Professionals in IT operations often resolve issues by automating scripting or coding.
Why use automation?
Throughout the past two decades, technological innovations and information delivery systems have spurred unprecedented growth. The continued evolution of tech, as well as human ingenuity, present organizations across the retail, manufacturing, telecom, banking, and financial services sectors with an array of ever-expanding scenarios and challenges. As just a few examples, being connected continues to become cheaper, and device ownership is skyrocketing.
Data volumes are soaring, and billions of new connected data sources are anticipated within a few years. We are quickly approaching exabyte volumes and are surging toward zettabytes, and the growth of mobile connectivity continues to surpass fixed lines. Security is, as always, a major issue, along with regulatory complexity.
These automations, however, often only work within a monolithic and extremely predictive environment. If one thing changes in that environment, it typically results in the automation failing within the system. Once this happens, an IT professional must begin the troubleshooting process, which might take anywhere from five to thirty minutes to complete. This increases a company’s internal costs and bogs down IT resources.
Are Humans and Artificial Intelligence (AI) Destined to Work Together?
IT has revolutionized businesses across global industries. The way IT operates in most enterprises, however, is still very people-centric, which means the industry is prime for robotic or runbook automation initiatives. Having a fairly straightforward goal of achieving direct cost savings, these automations can reduce the manual effort spent on repetitive activities.
Robotic process automation (RPA) is great for a predictive environment, but it’s not necessarily designed for an ever-changing landscape. It lacks, therefore, the agility to successfully handle many scenarios. To see better results, the automation efforts need to be cognitive and intelligent.
While script-based automation yields quick, small wins, most organizations soon realize the accelerating pace of business-related changes, the increasing complexity of technology and operations, and rising technology-based operational risks far outmatch traditional automation capabilities. There is a critical need, therefore, for an intelligent system that can keep up with technology churn, understand business processes, and be customized to an industry domain and business model.
Many companies praise automation like it’s already the backbone of their business platforms, but human intervention within that automation is still largely necessary. Companies like Digitate try to be aware of this (currently) inescapable reality by working with top brands in virtually every industry. By continuing to improve their product capabilities, service delivery, and customer support, they can build a community of dedicated users who are excited about sharing their stories with them.
Digitate™ leverages machine learning and artificial intelligence to manage IT and business operations. Their product, ignio™, enables better decision-making and ultimately solves IT operations challenges.
Other companies that also leverage machine learning and AI to manage IT and business operations are still working on developing an overarching process that can understand system needs across dynamic situations from different sectors. This is a daunting task, though, and something no one has been able to achieve—yet.
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