Chatbots Create a Smarter and More Efficient ITSM Experience

55% of all large enterprises will have deployed at least one bot or chatbot in production and AI augmentation will generate $2.9T in business value and recover 6.2B hours of worker productivity by 2021. – Gartner

Chatbots – Future of IT Support

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Of the businesses want chatbots by 2020
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Of support capacity will be freed up by IT service desks utilizing machine learning enhanced technologies
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of level 0 & 1 requests are repetitive in nature and can easily be taken care by Chatbots

Use of Chatbots in ITSM and IT Support

The current use of Bots is still at a nascent stage where they are being used to handle common tasks. Given the volume of transactions and tickets raised in an enterprise setup, it becomes impractical for humans to support such operations. Automation of predictable, common support requests is the need of the hour and with the advancement in AI, ML and NLP, Organizations can expect a drastic increase in usage. Early adopters are witnessing tangible benefits in terms of cost, time and overall efficiency of their IT Operations.

Improved self-service quality

Chatbots can take care of routine incidents and service requests while providing a swifter service. Few smaller tasks like Categorization, prioritization and assignment of tickets

can easily be taken care by Chatbots and both customers and IT staff get benefit from this.
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Cost optimization

Chatbots, as with self-service, reduces the costs related to handling routine tasks and increases IT staff efficiency by engaging them in more productive work.

24/7 support availability

Chatbots leveraging artificial intelligence allow IT service desks with staff and/or cost limitations to offer around-the-clock service, self-service support. This 24/7 availability also means that response and resolution times are improved, as

is productivity.
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AIOps and Decision Support

With the use of Chatbots Advanced AI analytics, ITSM and IT Staffs can proactively detect, diagnose and address problems. With the advancement and utilization of the predictive capabilities of machine learning algorithms, it

helps them to make better, informed and data-driven decisions.
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