Defining Cognitive Systems Roles in the Business

By: Bill Kleyman| - Leave a comment

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One of the hottest conversation points in IT today revolves around smarter networks, smarter technologies, and new – evolving- cognitive systems. New technologies around cognitive systems and artificial intelligence are already impacting organizations in a variety of industries. According to IDC, widespread adoption of cognitive systems and artificial intelligence (AI) across a broad range of industries will drive worldwide revenues from nearly $8.0 billion in 2016 to more than $47 billion in 2020.

“Software developers and end user organizations have already begun the process of embedding and deploying cognitive/artificial intelligence into almost every kind of enterprise application or process,” said David Schubmehl, research director, Cognitive Systems and Content Analytics at IDC. “Recent announcements by several large technology vendors and the booming venture capital market for AI startups illustrate the need for organizations to be planning and undertaking strategies that incorporate these wide-ranging technologies. Identifying, understanding, and acting on the use cases, technologies, and growth opportunities for cognitive/AI systems will be a differentiating factor for most enterprises and the digital disruption caused by these technologies will be significant.”

IDC went on to point out that the industries that will invest the most in cognitive/AI systems are banking and retail, followed by healthcare and discrete manufacturing. Looking ahead, healthcare and discrete manufacturing will deliver the greatest revenue growth over the 2016-2020 forecast period, with CAGRs of 69.3% and 61.4%, respectively. Education and process manufacturing will also experience significant growth over the forecast period.

With this in mind, imagine if you had a cognitive IT model that delivered unmatched service quality, reduced downtime, optimized operating costs, provided pervasive security, and increased business agility and innovation with a continual pipeline of new functionality.

This is the new reality when it comes to work with new types of advanced – smart – IT models.

And, it doesn’t stop there. “AI is changing the way in which organizations innovate and communicate their processes, products and services,” said Whit Andrews, vice president and distinguished analyst at Gartner. “AI continues to drive change in how businesses and governments interact with customers and constituents.” The Gartner report when on to state that by 2020, 20% of companies will dedicate workers to monitor and guide neural networks.

So, how can a cognitive IT model help you out? There are some core benefits to be aware of.

  • Agility. Let’s look at something like DevOps for a minute. Agility is augmented even further when that platform supports the entire solution lifecycle and enables a DevOps approach of continuous delivery into hybrid cloud environments. Here’s the important point to remember: Agile businesses require agile IT. However, it’s not always easy to consume IT, align with the business, and still increase agility. When this complexity is compounded by accelerated business cycles, people alone cannot manage the environment. So, for example, to deal with the challenges of managing IT services in a hybrid environment, IBM has augmented its service delivery with the advanced automation, analytics, and cognitive capabilities of Watson.
  • Enabling True IT-as-a-Service. When you deploy smarter systems, your IT environment will absolutely thank you for it. In fact, we’re so used to doing things manually, that a lot of IT leaders forget that there is a better way. So, when you combine a cognitive IT model to IT – you can enable a smarter, faster, ITaaS architecture. From there, ITaaS optimizes the planning, selection, delivery, and management of a multi-sourced, hybrid environment. It provides the framework, processes, and software tools to help enable self-service provisioning, service orchestration, and consumption governance of hybrid environments so that each workload can run at its optimal location and cost.
  • Business and IT Automation. Not only can you leverage cognitive systems to learn more about your business and IT process, you can also automate quite a bit of it by leveraging data, analytics, and a platform that drives innovation. Technological facilitation of the automation of repetitive tasks is a proven optimization approach, allowing your business to respond quickly to situations while increasing compliance, stability, and overall consistency and quality of service. There are a variety of technologies for automating with both depth and breadth – from event management and diagnosis to process orchestration.

Moving forward, competitive advantages will be gained by leveraging smarter and faster IT models. Cognitive systems allow your platform to align with the business model to bring real-world agility and intelligence into your architecture. These types of systems help you understand how your data interacts at an IT and business level. From there, you can use systems like IBM Watson to make powerful decisions; helping you keep a competitive edge.

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About The Author

Bill Kleyman

CTO at MTM Technologies

Bill is an enthusiastic technologist with experience in datacenter design, management, and deployment. His architecture work includes large virtualization and cloud deployments as well as business network design and implementation. Bill enjoys writing, blogging, and educating colleagues around everything that is technology. During the day, Bill is the CTO at MTM Technologies, where he interacts with enterprise organizations and helps align IT strategies with direct business goals. Bill’s whitepapers, articles, video blogs and podcasts have been published and referenced on InformationWeek, NetworkComputing, TechTarget, DarkReading, Data Center Knowledge, CBS Interactive, Slashdot, and many others. Most recently, Bill was ranked #16 in the Onalytica study which reviewed the top 100 most influential individuals in the cloud landscape, globally.

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