The five key benefits of AIOps and automation


If you’re an IT professional—from the C-suite to a hands-on practitioner—you know the pressure your IT operations (ITOps) are under. You’re responsible for optimizing spend, operational efficiency and incorporating new and innovative technologies. But are your tools slowing you down?

Coined by research firm Gartner, AIOps is artificial intelligence for IT operations. It is the application of artificial intelligence (AI) capabilities (e.g., natural language processing and machine learning models) to automate and streamline operational workflows.

In this blog post, we will examine traditional IT operation problems through the lens of data-driven automation and the benefits of AIOps. It’s a powerful way to address critical issues like sub-optimal application performance and poor customer experiences, boost metrics like MTTR and address IT team skill issues for greater resiliency.

We’ll show you how AI-powered solutions can help your IT staff move from a “break-fix” approach to one that’s more predictive and proactive, designed to address dynamic challenges, deliver faster problem remediation, provide bottom-line benefits to your organization and help you achieve digital transformation.

1. From performance blind spots to more observability and better collaboration

The proliferation of cloud services, microservices, containers and hybrid cloud environments can leave traditional IT operations teams struggling to monitor and manage potential issues within these complex environments. The result is blind spots, false alarms and delays in identifying and resolving issues. And every second counts—a recent IDC survey found that a single hour of downtime costs an average of USD 250K or more when a revenue-generating production service is impacted.

With AIOps, you have the benefit of observability tools that deliver near real-time data granularity and cardinality for all application stakeholders. Better visibility, communication and transparency means teams can pinpoint problems in a more nimble and responsive fashion. For example, as Enento Group modernized existing, on-premises systems, it used observability to monitor all of its applications in one place. This approach allowed them to meet SLAs and achieve 99.99% availability.

Today’s complex, diverse networks also benefit from AIOps and real-time performance monitoring. BT Business enabled a new level of visibility and consolidated the number of monitoring systems by 80%. This enabled simpler integration and offered a major reduction in software licensing costs.

2. From “no human can keep up” to faster MTTR

On average, organizations are using 1,000+ applications across hybrid cloud environments. We’re also drowning in data, yet less than a third of enterprise data is even used. Traditional IT infrastructures can’t keep up with analyzing all the information, which means it’s difficult—if not impossible—to understand opportunities for improvement and innovation.

The benefit of AIOps is that you have the tools to cut through IT noise while correlating operations data from multiple IT environments. This means you can use anomaly detection, perform root cause analysis and propose solutions faster and more accurately than humanly possible. IT teams can shift from fixing to deploying and deliver greater value to the business. For example, ExaVault chose an observability solution for instant visibility into application performance issues and reduced mean time to resolution (MTTR) by 56.6% as a result.

3. From overspending to cost optimization

Too often, the traditional ITOps approach to managing applications is to overspend in the cloud to avoid performance risks. No wonder organizations say 32% of their cloud spend was wasted in 2022. But these days, every penny counts, and this wasted spend has environmental implications, too.

The benefit of AIOps is the ability to optimize cloud costs by using software—not human intervention —to make critical decisions. Applications get exactly the resources they need, when they need them—continuously and automatically. For example, in just 10 months, Providence safely migrated a significant portion of its workloads to Azure and achieved more than USD 2 million in savings through optimization actions—all while assuring application performance, even during peak demand.

4. From a negative environmental impact to more sustainable IT

Data centers account for 1-1.5% of global electricity use. As we mentioned above, it’s not uncommon for IT teams to over-allocate resources to mitigate application performance risks. Yet that traditional approach costs both the business and the environment, and customers are watching how seriously you take commitments to ESG. According to Nielsen, 75% of Millennials will change their buying habits to favor environmentally-friendly products.

When it comes to sustainability, AIOps tools enable you to implement the FinOps cloud financial management discipline and automatically optimize your cloud and data center environments. That, in turn, lessens the amount of energy used, reducing waste produced by idle machines. For example, since shifting to AIOps, BlueIT reduced waste across their clients’ environments. After executing resourcing recommendations powered by artificial intelligence, one customer achieved a 10% reduction in memory and CPU over-allocation.

5. From staff concerns (and IT fire drills) to a more productive workforce

Finding, keeping and training the right IT staff is a top concern. Because of automation and new technologies, it’s estimated that 50% of all employees will need to upskill or reskill by 2025. Traditional ITOps rely too much on individual, human intervention, manual efforts (like chasing down bugs) or on institutional knowledge of what’s worked in the past.

The benefit of AIOps is that it allows employees to use tools that continuously learn, so knowledge doesn’t leave when someone retires. AI-powered proactive incident management helps identify false positives and prioritize the most urgent alerts. That gives IT teams the power to address potential issues before they lead to slow-downs, outages or poor customer experiences.

For example, Electrolux accelerated IT-issue resolution from three weeks to just an hour via faster mean time to detect (MTTD) and saved more than 1,000 hours per year by automating repair tasks.

As our systems continue growing in complexity, IT challenges (and the pressures you’ll face) certainly won’t decrease. But by up-leveling your IT operations with AIOps solutions (and the AIOps benefits that come with them), you’ll have the automation, powered by artificial intelligence, to create IT that can respond in seconds for less downtime, better application performance, lower operational costs and greater success with digital transformation.

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