2020 Business Trends: AIOps and the Promise of Self-healing IT

New technology is enabling new efficiencies, enhanced performance, and filling the critical need to manage increasingly complex infrastructure.

Today’s overtaxed IT teams are under tremendous pressure to leverage new technologies like AI, cloud and IoT to innovate, but in reality, they spend most of their time just trying to keep the lights on.

According to a Gartner survey, 63% of senior executives indicated that an IT talent shortage was a key concern for their organization, with additional studies showing that by 2030 more than a million IT and telecommunications jobs will go unfilled in the Unified States; the European Commission estimates a shortage of 756,000 skilled workers in these fields in just the next 18 months.

The lack of skilled technical workers comes at a time when IT complexity is increasing exponentially, and data volumes are exploding – all driven by digital transformation initiatives underpinned by understaffed IT departments. While IT has finally achieved a prominent seat at the table as the enablers of innovation, most CIOs find themselves still spending 70 percent of their budget and staff just keeping things up and running, according to a survey from Deloitte. Gartner estimates that number closer to 85 percent.

With this perfect storm brewing, companies who want to survive and thrive are looking towards new technologies like AI and automation to bridge the gap and gain a competitive edge. As we look to 2020, you should look for increasing focus on intelligent automation and AIOps to help them address challenges introduced by digital transformation and to move closer than ever to achieving truly self-healing IT.

Challenges of Modern IT Infrastructures

As digital transformation initiatives have hit their stride, IT infrastructure has become exponentially more complex. It’s no doubt that IT now plays a critical role in business innovation, but it has come with challenges, including:

  • Exponential increase in data volumes and data types, with Gartner estimating that data volumes generated by IT infrastructure and applications are increasing two- to three-fold every year.
  • Constantly changing infrastructure that is heavily virtualized and spread across hybrid environments in the cloud and multiple data centers.
  • Overwhelming influx of alarms and monitoring data, making it almost impossible to know where to focus and find the needle in the proverbial IT haystack when it comes to alarms and incident resolution.

In spite of these challenges, the IT department is still expected to rapidly resolve requests, incidents, and performance issues without adding members to teams that are already stretched thin.

Improving Operational Efficiency with AIOps

Despite all the hype, AIOps really does promise significantly improved operational efficiency for IT teams and to address the challenges mentioned above. Two years ago, Gartner reported that 78 percent of CIOs and senior IT leaders were looking to AI to address complexity. We believe 2020 is the year we’ll see that vision become reality, with Gartner now estimating the subsegment of the performance analysis market that includes AIOps, ITIM, and other monitoring tools at $5.7 billion by 2020.

With AIOps, IT teams can leverage artificial intelligence and machine learning to analyze and contextualize large volumes of systems data from multiple sources to provide a single pane of glass into the health of the IT infrastructure. AIOps quickly identifies existing or potential performance issues, spots anomalies, and pinpoints the root cause of problems.  Through machine learning and advanced pattern matching, these solutions can even effectively predict future issues, enabling IT teams to automate proactive fixes before issues ever impact the business.

AIOps tools also perform advanced correlation and offer automated mapping of dependencies between dynamic, changing infrastructure components for a real-time visualization of relationships between applications and the technology that supports them. This makes it easier for IT teams to see how things are connected and quickly get to the root cause of the problem, while filtering out false alarms.

AIOps solutions are seeing significant growth as IT teams cope with various challenges, like reducing IT costs and dealing with a shortage of skilled talent while managing increasing complexity.

The Promise of Self-Healing IT

AIOps alone can deliver incredible value for a business. But the real power comes when it’s paired with robust automation capabilities that can autonomously execute immediate actions based on AI-powered insights. Combined, AIOps and automation deliver a closed-loop system of discovery, analysis, detection, prediction, and automation – bringing the promise of “self-healing IT” one step closer to reality.

Self-healing IT offers the possibility of not only significantly improving performance and uptime, but also to achieve the aspirational goal of “NoOps” where automation and AI handle the majority of IT operations and, in doing so, free up IT resources to focus on more strategic, value-added projects and innovation.

We believe that in 2020, AIOps and IT automation will be widely embraced by organizations to tackle the IT challenges resulting from a decade of digitization, and be critical components in improving operational efficiency, reducing mean time to resolution (MTTR), and increasing the performance of business-critical infrastructure. In fact, for future digital transformation efforts to succeed, IT teams absolutely must harness AI-driven and automation technologies — and ultimately self-healing IT – lest they risk falling behind as infrastructure complexity eclipses the human capacity to manage it. 


Vijay Kurkal serves as the Chief Executive Office for Resolve where he oversees the strategic growth of the company as it helps maximize the potential of AIOps and IT automation in enterprises around the world. Vijay has a long history in the tech industry, having spent the last twenty years working with numerous software and hardware companies that have run the gamut from mainframe to bleeding-edge, emerging tech.