This is the final installment in a three-part series. Be sure to read part 1 for the more information on unified endpoint management (UEM) and part 2 for additional details surrounding the Internet of Things (IoT).

Whether you read about it in a news article, saw it on a TV commercial or demoed it at a technology conference, you’ve probably had at least one interaction with cognitive technology as it relates to modern business. If you’re ahead of the curve, you’ve already begun using it daily.

Since cognitive UEM is such a new concept, very few professionals have the tacit knowledge or years of experience required to determine how effective use cases are. Before everyone begins exclaiming that they’re taking a cognitive approach to solve their biggest challenges, let’s first take the time to examine what constitutes cognitive computing to better understand how it’s changing the way we work.

Watch the on-demand Webinar With Forrester Research

What Does It Mean to Be Cognitive?

The Oxford English Dictionary defines cognition as “the mental action or process of acquiring knowledge and understanding through thought, experience and the senses.” The term has evolved in the context of modern-day business as artificial intelligence (AI) became integral for behavior modeling, data crunching and predictive analytics. Cognitive systems can analyze massive amounts of data generated through endpoints such as smartphones, tablets, laptops, desktops and IoT devices. These systems offer diagnostic, predictive and prescriptive analytics tools that observe, learn and offer insights.

Unified endpoint management is mission-critical for enterprises seeking to achieve business transformation heading into the next decade. Although all UEM tools simplify day-to-day processes for IT administrators by bringing everything under one roof, the process of assimilating data gathered across various types of endpoints has become no less complicated.

With more devices in use than ever before, and an expected explosion in the number of endpoints with the rise of the IoT, data analysis poses significant challenges for those looking to achieve effective management and security. Cognitive UEM solutions can help analysts make sense of the massive amounts of data generated by endpoints and their users, apps and content.

According to the new thought leadership paper, “Mobile Vision 2020,” a commissioned study conducted by Forrester Consulting on behalf of IBM, “the IT and security pros surveyed recognize the value of applying AI/cognitive computing to their organizations’ endpoint data, with the majority indicating it plays a very important or critical role in their endpoint management (76 percent) and endpoint security (83 percent) strategies.”

A Day in the Life Without Cognitive UEM

Perhaps the best way to recognize the value of cognitive technology is to venture into a day in the life of a UEM administrator without it. Tasked with managing multitudes of endpoints across all operating systems and form factors, IT professionals must continually read up on information about multiple operating systems, millions of apps, and looming threats and vulnerabilities.

With this information, analysts must identify opportunities and threats that can improve or potentially hinder productivity and the overall user experience. Combined, there are over 3 million public apps available in the Apple App Store and Google Play that can be assessed for productivity benefits. By the same token, there are millions of apps unknown to these app stores that could potentially infect applicable endpoints. There is a significant amount of structured and unstructured data — internal and external to corporate environments — that, if left undiscovered, could hinder an organization’s performance and reputation.

Now imagine that you work for a global organization with over 5,000 employees accessing corporate data through their laptops, smartphones and tablets, running countless applications and different operating systems. The amount of data generated through connected devices in this scenario is to the tune of 100,000 events per day alone. Multiplexing these events across millions of apps, multiple endpoint management policies, and ever-evolving threats and vulnerabilities, the diagnoses and prevention of incoming threats is of critical importance. Ensuring a risk-free security posture, as well as leveraging the latest and greatest UEM and OS capabilities within the ever-evolving management paradigms, suddenly seems like a tedious task.

So how do UEM administrators discover, diagnose, predict and prevent risk exposures, and identify the impact of opportunities within their environment? According to the Forrester paper, “over 80 percent will implement AI/cognitive computing by 2020 to analyze the vast — and increasingly growing — volume of endpoint data they collect.”

Enabling Endpoints, End Users and Everything in Between

Cognitive computing and AI support two distinct features that help the UEM administrator. The first is natural language processing (NLP), which is the capture and identification of data. NLP parses the datasets and identifies relevant information that could potentially impact target entities, such as devices and their apps. The second key feature is machine learning, the ability to see data patterns and predict outcomes by analyzing historical patterns or through training on relevant data.

Leveraging these distinct features, cognitive computing correlates external sources, including data on active threats such as zero-day vulnerabilities and malware, the latest updates to operating systems, social media posts on Twitter, blogs and analyst reports to identify relevant insights by analyzing the near real-time posture of endpoint devices.

With cognitive UEM, IT professionals can mitigate risks while jumping on opportunities that improve end-user productivity, with minimal business impact and at a reduced cost. The Forrester study noted that “investment in AI/cognitive computing will increase by greater than 300 percent in 2017 compared with 2016.”

Elevating Your Security Strategy Before 2020

Now that you know what it’s like to manage an endpoint and mobile environment with and without cognitive UEM, which approach will you choose? No matter what path you take, bear in mind that this is an evolving field and we will see regular progress as we move ahead.

Watch our on-demand webinar, “Forrester Forecasts 2020: Is Your Mobile Strategy Aligned?” to learn more about the biggest trends heading into the next decade: UEM, IoT and cognitive/AI. Wes Gyure, IBM MaaS360 portfolio offering manager, and special guest Chris Sherman, senior analyst at Forrester, share top considerations for each as you craft your transformational strategy.

More from Artificial Intelligence

ChatGPT 4 can exploit 87% of one-day vulnerabilities: Is it really that impressive?

2 min read - After reading about the recent cybersecurity research by Richard Fang, Rohan Bindu, Akul Gupta and Daniel Kang, I had questions. While initially impressed that ChatGPT 4 can exploit the vast majority of one-day vulnerabilities, I started thinking about what the results really mean in the grand scheme of cybersecurity. Most importantly, I wondered how a human cybersecurity professional’s results for the same tasks would compare.To get some answers, I talked with Shanchieh Yang, Director of Research at the Rochester Institute…

How cyber criminals are compromising AI software supply chains

3 min read - With the adoption of artificial intelligence (AI) soaring across industries and use cases, preventing AI-driven software supply chain attacks has never been more important.Recent research by SentinelOne exposed a new ransomware actor, dubbed NullBulge, which targets software supply chains by weaponizing code in open-source repositories like Hugging Face and GitHub. The group, claiming to be a hacktivist organization motivated by an anti-AI cause, specifically targets these resources to poison data sets used in AI model training.No matter whether you use…

How to embrace Secure by Design principles while adopting AI

5 min read - The rapid rise of generative artificial intelligence (gen AI) technologies has ushered in a transformative era for industries worldwide. Over the past 18 months, enterprises have increasingly integrated gen AI into their operations, leveraging its potential to innovate and streamline processes. From automating customer service to enhancing product development, the applications of gen AI are vast and impactful. According to a recent IBM report, approximately 42% of large enterprises have adopted AI, with the technology capable of automating up to…

Topic updates

Get email updates and stay ahead of the latest threats to the security landscape, thought leadership and research.
Subscribe today