In most conversations surrounding cybersecurity these days, the term “digital transformation,” gets frequently thrown in the mix, especially when the discussion revolves around AIOps. If you’ve got the slightest bit of interest in any recent developments in the cybersecurity world, you might have an idea of what AIOps is.
However, if you didn’t already know- AIOps refers to a multi-layered, modern technology platform that allows enterprises to maximize IT operations by integrating AI and machine learning to detect and solve cybersecurity issues as they occur. As the name suggests, AIOps makes use of essential AI technology such as machine learning for the overall improvement of an organization’s IT operations.
However, today- the role that AIOps plays has shifted dramatically- which leaves a lot of room for confusion to harbor amongst cybersecurity officers since most enterprises prefer to take the more conventional route as far as AI application is concerned.
To utilize the most out of AIOps, enterprises need to understand the significance of the changes in the present-day IT environment, and how those changes influence the AI’s applications.
To aid readers in understanding the volatility of the relationship between AI’s applications and the IT environment it is applicable in, we’ve put together an article that dives into the differences between conventional monitoring methods and present-day enterprise needs. Moreover, we’ll also be shining a light on the importance of the adoption of AIOps in enterprises as well.
How has the IT environment changed in the modern times?
Before we can get into every nook and cranny of why the transition from a traditional approach to a more modern approach matters, we’d like to make one thing very clear. Just because a specific approach works for one organization in no way guarantees that it would work for you.
Perhaps the greatest advice any business owner could receive is to plan according to the specific requirements of their security and IT infrastructure. The greatest shortcoming of many CISOs and CSOs is that they fail to understand the particular needs of their IT environment and rely on conventional applications of AI to maximize the overall IT experience.
Speaking of traditional AIOps applications, since the number of ‘moving’ parts or components involved was significantly less in number- the involvement of AI was far less complex, and therefore much easier to monitor and control.
In a more modern setting, however, with the wave of digitalization and the ever-growing reliance that enterprises have on cloud computing systems, the number of components involved has increased, which also makes understanding the web much more difficult. Bearing witness to the ever-evolving and complex nature of today’s IT environment are the results of the research conducted by Dynatrace. The results explicitly state that something as simple as a single web or mobile application transaction can involve a staggering number of 37 different components or technologies on average.
Taking this into account, relying on a traditional approach to AI becomes redundant, and ineffective since the conventional approach relies on an extremely limited understanding and fails to make sense of all the information provided by an arsenal of tools and dashboards.
Not only is the conventional approach to AIOps impractical within the modern IT context, but it is also extremely outdated. Having said that perhaps the only approach that fits in the modern-day IT environment is a software intelligence-centric approach, which allows for fast-paced and robust solutions to present-day IT complexities.
How important is AIOps for enterprises today?
As we’ve already mentioned above, the present-day IT infrastructure requires a drastic change in the relationship that enterprises have had with AIOps so far. For starters, enterprises and organizations need to realize the importance of the role that AIOps plays.
Unfortunately, however, there’s an overarching tendency seen in enterprises that enables them the naivety of labeling investing in AIOps as yet another “IT expense.” On the contrary, AIOps is essential for companies and organizations today, since every company is undergoing digitalization, along with increasing their reliance on modern technology more and more. Some cybersecurity specialists might even argue that each company is slowly turning into a software company, primarily because of the rise in cloud-computing systems.
AIOps also works on improving the ‘business’ aspect of an enterprise, since the modern consumer looks for enterprises that offer innovative features, along with their ability to enhance user experience through an impeccable and seamless digital experience. Furthermore, in the competitive economic conditions of today, carrying out business operations in a timely manner is critical to an enterprise’s longevity- which is where the integration of AI can help an organization function smoothly.
It should also be pointed out that the employment of AIOps opens up new avenues for businesses to step into since it removes the element of fear present in most business owners. The implementation of AIOps also enables an organization to make quick-paced releases since it takes IT problems out of the equation. These problems usually consist of bugs, regulation, and compliance, along with monitoring the overall IT experience being provided to consumers.
How can enterprises ensure the longevity of their reliance on AIOps?
When it comes to the integration of any new technology into an organization’s routine functions, there are always questions to be asked regarding the impact of the continued reliance on modern technology.
To demonstrate the point we’ve made above, let’s return to a tech we’ve referred to throughout the article- cloud computing. Introduced in the 1960s, cloud computing revolutionized data storage to what it is today. However, after a couple of years and some unfortunate cyberattacks launched on cloud storage networks, cybersecurity specialists have found some dire problems with complete dependency on cloud computing storage.
Similarly, many cybersecurity specialists and researchers wonder about the negative impacts that a dependency on AIOps could have in the future. When it comes to ensuring enterprises about the longevity of amalgamating AIOps into an enterprise, we’d like to give our assurance through the following reasons:
- Unlike cloud computing, developments in AIOps are heavily rooted in real-time data fed to the algorithm by an IT team. When you strip down all the fancy IT jargon, the only thing identity you need to trust is that of your IT personnel.
- Since AIOps relies on smart auto-remediation capabilities, business owners can see an immediate response geared by the employed algorithms. One such way that AIOps deploys auto-remediation strategies is by sending out alerts of any possible issue- the practice of which enables businesses to operate on the “business” side of the spectrum since they’ve got a trustworthy agent to rely on.
Conclusion
At the end of the article, we can only reinstate what’s been said before, in a thousand different ways- it’s high time that enterprises welcome change in the form of AIOps, instead of resisting it.
In the modern age of digitalization, the key differences seen in the modern-day IT landscape should be reason enough for enterprises to be on the lookout for new alternatives to securing their data, and by extension- their companies.
Author Bio
Rebecca James is an enthusiastic cybersecurity journalist. A creative team leader, editor of PrivacyCrypts.
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