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Testimonial: I have found that the new HDAA Knowledge Base reduces the time it takes me to research industry stats & reliable information for the ITSM sector. It’s easy to use search functionality encompassing KCS principles, helps to filter & tailor my searches more accurately & there are numerous new services now available through the website. Every time I return to the site there is new information published. Very impressive.
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The utility, efficacy, and viability of traditional IT management solutions have plateaued for a variety of reasons, including costs, productivity issues, and scarce talent, to name just a few. Organizations may think they are saving money by keeping their legacy infrastructure, but it brings a high maintenance cost. Meanwhile, IT staff now has hundreds of thousands of assets and endpoints to manage—all at a time when IT talent is in short supply.
To address these factors, many organizations are turning to artificial intelligence, automation, and machine learning. Artificial intelligence and machine learning offer a lot of opportunities to address these dueling situations and help improve IT service management overall. Let’s examine the challenges that organizations are facing with respect to IT operations, as well as examples of how IT managers and directors can implement AI to improve their operations.
Starting in 2006, several breakthroughs in technology enabled the widespread use of AI and machine learning: a reduction in the need for computing power, inexpensive parallel computing, and the arrival of the huge datasets needed to train AI. Organizations can now create Systems of Intelligence that address business challenges and objectives. For IT and Enterprise Service Management, this includes objectives like improved customer experience, increased employee productivity, optimized operations, and reduced risk.
These technologies hold huge potential: Forrester Research has predicted that by 2020, businesses that use AI and other emerging technologies will capture $1.2 trillion a year from their peers who don’t. Similarly, Gartner predicts that in 2021, AI augmentation will generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity.
Even though AI and automation are used interchangeably, there are significant differences between complexity level of both systems. Automation, as the name suggests, is about automating certain manual tasks in a repetitive, error free manner without human intervention. Automation is basically making hardware or software that can do things automatically, without human intervention.
Artificial Intelligence, as defined by John McCarthy in 1956, however, is to make machines emulate human activities by use of language, form, abstractions, and concepts, to solve problems typically reserved for humans, and to improve themselves.
AI-driven automation can bring a lot of benefits where AI is doing the decision making and automation is executing the actions in a repeatable manner. Together they can bring a lot of benefits to ITSM:
GTAA, which operates Toronto Pearson International Airport, provides a great example of the benefits of AI-enabled ITSM. Toronto Pearson serves almost 50 million passengers each year, making it Canada’s busiest airport.
GTAA is responsible for a myriad of operational details across the board and faces many daily
With only 1,600 of its 50,000 employees handling management, operations, and IT, the workload was keeping team members from addressing some tickets in a timely manner.
The organization adopted an AI-based ITSM solution to help improve its service. The resulting automated, rule-based workflow management ensures that maintenance issues are addressed before they become passenger safety issues. The solution also enabled them to deliver enhanced customer experience, faster resolution of tickets, and an improved CSAT.
Enhanced reporting provided deeper operational insight and helped drive proactive and prescriptive problem management. A highly intuitive service desk screen has resulted in a First Call Resolution of up to 81%, and a fully automated employee onboarding and termination service catalogue has reduced the total cycle time substantially.
The complexity of today’s IT landscape and the volume of assets and endpoints make the transition from human to machine scale necessary. The combination of AI and automation is changing the game by not only replacing or improving existing manual processes but also adding intelligence to IT management tasks. This leads to faster ticket resolution, better management and use of assets, much improved customer experience, and streamlined operations.
As chief product officer at Symphony Summit, Dr. Akhil Sahai heads product management and marketing, leveraging more than 20 years of experience in product strategy and management marketing and business development. Previously, he was the chief product officer at LexisNexis. Prior to that, he led early-stage AI/machine learning-based start-up Perspica Inc. to successful acquisition by Cisco; initiated, funded, and managed enterprise-wide solutions programs at HP; and worked in product management at VMWare, where he launched vCloud software. Akhil received his PhD in computer science from INRIA France and his MBA from the Wharton School of the University of Pennsylvania. He holds 17 technical patents, has authored a book, and has written more than 80 peer-reviewed articles.
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