What is AIOps? Streamline IT operations with AI automation

AI for IT operations (AIOps) is transforming how businesses manage their complex IT ecosystems. Using AIOps can help put your response teams back on the offensive, automating time-intensive activities and preventing disruptions before they occur.

First coined by Gartner, AIOps, or AI artificial intelligence for IT Operations, refers to using AI, machine learning, and big data to improve the way IT systems are managed. AIOps tools use AI to monitor system performance, link related events, and spot unusual activity automatically, reducing the need for constant supervision and human guidance. 

Why is this important? Consider the old saying: By the time you hear the thunder, it’s too late to build the ark. As an IT decision maker, you know that most complications start small, as inconspicuous anomalies or subtle issues that can be easy to ignore in the face of more pressing concerns. Without embracing AI, it can be extremely challenging to see or keep up with these early warning signs, and we may eventually find ourselves frantically hammering together solutions as major problems rain down. AIOps is the solution.

Here, we break down the basics of AI for IT operations—what it is, how it works, and the value it brings to your business.   

What is AIOps? AI for IT operations explained

Modern businesses are enjoying a renaissance of technological innovation, nearly outpacing the kind of exponential growth predicted by Gordon Moore way back in 1965. According to a recent survey, 88% of organizations note that their technology stack has grown within the past year, and more than half of respondents expect that it will continue to do so. 

But while expanding IT systems and tech stacks means expanding capabilities, it can also mean increased data complexity—often to the point of obfuscation. IT systems generate a flood of data, and that can make it very challenging to spot the early indicators that something is going wrong. And when IT teams are forced into a reactive stance, they don’t have time to address root causes. 

The core goal of AIOps is to leverage advances in artificial intelligence to enable continuous improvement and optimization of IT systems, data, and processes. AIOps helps empower IT leaders to manage their infrastructure with greater precision. It sifts through the deluge of data from multiple sources (including historical and real-time data), calling out meaningful patterns and identifying issues long before that first, thunderous alert. This gives IT operations management a solid foundation on which to analyze data, automate processes, and enhance IT operations and workflows. 

How does AIOps work?

Now we'll explore how AIOps turns the vast amount of data from different sources into clear actions and fixes. By beginning with data ingestion and aggregation, then using data analysis, and finally having proactive incident identification.  AIOps tools use machine learning to sort through data, pick out real problems from minor glitches, and give a complete picture of your IT setup.

1. Data ingestion and aggregation: AIOps platforms typically aggregate information from application logs, performance metrics, event data, configuration data, network traffic, and even unstructured data (like documents and social media mentions). This data ingestion is possible because AIOps platforms can integrate with a wide array of IT monitoring tools and data collection platforms. By consolidating diverse data from across IT ecosystems, advanced AIOps solutions can break down silos to provide a holistic and unified view of your entire infrastructure. 
2. Data analysis: Advanced AIOps solutions employ sophisticated ML algorithms, which include both supervised and unsupervised learning methods, to process this downpour of information. Through anomaly detection, pattern recognition, and predictive analytics AIOps sifts through the noise, distinguishing between genuine issues and irrelevant fluctuations. This intelligent filtering is crucial, as it ensures that IT teams are alerted only to real problems, not overwhelmed by false alarms. Using the power of AI for data analysis, IT Ops teams are able to process and analyze data at a speed and scale unattainable by human teams alone, underscoring the necessity of AI in managing modern IT ecosystems. AIOps likewise works to reduce alert fatigue by intelligently grouping related alerts and eliminating false positives. And because the best AIOps systems are self-learning (i.e. using feedback from their actions), they are able to improve their capabilities over time.
3. Proactive incident identification: Once potential issues are flagged, these advanced AIOps solutions dive deeper into inference and root cause analysis, pinpointing the underlying causes that lead to disruptions and other problems. They then take things a step further by helping to automate remediation steps, such as by executing predefined scripts or scaling resources autonomously to resolve issues completely on their own.
   
   In other words, leading AIOps platforms give IT teams the insights and automated support they need to close the loop, ensuring the right actions at the right time to turn what has traditionally been a more manual approach into something tactical, intelligent, and assertive.

Benefits of AI for IT operations

If IT teams are flooded by tickets and trying to keep the department afloat, they’re not focusing on more strategic initiatives that drive growth. Implementing AI for IT operations can help your support teams to take a more active approach, automating time-consuming tasks and addressing potential disruptions before they escalate. One study found that the average AIOps solution could improve IT efficiency by as much as 28% to 50%.

More generally, businesses that prioritize AIOps typically see the following advantages:

• Increased operational efficiency: This has already been partially addressed, but it’s worth repeating: When AIOps becomes integral to your IT strategy, it positions your team as a driver of innovation. Intelligent automation evolves the role of the IT professional to operate as more than just a triage-and-response unit. They can instead dedicate the majority of their time towards higher-value activities, delivering a greater return while driving innovation in support of your company’s broader objectives. Add to this the increased accuracy and reduced response times associated with AIOps, and IT teams can achieve a level of efficiency that manual processes cannot match.
  
  
• Proactive issue management: Would seeing into the future benefit your IT department? AIOps is the next best thing. With predictive capabilities, AIOps identifies potential upcoming issues based on data patterns and trends. This approach reduces the frequency of emergencies and minimizes the need for stop-gap solutions or reactive problem-solving. Advanced AIOps solutions detect even the most subtle indicators of future issues—like unusual usage patterns, performance dips, or security anomalies—and with this foresight, IT teams can take preemptive action.
  
  
• Reduced costs: Proactive issue management likewise leads to better resource allocation. Knowing what to expect (and when) means knowing how much of any particular resource you might need at any given time. This allows for more accurate budgeting, eliminating the dangers of overstaffing or under-resourcing critical IT functions. Task automation also leads to improved accuracy and lower operational expenses.
  
