In this article, Richard Whitehead, Chief Evangelist, Moogsoft, tells you why AIOps stands out as a practical and necessary choice amongst a suite of next-generation IT solutions.
While some people may be leery of tapping into the potential of artificial intelligence and machine learnings for fear of investing in “buzzwords,†AI for IT operations (AIOps) stands out as a practical and necessary choice amongst a suite of next-generation IT solutions. Gartner defines AIOPs as “software systems that combine big data and AI or machine learning functionality to enhance and partially replace a broad range of IT operations processes and tasks, including availability and performance monitoring, event correlation and analysis, IT service management, and automation.â€
Successful digital transformation relies on AIOps technology to ensure that IT professionals and teams are able to operate at the speed that modern business requires — and unless you’ve been out of the office for the last decade, you’ll know that this is fast.
Essentially, AIOps meets the needs of a modern organization because you can’t manage today’s dynamic, constantly changing IT landscape with tools of the past. They simply aren’t built to handle the amount of data and infrastructure of today or the future. And, AIOps is transforming the future of work — no longer are IT teams working around the clock to monitor incoming, mundane issues.
Instead, AI is doing the work overnight and, in the background, while IT teams experience more of a work-life balance to enjoy time with families. Additionally, while AI is working in the background, IT teams have the opportunity to sit at the boardroom table and bring their behind-the-scenes knowledge and business insight into big picture conversations to elevate the company.
To differentiate between the hype and the real benefits of AIOps, it’s worth considering the startling “growth†of the market. The number of vendors offering AIOps features grew dramatically over the last few years, so quickly, in fact, you might be suspicious of the technology being offered by some. And in many cases, you’d be right.
While some vendors have invested years of research building intellectual property in this new field, many have just bundled vanilla open-source Machine Learning libraries, or worse, simply re-branded their legacy rules-based solutions as “AIOpsâ€. No wonder some enterprises are failing to see the promised benefits. However, there are solutions out there that are not just meeting, but exceeding expectations. In almost every case, these solutions are applying ML and AI to specifically focused use-cases “Applied AI†if you will.
With Gartner recently reporting, “by 2022, 40% of all large enterprises will combine big data and machine learning functionality to support and partially replace monitoring, service desk and automation processes and tasks, up from 5% today,†here are four predictions about how AIOps (Applied AI specifically) will impact the industry next year.
1. Checking Off the Boxes of Decades-old IT To-do Lists
We’ve been hearing the same IT-related complaints for the last twenty years, such as data management and analysis, and with the rise and implementation of AI technologies, we’re finally able to circle back to those issues with a proper solution.
But we’re only beginning to scratch the surface. The biggest victories we’ll see for the industry next year is finally being able to resolve decades-old challenges in infrastructure observability and noise reduction.
2. Eliminating 100% of IT Operational Noise
When we apply automation technologies to IT operations today, we’re able to see up to a 99 percent reduction in noise. Over the next decade, experts and innovators will continually push to eliminate that extra one percent.
While at first, that might sound like a minimal accomplishment, the exponential increase in data and information makes this a monumental task.
3. Increased Security Measures to Deter AI Weaponization
Implementing automation and IoT in our lives has plenty of benefits, but there’s also an opportunity for weaponization. This isn’t unique, though, as all technology has faced weaponization in the past. The bad guys will be invested in AI, too, and we’ll see more data than ever before.
It’s essential that we have the ability and resources in place to monitor the data to avoid hacking and other dangerous situations. In the future, it’s absolutely necessary that data scientists and security experts align their work and mission to ensure safety and protection.
4. Re-skilling, not Replacing IT Professionals
For the foreseeable future, IT teams won’t shrink in size. There has been an industry-wide push for efficiency, but what we can expect in the next few years is re-skilling employees to accomplish new and innovative initiatives. We’ll be doing more, but with the same amount of people. Teams will remain the same, but we’ll increase the amount of business by restructuring the way IT teams operate.
A recent PwC survey shows that 73 percentOpens a new window of workers believe that artificial intelligence will never replace the human mind— so, while some fear that AI will replace jobs, it will actually assist in advancing teams to the next level. That’s what’s so great about this industry and an AIOps solution — humans and teams are still central to the work. We’ve seen how AIOps can increase productivity and keep businesses agile, and we can expect to see this concept continue to grow in the next year and beyond.
Where Does AIOps Fit into Your 2019 Strategy?
AI and machine learning are disruptive technologies, and that causes some people to pause and question whether they really want to challenge the status quo. Sure, change is difficult, but it’s important to understand how necessary it is to transition or pivot strategies in today’s workforce.
Now more than ever, we are always on, constantly checking email and working around the clock to keep up. In this fast-paced environment, an AIOps solution can save businesses time, energy, and money, and is essential to successfully operate in today’s competitive business landscape.