Recently, there has been a steep rise in the research and utilization of Artificial Intelligence (AI). While AI once seemed like nothing more than a fantasy from a sci-fi movie, AI technology is now very much a reality in our everyday lives. Artificial intelligence and machine learning are involved in many of our daily tasks, from search engines that finish your thought, to pulling up directions in Google Maps, and how your Facebook and other social feeds are so perfectly catered to your interests.

Despite what movies like The Terminator may lead you to think, AI is not something to be afraid of or avoid. Instead, AI can be used to improve upon many of the services and apps we use in our daily lives, while also encouraging innovation. Currently, artificial intelligence and machine learning (ML) are helping to fuel major changes in IT Operations. With AIOps—or Artificial Intelligence in IT Operations—tech companies are finding new ways to streamline and automate many internal processes, while ensuring an optimized user experience for their customers.

With the new year well under way, let’s take a look at the top 5 biggest AIOps trends to watch out for in 2021.

AIOps Trend #1: Multi-Purpose Tools

One of the most appealing trends coming to AIOps is the presence of multi-purpose tools. Currently, many of the available AIOps tools are only able to handle a single data type at a time – be it metrics, logs, etc. This means having to use multiple tools and combine data points in order to achieve a given task.

However, in 2021, we’ll be seeing new AI algorithms get created to handle multiple data types at once and by a single application or tool. This will allow these tools to view all of the given data (metrics, logs, transactions, events, etc), analyze how they relate and interact with each other, and help reduce alert noise by grouping them together whenever it makes sense. Most importantly, the presence of multi-purpose AIOps tools will ultimately save companies time and money.

AIOps Trend #2: Faster Incident Response

An area where AIOps truly shines is incident response. AIOps provides teams with much faster root cause analysis by automatically performing analysis procedures for events, logs, other metric data, and providing relevant and real time context to responders to accelerate triage. Teams can be equipped with information such as past incidents that look similar to the one at hand, or pointed to relevant incidents happening at the same moment in time. What this means is much faster incident response times and a more reliable service. AIOps takes all of the data to predict possible issues much sooner, allowing your team to respond much more quickly—often before an incident even occurs.

With proactive incident detection and AI-backed event management, response times are faster than ever, and we only expect this to improve in 2021 with multi-purpose tools and smarter algorithms.

AIOps Trend #3: Heavier Reliance on AI for Remote Work

With everything that’s happened in 2020, one thing that became very apparent is that remote work is here to stay. Due to the pandemic, many tech companies were essentially forced to have to close down their offices and have their employees work from home. This eventually led to companies like Facebook and Twitter to adopt permanent work from home policies.

What remote work means for AIOps is data is now being collected from a wider area of locations rather than single clusters (ie: an office building or classroom). There are now many unique data generators, which will require new intelligent algorithms to help predict new incidents with employee productivity and the remote use of the service. These changes can help to predict problems before they occur as many of us continue to adjust to a fully remote workspace.

AIOps Trend #4: Better Security and IT Integration

In 2021, we’ll be seeing much more integration between security and IT as a means to more quickly detect and prevent problems, threats, and vulnerabilities. The data sets for securing your infrastructure and IT operations are nearly identical. AIOps can help automate the interaction between security and operations algorithms, allowing the system to almost immediately stop cybersecurity threats in their tracks.

AIOps Trend #5: Preventative and Automated Remediation

AI algorithms can help with preventative and auto remediation of incidents. With AIOps, incident detection and resolution can be automated to detect anomalies and prevent a problem from occurring. This will free up time for IT operations teams to innovate and focus on providing their customers with the best possible experience.

As we see new tools in 2021 with multi-data point collection, proactive incident detection and resolution, and smarter algorithms that include a focus on remote work, we’re excited about the new ways AIOps can help teams work more efficiently and creatively.

Artificial Intelligence in Tech: What is AIOps?

As Gartner defines it, “AIOps combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination.” Simply put, AIOps allows teams to focus far less on completing or assigning individual tasks and more on what they do best—innovating and creating better products and services. Plus, with AI-backed insights and intelligence, teams and processes are made more efficient and services more reliable.

In the tech world and for IT Teams, AI has brought along new ways to further increase speed and efficiency to provide users with seamless experiences that meet their rising expectations in a world of “digital everything.” You’ve seen how DevOps has completely changed how development and IT Operations work together. AIOps takes things a step further, using data science and AI to further automate several processes for faster service delivery, reduced costs, and overall improved quality.

Want to learn more about AIOps and how you can bring it to your company? Read up about PagerDuty Event Intelligence or check out this interview with PagerDuty’s Director of Product Marketing, Julian Dunn, to find out What is AIOps, Exactly?