Hi, have you heard of Conversational AI or AI Virtual Agents, or AI Chatbot? You sure have. Most of us might have already interacted with them at one point or another.
In this article, we will see how Conversational AI can transform the IT service desk. Let’s get started then.
Throughout the years, CIOs have overinvested in optimizing the value chain: better ticketing software, expensive call-routing processes, and outsourcing to cost-effective geographies and process-centric metrics—all with mixed results.
As more and more services are offered and exposed to business units and employees through Service Catalogs, Service Desks like BMC Remedy, ServiceNow, Cherwell, Zen Desk and more have become inundated by queries, complaints, and calls for assistance. This can make for a significant drain on a company’s resources.
Despite all their cost-saving efforts, Service Desk departments are now underfunded and overloaded.
What Conversational AI Promises?
Conversational AI promises a trifecta of possibilities to disrupt and transform the modern IT Service Desk:
- Automate repetitive tasks
- Accelerate productivity
- Deliver exceptional experiences
Automated Repetitive Tasks
According to Gartner, 40% percent of all service desk requests are password resets for various devices, applications, and IT services.
The voluminous and mundane nature of IT support tickets and the sheer lack of challenges in daily chores are draining the excitement and focus of the team. This often leads to a huge turnover in service desk staff, with the associated complications.
Conversational AI or Virtual Support Agents (VSAs) have now entered the market to rapidly resolve those tedious and repetitive service requests.
Rather than trying to “fill in” for human support staff, they work on simple tasks which constitute majority of customer issues to the service desk. This leaves service agents free to handle more complex and interesting issues.
One such case is when users search for answers. Users are often reluctant to address their own technical issues, even when the solution is just a few steps away. When it comes to searching for answers, the search capability in enterprise knowledge systems is broken. IT teams often resort to hiring people to augment knowledge articles with keywords to help surface relevant results for employees.
In practice, these techniques do not work, because employees describe their issues with symptoms. This approach will most likely result in creating a service request or calling the service desk.
Virtual support agents can guide end-users to solve most of their typical questions on their own with a deep understanding of the user intent and meaning of the question asked using advanced AI (Natural Language Understanding or NLU). It does this by retrieving and exposing to the users only the relevant information or snippet—even though it may be buried in unstructured support web pages or lengthy troubleshooting documents.
Conversational AI goes beyond just information retrieval. By integrating with back-end enterprise systems (configuration management, application access, service catalogs, identity management, workflow orchestrator, and so forth), it can resolve service requests which require the end-to-end execution of cross-system business workflows.
“The selection and serving of how-to knowledge articles by a VSA are not trivial. There is a lot of AI and deep-learning science behind it. In spite of no prior labeling of data, the VSA picks up exactly the relevant article. It understands phrases, sentences and context.” says Uday Birajdar, CEO of AutomationEdge.
Empowered by robotic process automation (RPA) technology, they can address repetitive actions such as unlocking accounts, resetting passwords, and even complex tasks like provisioning an application, troubleshooting email, or resolving VPN connectivity.
These capabilities free up service agents for higher-level tasks to increase their productivity. The virtual assistants are available 24/7. Scaling to higher volumes does not require bringing new headcount, but can be addressed elastically by adding more compute power! The last two years have seen a massive recognition among CIOs that the level-one support is the major cost to the functions and does not account for productivity.
Conversational AI technology has come up as a viable option to provide customer experience with productivity. Currently, global organizations have already deployed the technology in some other way and it is growing in terms of the impact.
Auto-resolution of service requests (self-service requests), reduction of support costs, increase in employee productivity, customer loyalty and satisfaction, plus lower Mean-Time-to-Resolution (MTTR), increase in morale and sense of career growth for support personnel, and lower attrition.
Conversational AI systems that leverage natural language interactions are already considered a main driving force for an IT paradigm shift. According to Gartner, “conversation first” will be adopted by the majority of enterprise IT organizations as the most important new platform paradigm, superseding “cloud first, mobile first.”
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According to Gartner, a typical IT service request gets resolved in 10 hours, costing $15 for each ticket. The process includes multiple conversations with Level 1 agent, sometimes the criticality of the issues needs involvement of the Level 2 service agent or escalating to Level 3 agent.
Conversational AI solutions can now use the abundant history available from existing enterprise knowledge-based systems and interactions—including chat conversations, emails, voice transcripts, transactions, and other pre-existing enterprise data in the IT Service Desk systems— to learn by itself with minimal or no user supervision.
They automatically learn from structured and unstructured data and leverage such knowledge to converse directly with the user. They can discover user intent by means of smooth disambiguation technology and are effective in suggesting, recommending, and tailoring their engagement based on learning.
When the Conversational AI agent fails to auto-resolve the issue, it automatically records the entire conversation, including questions, answers, attempts, and corresponding status. Then categorize and route the request to the right agent with the necessary context and recommendations to accelerate closure of the request.
Conversational AI, to some level, can learn from the conversations and responses to adapt to the user persona. As the number of interactions grows, so the knowledge base of the virtual agent making it smarter and smarter.
Available 24/7, continuously learn and dynamically adapt to cope with today’s and tomorrow’s IT Service Desk challenges.
Deliver Exceptional Experiences
Most of today’s users have a smartphone as a primary medium of accessing IT products for reading emails, browsing the internet, tracking calendars, and chat. And multitasking on smartphones with multiple applications is a common thing. This holds true for IT support as well.
The next-gen users accustomed to instant support and services. They expect instant IT support options like chat with executives via email, chat messenger, voice, or messaging.
The advanced conversational AI technology can make it possible. The virtual agent can be embedded into any of these channels for the instant response to the user round the clock.
Users can engage with virtual agents in a long looped conversation with even multiple devices. Conversational AI technologies have initiated a new turn in human-computer interaction, and this is best seen in deployments on the humble Service Desk.
The ability for AI to both help in a natural language interface to people, while also performing intelligent process automation (Conversational RPA) in the background is key to modern customer service management,” said Muddu Sudhakar, Ph.D., Co-Founder and CEO, Aisera. “Whether fully autonomous for end-users or enhancing service agent tasks with AI-driven RPA workflows, both natural language and machine learning are necessary for a successful CSM system.”
Modern user experience, omnichannel, multi-devices, serve users wherever they are, real-time engagement, consistent experience across channels.
There is more to Conversational AI than what meets the eye. It has a huge potential to transform the customer experiences and help people make their work interesting and productive.
In the next article, we will discuss how organizations are losing this opportunity and in return incurring opportunity costs. What do you think about conversational AI or Virtual Agents? Are you using it in your organization? Let me know in the comments section.