Anyone who’s worked in IT service management is well aware of the disappointment that often follows the inflated promises of process automation. The only way ITSM professionals will ever be able to focus on the growing demand for more strategic digital initiatives is to fully automate IT and business processes, not to mention meeting the demands of business users who don’t easily tolerate the errors that often result from manual processes.
The fact is, while process automation has long been promised for ITSM processes such as changes, patch management, incident routing and software deployments, there has always been something lacking in these tools that requires manual intervention. End-to-end automation, it seems, has been more of a claim than a reality.
Today, however, through the combination of digital technologies such as Internet of Things (IoT), artificial intelligence (AI), robotic process automation (RPA) and bots, ITSM automation, or ITSM modernization, as I call it, has taken a giant leap closer to reality.
The capabilities now exist for organizations to leverage AI to automate every level of their IT operations and intelligently automate complex IT tasks. This means IT experts can spend more time innovating and evolving the department to help achieve business goals.
ITSM Must Robotize … or Else
Let’s take a closer look at each of these:
- With IoT and embedded sensors, data collection is dramatically expanded, enabling far more precise data analysis, as well as intelligent auto-routing of incidents and requests.
- With service and chat bots, driven by machine learning, systems can continuously learn to the point where they can predict the failure of infrastructure and automatically provide intelligence and key knowledge to resolve issues quickly.
- Through RPA, service and chat bots can automate high-volume, repeatable tasks that used to require human intervention.
Enabling AI in ITSM
To enable end-to-end ITSM automation, the following AI elements are needed:
- Problem-solving service bot: Automates IT problem solving across the full IT stack of hardware, software, resource and application layers.
Example: We’ve integrated Hubot with ServiceNow to automate tasks such as Windows service restart and Java virtual machine reboots on app servers.
- Knowledge item chat bot: Uses flexible algorithms to leverage human-created knowledge items to determine the shortest route to a solution. Example: We’ve created iVA, a chatbot that provides end users with relevant information when they create incidents, such as a request for a password reset.
- Flexible architecture to incorporate AI: Enables easy integration of AI and the ITSM tool using RESTful web services and streaming application programming interfaces (API). Example: We’ve developed the Integrat’R’ app to facilitate the integration of any AI platform with ServiceNow.
- Machine learning-enabled self-service: Use of a bot that interacts with customers, listens to questions and offers solutions, engages with humans and grows its knowledge base. Example: Our iVA chatbot can assist end users with any question related to service management.
Implementing a Service Bot Framework
We’ve conducted extensive research into enabling full ITSM automation through the use of AI-driven bots. Our specific approach begins by integrating ServiceNow with the Microsoft Bot Framework to provide a virtual assistant solution for the end-user experience and service desk automation by connecting ServiceNow with Skype4B or with IBM Watson, etc.
There are several other technologies, such as Slack, Neva and Drastin, that integrate with ServiceNow to create bots that gather machine learning data to inform the actions and decisions of a virtual assistant.
But before the technology comes into play, it is vital for businesses to ensure organizational readiness to move forward with bot-enabled automation, ideally using an automation assessment and bot adoption framework.
As the intelligence economy unfolds, the use of service and chat bots will only grow more critical, as increased automation will be necessary to drive digital enterprises. By enabling ITSM with AI capabilities, organizations can finally free ITSM professionals to focus on more creative and constructive endeavors that drive business success.
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