess current usage patterns and predict future demands on resources, helping organizations allocate resources more effectively.
IT pros need accurate information that can help them stay ahead of any potential problems in their environment. We'll dig into the landscape of diagnostic AI, discussing where it’s most effective and how your team can reap the benefits.
Leveraging AI to Assist in Managing Your IT Infrastructure
Assistive AI augments and streamlines various processes, acting as a helpful, interactive aid supporting IT pros through their daily tasks. Some typical use cases for assistive AI in IT management include:
- Chatbots and Virtual Assistants: AI-powered chatbots can respond instantly to user inquiries, helping resolve issues without human intervention for basic queries.
- Automated Troubleshooting: By cross-verifying information, assistive AI can provide IT teams with specific answers to common issues for faster resolutions.
- Smart Ticketing Systems: AI can prioritize and route support tickets based on urgency and impact, helping IT staff address the most critical issues first.
- Knowledge Base Enhancement: Assistive AI can analyze past tickets and resolutions to identify gaps in knowledge bases and suggest updates to improve the resource pool for IT teams.
Building on our breakdown of diagnostic AI, our next article will identify where assistive AI tools are best deployed to enhance your IT operations.
Mobilizing AI to Automate Workflows
When we’re served up utopian visions of total automation, with AI handling our tasks while humans put their feet up, we’re talking about AI automation. The main use cases for this approach in IT management include:
- Workflow Automation: By integrating with various tools and systems, automated AI can automate workflows like incident management processes, change requests, and approval chains, improving overall efficiency.
- Automated Incident Resolution: AI can handle routine incidents by automatically diagnosing and resolving issues without human intervention, allowing IT teams to focus on more complex problems.
- Dynamic Resource Management: AI can automatically adjust resources based on real-time demand, optimizing performance and cost-efficiency by scaling up or down as needed.
- Predictive Analytics for System Maintenance: Certain kinds of AI leverage historical data to predict potential failures and automatically schedule maintenance tasks, preventing issues before they impact users.
- Intelligent Security Responses: In cybersecurity, AI can automatically respond to threats by isolating affected systems, blocking malicious traffic, or initiating predefined mitigation protocols based on real-time analysis.
Our third article aims to provide a realistic overview of how AI automation can be deployed in IT management today. In which areas of your business is it worth investing? What does the future hold as technologies like Agentic AI gradually emerge?
Finding an Approach to AI Integration that Works For You
A simplistic interpretation of AI adoption sees organizations making linear progress through stages, starting with diagnostic AI, then moving to assistive, before graduating to full workflow automation.
But this is naïve, with countless variables, including resources and risk, influencing the appropriate approach for a given situation. This series aims to provide detailed insights into each approach, outlining the best use cases and contexts for their deployment. By the end, you should be well-equipped to begin optimizing artificial intelligence in a way that suits your organization.
Interested in how SolarWinds develops artificial intelligence-driven solutions? Check out our AI by Design series.
