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

Autonomous security for cloud in AWS: Harnessing the power of AI for a secure future

3 min read - As the digital world evolves, businesses increasingly rely on cloud solutions to store data, run operations and manage applications. However, with this growth comes the challenge of ensuring that cloud environments remain secure and compliant with ever-changing regulations. This is where the idea of autonomous security for cloud (ASC) comes into play.Security and compliance aren't just technical buzzwords; they are crucial for businesses of all sizes. With data breaches and cyber threats on the rise, having systems that ensure your…

Cybersecurity Awareness Month: 5 new AI skills cyber pros need

4 min read - The rapid integration of artificial intelligence (AI) across industries, including cybersecurity, has sparked a sense of urgency among professionals. As organizations increasingly adopt AI tools to bolster security defenses, cyber professionals now face a pivotal question: What new skills do I need to stay relevant?October is Cybersecurity Awareness Month, which makes it the perfect time to address this pressing issue. With AI transforming threat detection, prevention and response, what better moment to explore the essential skills professionals might require?Whether you're…

3 proven use cases for AI in preventative cybersecurity

3 min read - IBM’s Cost of a Data Breach Report 2024 highlights a ground-breaking finding: The application of AI-powered automation in prevention has saved organizations an average of $2.2 million.Enterprises have been using AI for years in detection, investigation and response. However, as attack surfaces expand, security leaders must adopt a more proactive stance.Here are three ways how AI is helping to make that possible:1. Attack surface management: Proactive defense with AIIncreased complexity and interconnectedness are a growing headache for security teams, and…

Topic updates

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