You may have already read a lot of studies and white papers about bots, chatbots and intelligent virtual agents. Confusing, right ? Because unless you have directly been involved in a conversational AI project, the difference between those technologies might not be clear. So to give you the fundamental principles, here are 4 main characteristics of an Intelligent Virtual Agent (or IVA).
This is based on our experience since 2017, building a conversational AI platform and Virtual Agent solutions. Konverso has been named a top player in Everest Group's report on Intelligent Virtual Agents, both in 2019 and 2020, a recognition of our continuously improving capabilities in the field of natural language processing and Machine Learning.
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Intelligent Virtual Agents are conversational bots capable of assisting humans in a variety of tasks from the IT helpdesk to HR and Finance. Those conversational skills are powered by cognitive process automation and natural language understanding, a subset of artificial intelligence that mimic the way the human brain works - to assist humans in making decisions, completing tasks, or meeting goals.
Cognitive Process Automation uses technologies such as natural language processing (NLU/NLG), image processing, pattern recognition, and - most importantly - contextual analysis to make more intuitive leaps, perceptions, and judgments for better speech recognition
In short, an Intelligent Virtual Agent is not a basic bot that will only feed the user a limited set of preregistered answers.
A Virtual Agent’s conversational skills enables better language understanding of the user, ask additional questions to understand a context (who the user is, his role in the organization) and orchestrate multiple actions.
Focused on end-user experience
A traditional chatbot can usually manage chat or email conversation with humans. But a Virtual Agent can offer multichannel integration to be reachable through the channels users are most comfortable with (live chat, voice or call bot, etc.). This includes phone and enterprise digital workplace solutions such as Microsoft TEAMS.
It might surprise you to know that in many IT helpdesk scenarios, the telephone is still the preferred channel for users (72% of users would rather call their IT help desk than use self-serve solutions like a portal). That’s why AI powered voice technologies (voicebot/callbot), in different languages, are also crucial to ensure that users feel comfortable reaching a call bot.
And because human expertise is always valued, a Virtual Agent can also act as an additional digital workforce to assist human specialists. For instance, ITSM specialists for IT support triage or complex requests.
Synergies with other technologies
Virtual Agents can work in synergy with other digital and automation technologies, including RPA (Robotic Process Automation), IoT (Internet of Things), and analytics.
Let’s focus on RPA. Because when Virtual Agents and RPA work together, in an integrated end-to-end automation solution, it can increase operational efficiency and business agility. A perfect example of this IVA + RPA approach is the implementation of a self-service for password reset.
According to Gartner, managing password reset or account lockout generates 40% of helpdesk calls. Enabling the users to reset their password by simply calling an Intelligent Virtual Agent can save 70% to 90% of the help desk costs associated with passwords.
In this scenario, the IVA can qualify the incident, assist the user in the resolution of his problem, unlock the account or create a new password, in collaboration with an RPA solution to generate the validation emails. For more information about Cognitive Process Automation and how it can be integrated with RPA, you can check this dedicated blogpost.
Capable of automated learning
A Virtual Agent can be very smart from day one, through the integration of Knowledge bases (for instance from Upland RightAnswers, ServiceNow, Confluence, etc.), existing Q&A / FAQ, and connexions to Digital Workplace tools like Microsoft Sharepoint.
But what makes an IVA approach really valuable in an enterprise environment is its machine learning ability to improve over time by studying automatically from human conversations.
This automated learning capability might be the most important factor to really understand what an IVA is, or should be. Because ultimately, what is at stakes here is the end-user experience and satisfaction, a factor that can make or break any technological project.
This end-user experience is in constant evolution, with new tools and methods that employees need to master quickly to maximize productivity. That’s why a Virtual Agent needs to be agile, evolutive, and generate more value over time, as it collects and analyses more data from its interactions with employees.
Example of use cases for an Intelligent Virtual Agent
Now that we have defined what an Intelligent Virtual Agent is, we can start thinking about the possible use cases in the enterprise.
In the field of IT Service Desk, we can list 5 major Intelligent Virtual Agent scenarios, some initiated by the end-user and others by the Virtual Agent.
Those scenarios are always a two-way conversation where the Virtual Agent is able to understand questions and reply, but also to handle context-switching and digressions that are inherent to human conversations. This means that even if a user skips some questions, the Virtual Agent will not be stuck in a scenario but adapt in real time to the conversation and answer questions.
3 types of scenarios initiated by the end-user : self-service password reset, IT requests and Troubleshooting, but also Assistance on configuration tasks, aka “How to” questions.
The conversation flow can also be initiated by the Virtual Agent to send an important message to the users.
2 types of scenarios initiated by the Virtual agent : communicating on the Virtual Agent’s field of action, and communicating on programmed maintenance and outages.
We have dedicated another article to detail those different use cases, illustrated by actual conversations between the Virtual Agent and end users.
All those use cases for Intelligent Virtual Agents can help improve employee productivity, boost the usage of digital Workplace tools and reduce IT Service Desk costs. But the best use cases and quick wins will depend on your own users’ needs and pain points.
With Konverso’s virtual agents, our clients increase end-users satisfaction by 80%.