  
• Faster issue resolution: When it comes to resolving IT problems, every second is precious. We mean this literally; a recent report from Information Technology Intelligence Consulting (ITIC) revealed that a single hour of server downtime can cost anywhere from $1,670 to $5,000 per minute. By reducing downtime and improving mean time to resolution (MTTR), AIOps keeps business operations running smoothly and minimizes those little interruptions that end up costing big in terms of lost revenue.
  
  
• Better decision making: Visibility in modern IT environments is often cloudy at best. Effective AIOps solutions clear the skies by consolidating data from across the tech stack to create a centralized view. Gaining real-time observability backed by actionable insights, IT teams and management-level decision-makers gain the benefit of having all the right information before they commit to a course of action.
  
  
• Improved collaboration: By centralizing information access, top-tier AIOps platforms establish a reliable single source of truth for everyone working with IT data. Gone are the days when teams operated in silos; with AIOps providing a unified, real-time picture of the entire infrastructure, teams across the organization can now share insights and address issues as a cohesive unit.
  
  
• Optimal scalability: Your business isn’t static. And as it grows and changes, the data produced by your IT systems likewise expands. This isn’t a problem for most AIOps solutions, handling growing workloads without the associated increase in IT resources. This unrestricted scalability empowers IT teams to manage complex environments and higher data volumes, ensuring systems remain resilient as the organization expands.

Challenges in implementing AI for IT operations

An effective approach to AIOps simplifies and streamlines IT operations, but that doesn’t mean that every AIOps solution is a walk in the park. Effectively implementing AI for IT operations requires acknowledging and overcoming a few challenges that, if left unaddressed, could easily derail your efforts. Below are some of the most common hurdles businesses may face with AIOps:

• Insufficient or poor-quality data: There’s a concept in computer science that applies to any data-backed initiative: ‘garbage in, garbage out.’ The effectiveness of your AIOps solution is typically only as good as the data on which it is built. So if your data isn’t up to par, then AIOps won’t have as much to work with. AI relies on large amounts of high-quality data to train its models and make accurate predictions. When that data is inaccurate, incomplete, or inconsistent, the platform’s effectiveness is compromised.
  
  The right data governance framework may help bring your data in line, and regular data audits can improve the quality of the information before it enters the AIOps platform. Integrating data validation tools and collaborating closely with data teams can also support ongoing data quality.
  

• Difficulty integrating with legacy systems: Unless you’re operating a well-funded startup, there’s a good chance that your organization relies at least partially on legacy systems. Digital solutions that predate AI solutions are unlikely to integrate with AI-driven platforms. As such, legacy infrastructure can hinder AIOps from accessing critical data sources or executing automation across various systems. When AI for IT operations can’t integrate, it can’t also consolidate all the relevant data it needs to create a complete and actionable picture.
  
  Counter this by implementing middleware solutions or APIs that can bridge the gap between legacy systems and AIOps. For more long-term benefits, consider a phased approach to system modernization, gradually updating critical infrastructure to progressively improve compatibility.
  
  
• Lack of process standardization: AIOps tends to perform best in a structured environment, where IT processes are well-defined and consistent. But the reality is that many organizations operate with improvised workflows that vary from team to team. This lack of standardization creates unpredictability, making it difficult for AIOps to effectively automate tasks or generate accurate insights.
  
  Adopting a structured IT service management framework can help bring consistency and predictability to your IT processes. Standardizing workflows and then training teams on these refined processes allows AIOps to operate in a more stable environment.
  
  
• Resistance from internal users: Even the best tools are inadequate if no one bothers to use them. Making the shift to AI for IT operations can be a disruptive process, which can lead to resistance among your IT teams. Some users may view AI as a threat to their jobs, while others might simply not want to change the way they’re most accustomed to working. Whatever the motivation, the end result is the same: Lack of adoption and reduced engagement that ultimately lead to decreased platform effectiveness.
  
  As is so often the case, the solution is transparency and education. Leaders must address user concerns by emphasizing how AIOps will empower IT teams to devote more of their time towards higher-level tasks instead of near-constant troubleshooting. Clearly communicate the advantages of automation and observability, and offer comprehensive training to ensure everyone is prepared before making the switch. Buy-in at all levels is highly beneficial, but may be most impactful among leaders who can demonstrate their commitment and create a positive example for others to follow.

AI for IT operations: Staying afloat in a sea of IT

Manually trying to make sense of too much data can feel like trying to stop a flood. AIOps platforms can help you rise above the deluge, managing complex systems with precision, automating routine and complex tasks, and preventing costly disruptions from reaching the surface. 

Moveworks offers advanced AI for automated IT support, which can help streamline the ticket lifecycle and respond to IT issues efficiently. Our solutions include:

• AI service management: Unburden support teams and empower your workforce with the most complete AI solution for support automation.
• Pre-built integrations: Moveworks has 40+ prebuilt integrations for specific enterprise systems, including ITSM platforms, ITOM platforms, and more. These integrations facilitate complex interactions across multiple systems, enhancing IT operation.
• Better support through agentic AI reasoning: Moveworks’ proprietary language model, MoveLM, is fine-tuned using nearly a decade’s worth of enterprise support data. Integrated into our core Reasoning Engine, its fluency in real-world business scenarios sets our Copilot apart in delivering nuanced employee support.

With Moveworks solutions, you can elevate your employee productivity and reduce operational costs by helping your people make the transition from reactive IT operations to proactive IT management. 

Don’t let your team drown in IT data; demo Moveworks and see how AI can help you navigate the currents of operational information.