In a time when embracing digital transformation has become crucial for the progress of almost every business, those who don’t rely on artificial intelligence (AI) attempt the impossible. Years ago, predictions pointed out that 30 percent of IT organizations that failed to adopt AI would no longer be operationally viable by 2022. In reality, as companies embrace a multi-cloud ecosystem, the amount of data and high environmental complexity make it impossible for humans to trace, discern, and act. Adopting AIOps seems like the most logical and intelligent move to help companies thrive in an automated ecosystem. But what is AIOps and how can doing it the right way can be genuinely beneficial? 

What is AIOps, and why are more companies embracing it? 

Artificial intelligence for IT operations, better known as AIOps, connects two main concerns: AI algorithms with complex IT infrastructures. These multi-layered technology platforms automate and enhance IT operations through analytics and machine learning (ML). By collecting data from different tools and devices, AIOps can spot and react to issues in real-time. As we have become active consumers of technology, user expectations have evolved. Today, solving any related IT events demands urgent solutions so that user experience is not affected. 

Since this technology can detect errors and understand their actual root cause, humans will no longer play a crucial role in solving IT problems. These implementations don’t mean that this technology will replace humans; it simply shows how new realities need innovative technologies. As more enterprises start doing AIOps the right way, they will also realize that their workforce needs new skills, and new roles will need to be developed. 

Although artificial intelligence for IT operations could be relatively new for some CIOs and IT leaders, those employing it are saving considerable amounts of time by solving issues within minutes. AIOps also works as an emerging feature set to manage events such as network outages or delays. We can say these technologies are a form of superior IT analytics using cross domains, machine learning, and extensive data collection for many stakeholders. 

CIOs are constantly looking for efficiency, and they understand the importance of strategic investments in technology and the right talent to ensure an effective alignment of business priorities. All they need to do is to start. 

Introduction to AIOps

Starting points for businesses adopting AIOps 

Business stakeholders aren’t required to build their own in-house data science facilities. In fact, companies can rely on experts, vendors, or partners to handle the necessary research and implement the required products into their strategy. With IT at the center of digital transformation endeavors, AIOps grants organizations the speed to operate modern business demands.

Its benefits and purpose have significantly impacted its users; there has been an 83 percent increase in the number of organizations deploying or looking to deploy its capabilities since 2018. In addition, company surveys have ranked AIOps as the most successful IT analytics investment. With that in mind, we invite IT leaders who plan to employ it to start by reviewing the following tips for its right adoption: 

1. Take inventory 

To make the adoption of AIOps more effective, analyze and arrange an inventory of your current systems and processes. Some system duplicates will come up as you do this, and process inabilities will be more evident. Once you have identified the issues, you’ll be better prepared to move forward. 

2. Start small 

Figure out what the most relevant use cases that can benefit with AIOps in your business are. Decide which ones are most likely to succeed, and start small. Once you see the results and estimate their value, it will be easier for everyone to adapt to AIOps and embrace it confidently. 

3. Streamline the right data 

After recognizing what problems need the most attention, understand what it takes to solve them, and select the correct data. Keep in mind that not all operations data is necessary and focus only on what’s relevant for the process. 

4. Select the correct platform 

It’s essential to acknowledge your business’s maturity level to understand the type of platform that best fits your needs. Although some platforms may work for some companies, not all businesses operate the same way. Focus on choosing the right platform for your processes and systems more than rushing to implement the wrong one. 

5. Choose the right collaborators 

Operate with the right operations teams and ensure they have the required skills to help you achieve your goals. Keep in mind that this transition is a journey, and having clear objectives shared with your operations teams becomes crucial in the long run. 

Stages of AIOps platform monitoring

AIOps use cases 

Due to their capability to analyze extensive and diverse data, AIOps provide higher-level analytics and deliver faster mean time to resolution (MTTR). Using automation and machine learning capabilities to examine vast quantities of data makes this technology extremely useful. Most businesses seek a tool that doesn’t require overhead, is highly deployable, and can blend with multiple monitoring tools. In addition to optimizing IT operations, AIOPs visibility and automation can support and help drive other important business innovations. Let’s talk about some of the use cases. 

  • Threat detection 

With AIOps, patterns and anomalies are exposed, detecting possible risk events and taking the necessary actions to avoid them. When threats are complex, machine learning can undermine business service availability, becoming a valuable addition to a robust security management posture. The more it optimizes and learns to identify causes and propose solutions, the less human help it needs. Freeing the workforce from repetitive tasks will allow them to support and drive other important business and innovations. 

  • Event correlation 

While AIOps can group errors, they can also detect root issues at the core of the problem, transforming many alerts into one or two notifications that matter. AI empowers platforms to enhance correlation algorithms continuously and identify the root cause of problems more efficiently. 

  • Intelligent alerting and escalation 

After analyzing root causes, alerts, and notifications, ideal teams use AI to notify errors or incidents for faster remediation automatically. With machine learning capabilities predicting a fault, a ticket is created automatically, including all the necessary details required to resolve the issue. Since it acts immediately, it sets the remediation workflow in motion before a person ever gets involved. 

  • Automatic incident remediation 

AIOps take automated action in response to a problem; it resolves issues promptly and efficiently. Consequently, IT teams don’t have to worry about implementing any manual measures to fix an issue. In fact, this technology has greater visibility than the human eye, which guarantees a more effective solution. Considering that these tools continually learn from past data to improve solutions, the longer you use them, the better remediation processes you’ll acquire. 

  • Capacity optimization 

AIOps can also include predictive capacity planning, mapping workloads to suitable configuration of servers and virtual machines. Aligning the workload characteristics with an appropriate IT resource configuration optimizes application availability, maintains uptime, and attains continuous service assurance. 

AIOps use cases and automatic problem remediation

Modern CIOs are utilizing AIOps 

The truth is we can no longer manage the constant evolution of IT with old tools and practices. We are part of an unpredictable IT environment that demands progressive technology and innovative processes. For CIOs, this gives them the heavy responsibility of having to execute the most profitable decisions by establishing precise goals and objectives.

With the need to justify IT spending, CIOs are constantly looking for practical solutions that can add value and serve their purpose. To remain competent, modern CIOs are choosing artificial intelligence for IT operations, and organizations of all types and industries are employing its benefits globally. As a matter of fact, the AIOps platform market was making $2.55 billion in 2018 and is estimated to reach $11.02 billion by 2023; placing it at a Compound Annual Growth Rate (CAGR) of 34.0% during the forecast period. 

It’s clear that the adoption of artificial intelligence for IT operations is inevitable, and, fundamentally, business stakeholders are required to take the right path in order to achieve success. At TEAM International, we have guided many IT leaders to embrace this technology the right way. According to their needs and expectations, our experts have helped many businesses implement AI into their operations. We know firsthand how beneficial this tool can be. Contact us to assess further how your company can thrive by incorporating AIOps into your processes and systems. 


Could AIOps be beneficial for a small or midsize company? 

Yes, especially those conceived in the cloud with an urgent need to release and develop software. AIOps enables smaller companies to prevent pitfalls, failures, or outages, while constantly polishing their digital services. 

Is it possible to implement AIOps for a business currently going through digital transformation? 

With IT at the core of any digital transformation, speed and efficiency become crucial, and artificial intelligence for IT operations helps in their optimization. In fact, it is the right time to implement technology that delivers the level of support successful digital transformation projects require. 

Does effective IT depend on AIOps? 

Competitive enterprises understand the business advantage of effective IT. Doing AIOPs the right way helps IT be more efficient, resulting in the automatic improvement of conversion rates, financial metrics, and customer satisfaction.