AI Will Be The Most Powerful Tool for Real-Time Analytics

By Jeff Aaron, VP of Enterprise Marketing, Juniper Networks

Originally published on RT Insights on 4/7/20

AI and machine learning are dependent on high-value data, which means IT departments need to have the proper visibility into what is happening on their networks.

Achieving IT automation continues to be a major goal for many enterprises. As CIOs contend with shrinking staffs and increasingly complex IT needs, being able to redeploy resources away from the help desk and troubleshooting needs and onto more strategic challenges is a must. But reaching that goal requires organizations to embrace AI to solve the massive data and decision-making challenges needed to automate a large enterprise at scale.

Machine learning and AI are crucial tools in providing secure and predictive analytics in the data center and beyond. The focus there is on the predictive – by being able to understand and benchmark data center and network operations over time, AI will be able to thwart problems before they arise, streamlining operations and reducing unplanned downtime in the network.

By marrying AI with real-time analytics, enterprises are equipped with unprecedented visibility into the user experience. This information allows IT workers to be proactive in a way that they’ve never been before. It is transforming the support experience, moving away from the incumbent legacy world of reacting, and leaning towards proactively alerting through the power of data, data science, and AI so that they can resolve most problems well before end users even know there is an issue to report.

AI provides a number of benefits, all of which increase accuracy and efficiency while reducing individual time investment and costs. They include:

  • AI can improve accuracy and save employees time: By reducing the time needed for tasks such as collecting data and double-checking work, AI can save employees time and increase overall accuracy to empower enterprises to make faster and smarter business decisions
  • AI can help enterprises save money: AI is a long-term investment: implementing AI may be cost-heavy at the beginning, but over time, the increased efficiency will result in a more profitable process overall that is well worth the initial investment
  • AI allows enterprises to predict problems before they occur: AI gives IT workers the power to be proactive: in addition to less worry about human errors, workflows can be self-corrected and/or optimized in real-time, allowing for peace of mind so that employees can focus on more important tasks

There are a number of ways that businesses can adopt AI technologies and implement them into real-time analytics. Some include improving established processes, such as data management. Others include introducing technology that is new for the enterprise, such as the proliferation of virtual assistants.

Virtual assistants

  • Businesses can take analytics to the next level with tools such as the ability to have an AI virtual assistant that can proactively tell you how you should spend your time, measure your activities, learn from them and solve problems proactively in the future
  • Virtual assistants can also help users troubleshoot and extract insights from the network while applying data science and AI to analyze and correlate data

Data management

  • AI can make the data management process more robust; AI can utilize machine learning-based optimization to help businesses predict and shape outcomes via smart, data-based decisions
  • Creating a robust data set that characterizes network, client and application behavior can create a strong foundation for AI processes to build upon

Despite all of the benefits that AI can bring, companies do need to understand the challenges. AI and machine learning are dependent on high-value data, which means IT departments need to have the proper visibility into what is happening on their networks. Perhaps an even greater challenge is preparing employees for the realities of AI. Often feared as the job-killer, smart IT leaders need to get ahead of that issue by offering programs on how to work with AI technologies and ensuring their teams understand that AI is not a replacement for individuals, but instead another tool that will make their job simpler and more productive.