Automate HR applications using AI and ML

HR TECH CHATBOTS - GUIDE TO AUTOMATE
HR APPLICATIONS USING AI AND ML
Harbinger Systems

© 2017 Harbinger Systems | www.harbinger-systems.com 2
Speaker Introduction
Shrikant Pattathil Maheshkumar Kharade
President
Harbinger Systems
AGM - Technology
Harbinger Systems

© 2017 Harbinger Systems | www.harbinger-systems.com
Agenda
AI and ML Trends
Chatbots in HR Tech
Machine Learning in HR Tech
Benefits and Challenges
Summary

POLL

AI and ML Trends

Top 3 trends that will be part of most applications in 2018
Conversational interfaces (support, FAQs, simple workflows)
AI enabled recommendation engines (recruitment, engagement)
Self service reports (integrated BI tools, dynamic data correlations)

Chatbots in HR Tech

Web Mobile Conversational
8
Evolution of Interfaces

What is a Chatbot?
Automates routine and simple workflows
Uses natural language processing
Has learning capabilities (Machine Learning)- ability to add new workflows
Delivered through multiple channels like Skype, Slack, Email, Web…
Chatbot is an AI application with a conversational interface, that

Core HR
(Time Off,
Ticketing)
Recruitment
(Status Updates,
Scheduling)
Employee
Engagement
(Surveys)
FAQs
(I9, Benefits)
HR Tech – Chatbot applications
Any other HR applications or workflows that you think would be a good use case for chatbots?

Demo – Time Off Bot

Building blocks of a Chatbot
Natural
Language
Processing
Intents
Utterances
Vocabulary
Interpretation
Bot Framework
Business Logic
Workflow
App Platform
Enterprise Apps
HRIS
ATS
CRM
Integration
Conversational
Interface

Workflow of Chatbots
1
2
3
4
5
6

Machine Learning in HR Tech

HR Tech- ML applications
Recruitment
(Recommendation Engine,
Pattern Matching)
Employee Engagement
(Sentiment Analysis)
Core HR
(Succession Planning,
Anomaly Detection)

ML application- Problem Statement
“Harbinger’s talent management executive needs to hire a candidate with a
particular skillset. As per our companies policy, he needs to create a panel of
interviewers to conduct the interviews. Since, he is new to the company, he
doesn’t know all the interviewers. Also, he isn’t well versed with the skillset
requirements and its dependencies.”

Demo- “Recommendation Engine” for
Interview Panel Selection

Understanding and analysis of
business problem
Data source search, extraction and transformation
Model selection and application
Prediction Visualization Integration
Building blocks of a ML Application

Benefits and Challenges

AI and ML Applications- Benefits
For Employee
For HR
 Provides shorter and simpler workflows
 Provides in context assistance
 Facilitates better compliance
 Improves self service capability
 Enables new workflows (reduces dependence on programming)
 Improves productivity of HR Reps (focus on more complex tasks)

AI and ML Applications- Challenges
Achieving balance between functionality, accuracy and length of interaction
Humanization of overall experience
Addressing privacy and security concerns
Gathering data from multiple sources
What challenges have you encountered while using a chatbot or AI application in your enterprise? If you
haven’t used one yet, what roadblocks do you foresee?

Summary

Recap
Conversational
interfaces (Chatbots)
• Automation of
simple workflows
ML enabled
applications
• Leveraging
historical data to
make intelligent
recommendations
Challenges
• Finding the right
business case
• Dependency on
data

Thank you
24
Contact Us
Shrikant Pattathil – shrikant@harbingergroup.com
Maheshkumar Kharade – maheshkumar@harbingergroup.com

Automate HR applications using AI and ML

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