How AI can make user support more proactive

AI

Corporate users have been interacting with artificial intelligence for years, but most people are not always sure how to take advantage of the opportunity AI presents. That’s changing as AI’s new prominence offers compelling ways to solve some important IT issues and challenges.

AI represents an opportunity for “magic” across a number of scenarios, most notably in user support for IT issues both at home and in the office. Few people look forward to calling corporate tech support to fix PCs, tablets, phones and printers. And that’s understandable. While there are many new support options to make the experience more personable and convenient, we have all heard stories of coworkers waiting on hold, answering obvious questions such as “Have you turned it off and back on again?” and then waiting for corporate IT to dispatch the on-site tech for help.

During these frustrating scenarios, workers experience a tangible loss in productivity, at times made worse by their own attempts to resolve the problem. People don’t need these types of delays, particularly when they have to get the job done or their team or supervisors are waiting for results.

The Promise of AI

AI brings new hope and offers the potential to address this flawed experience. After all, the best user experiences are the ones that never happen in the first place.

Wouldn’t it be nice if problems were identified early, resolutions presented proactively and expectations (of service experience) managed actively? By combining automation with artificial intelligence, we can potentially create a user support model aligned with user needs.

It is not as simple as plug in AI and go. For AI to transform the user experience, an AI-powered support service must combine knowledge and operational processes with a set of tools and smart capabilities.

AI requires a vast, comprehensive knowledge base that’s well-organized, well- maintained and complete with resolutions. These are key elements for both teaching the system, as well as providing information that facilitates problem recognition and resolution. Without this knowledge base, the AI system will be as clueless as many of the users. With partial data, or a poorly trained system, AI will offer misleading information and send the IT staff down incomplete or multiple random paths. Comprehensive knowledge must also be integrated with support processes and the resolution engine. Regular updates to the body of knowledge feed in new problems and resolutions, and reinforce learning.

Having effective operational processes enables the system to use analytics and pattern recognition that can identify potential solutions and relevant trends before they become impactful problems. When we look at the system holistically, we can start to see cross-country or cross-organization issues that may also impact other clients. With a strong problem-management capability, we could use machine or artificial intelligence to automatically triage an issue and route the problem to the right department for action or resolution. Efficient and effective processes also ensure better problem diagnosis, which means corporate IT could resolve issues before some locations are ever impacted.

Truly Proactive

Finally, with a set of smart capabilities and AI-enabled tools, enterprises could rapidly recognize, classify, search and resolve many of the common IT issues. And in instances where the system can’t resolve an issue automatically, or where the user is upset or angry, it could hand the problem off to a human with enriched contextual information.

How does AI and support change all this? As we add intelligence to a mature support process, our world changes. Users could engage with a human or a chat bot that knows who the users are and what apps and devices they use. When a user talks, conversational AI helps define what resolutions may work for the user.

Chat sessions could start to present potential solutions, including confidence ratings so users know these are the resolutions they need. Better still, if issues are identified early, they could be resolved quickly. These same tools and processes could apply to other IT areas like order fulfillment, procurement and dispatch, and also to problems and requests like HR, Payroll or Facilities. Things will go wrong, but when they do, AI can make the support experience better.

And while AI can help, organizations still need to integrate knowledge, operations and a set of analytics, tools and automation. The next blog will cover how organizations can use all of these tools to set the stage for making more effective use of AI.

Have a look at more of Marc Wilkinson’s thoughts in Wired Magazine.


Marc Wilkinson

Marc Wilkinson, DXC Technology’s chief technology officer for Workplace and Mobility, focuses on bringing innovation and consumer-like experiences to enterprise work to enable an organization’s employees to be productive wherever and whenever they need, without compromising security or usability. Marc leads the development of technology strategy for support services, digital workplace, enterprise mobility services and productivity, unified communications and campus networking. He also collaborates with product management leaders on the transformative services and capabilities needed to enable organizations to become modern enterprises. He previously was responsible for the Enterprise Mobility, Managed Workplace and Networking Services portfolio for Hewlett Packard Enterprise. marc.wilkinson@dxc.com

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  1. […] the axiom from the last blog: “The best support experience is the one your user doesn’t have.” Users don’t want to deal […]

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  2. […] How AI can make user support more proactive […]

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