One of the most common questions I hear from HR professionals is: What is conversational artificial intelligence (CAI), and how is it different from recruiting chatbots?
Source: FGC / shutterstock
This question isn’t surprising. One of the biggest trends in recruiting over the last few years has been the use of chatbots to help address inefficiencies in the hiring process. Many of these bots are marketed similarly and even sound like CAI, which creates a lot of confusion in the market. But there are profound differences between CAI and other bots, such as the problems they can solve and the way they understand, engage, and support candidates.
The Limitations of Chatbots
Before CAI, there were two main types of chatbots: widgets and enhanced bots. While these legacy bots have helped to improve some inefficiencies in the market, they are limited in use and capabilities.
Chat widgets are the most basic form of communication on a website, enabling live chat among humans. Enhanced bots are a software program that automates conversations with humans to answer their questions but only accepts predefined answers in a multiple-choice format. The conversations with candidates are one way, with a bot serving to provide basic information confined to very specific tasks.
Building Relationships with CAI
CAI, also known as intelligent bots, serves a broader and deeper purpose: to help organizations build strong online relationships with candidates. Using AI and advances in natural language processing, CAI engages with applicants in ways not possible with legacy bots—dramatically improving the online candidate experience.
Building strong relationships with candidates is core to hiring the best talent—and it often starts as soon as an applicant lands on a career site. But recruiters are overwhelmed with the number of applications they receive, and it can take weeks for candidates to hear back. These inefficiencies can erode trust with candidates in the hiring process and gives applicants time to find other jobs.
CAI eliminates these inefficiencies by embedding directly into your current recruiting workflow, engaging candidates preapplication or even right at the application point—in time to accelerate the hiring process. These advances in technology allow for human-like, dynamic conversations with candidates, with CAI able to follow multiple new threads of topics, acknowledge what’s being communicated, and help applicants navigate toward a goal.
A Natural Feel
Unlike legacy bots, CAI allows candidates to express themselves naturally in conversations, whether they are asking or answering a question, and recognizes nuances in conversations, such as tone and emotion. For example, CAI might ask candidates about their latest skills. Applicants can express themselves in the way they would naturally respond, such as “I am a java programmer” or “I just completed a social media training course.” CAI understands what the candidate is saying and is able to acknowledge and progress the conversation.
CAI also uses machine learning to enable it to learn with experience—with every conversation informing the next one. As the bot collects more data, it gets smarter. For example, if a candidate provides a new skill that is not recognized in a company’s database, CAI will flag it, input it into the database, and recognize it the next time it’s mentioned by another candidate.
Many organizations are seeing multiple benefits from using CAI as their online recruiter, from helping to eliminate the application black hole to enabling recruiters to focus more on higher-value work. Beyond improving efficiencies, CAI is helping companies to create a positive brand experience—which is key to attracting and hiring the best talent. As HR leaders think about how to recruit the best talent, understanding the differences between CAI and other bots will help them make the best technology decisions while also avoiding potential problems. Using CAI can help set recruiters up for success—by building trust and engagement with candidates from the very first interaction.
Vinita is currently VP of Product Marketing at Mya Systems and brings nearly 15 years of domain, product marketing, product management and product strategy expertise from well-known brands including Workday, Rubrik, and Replicon. Mya, the company’s AI-recruiter, was launched in July 2016 and quickly became the industry leader in addressing inefficiencies in recruiting and improving the experience for job candidates and recruiters. Mya Systems has been recognized by CB Insight’s AI 100, Bersin by Deloitte’s 2017 Disruptions Report, and Kairos Society’s K50, among others.
Prior to her career in tech, Vinita worked in the financial services industry for several years as structured credit derivatives trader and structurer. Vinita has a B.S. in Mechanical Engineering, Economics and History from Columbia University, and a Masters in Management Science and Engineering from Stanford University.