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Ai in HR Tech: Trends, Use cases, and Demos

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A webcast on ‘AI in HR Tech: Trends, Use Cases and Demos’ by Harbinger Systems with HR.com to share insights about,
1. Trends and use cases of AI-enabled HR Tech applications.
2. How AI-enabled applications are enhancing candidate, practitioner and employee experience.
3. Key benefits and challenges in implementing AI-enabled applications.

Publié dans : Recrutement & RH
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Ai in HR Tech: Trends, Use cases, and Demos

  1. 1. AI in HR Tech: Trends, Use cases and Demos Harbinger Systems in association with HR.com December 11, 2018
  2. 2. © 2018 Harbinger Systems | www.harbinger-systems.com 2 Speaker Introduction Shrikant Pattathil Maheshkumar Kharade President Harbinger Systems AGM - Technology Harbinger Systems
  3. 3. © 2018 Harbinger Systems | www.harbinger-systems.com Agenda Key AI Trends in HRTech Demos and use cases of AI enabled applications Challenges faced in leveraging AI features and how to overcome those? Summary
  4. 4. Poll #1 What best describes your role? • Practitioner • Product Vendor • Service provider (consultant, implementation, etc) • Other How many employees are there in your organization? • 1 – 250 • 250 – 1000 • 1000 - 5000 • 5000+ Poll #2
  5. 5. © 2018 Harbinger Systems | www.harbinger-systems.com Key AI Trends in HRTech
  6. 6. © 2018 Harbinger Systems | www.harbinger-systems.com Key AI Trends in HRTech – Harbinger Analysis Ref: The State of AI in HR 2018 industry research (preview) by HR.com Talent Acquisition Training and Development Performance Management Time and Attendance Higher AI Adoption Lower AI Adoption Benefits, Payroll and Others.. Virtual Assistant Recommendation Engine Pattern Recognition Analytics Trend Dashboard Anomaly Detection Predictive Analytics
  7. 7. © 2018 Harbinger Systems | www.harbinger-systems.com Question #1 –Are you using AI in any other HR apps or modules?
  8. 8. © 2018 Harbinger Systems | www.harbinger-systems.com Demos and use cases of AI enabled applications
  9. 9. © 2018 Harbinger Systems | www.harbinger-systems.com Example #1: Course Discovery Chatbot
  10. 10. © 2018 Harbinger Systems | www.harbinger-systems.com Example #2: Chatbot solution for improving efficiency of Ticketing System About Customer • A US based technology company employing over 100K employees worldwide • Employees include skilled engineers, unskilled staff, contract staff and senior managers HR ticketing situation • Average 1300 tickets daily from employees • Limited number of HR and Support reps • Stringent SLAs • As a result, long wait times, unsatisfactory resolutions, increased anxiety and escalations. Solution for situation • A Chatbot that can handle routine HR requests without bothering the HR staff • Chatbot that integrates with popular channels like (Skype, Phone) • Chatbot that understands different languages, dialects and expressions • Chatbot that can connect with HR staff if needed Result • Significant improvement in ticketing productivity • HR reps focused on complex requests • Less anxious and more excited employees • Continuous analytics of Chatbot performance for betterment of service models • Bot auto trained on request resolution
  11. 11. © 2018 Harbinger Systems | www.harbinger-systems.com Chatbot training workflow 1 2 3 4 5 6
  12. 12. Poll #3 Are you seeing value being derived from the ‘AI features” of the HR applications that you are currently using? • Yes • No • Don’t know
  13. 13. © 2018 Harbinger Systems | www.harbinger-systems.com Challenges faced in leveraging AI features and how to overcome those?
  14. 14. © 2018 Harbinger Systems | www.harbinger-systems.com 14 Challenges Gathering (Multiple Sources) Cleansing Anonymizing Organizing Raw data transformation to good AI data Good Data Right Model Better AI Getting “Good Data” is the biggest challenge and most time consuming! Data processing is unique to each organization
  15. 15. © 2018 Harbinger Systems | www.harbinger-systems.com Example #1: Training data automation for Chatbot
  16. 16. © 2018 Harbinger Systems | www.harbinger-systems.com Demo
  17. 17. © 2018 Harbinger Systems | www.harbinger-systems.com Example of an application to generate questions (better quality training data) Submit Content Copy your content into Quillionz. Choose Keywords Tell Quillionz which keywords are important for question creation. Review Content Review and edit your content to get it ready for the Quillionz AI engine. Get Question Ideas Get quality question ideas within seconds, and tweak them as you wish. Case/Ticket Details Domain specific corpus Expert Review FAQs
  18. 18. © 2018 Harbinger Systems | www.harbinger-systems.com Example #2: Custom AI component for Talent acquisition
  19. 19. © 2018 Harbinger Systems | www.harbinger-systems.com Use case - Custom AI component for Talent acquisition Analytics Position Area Compensation Custom Component Job and Compensation Data NLP Based Parser Connector Data Cleansing Machine Learning DB
  20. 20. © 2018 Harbinger Systems | www.harbinger-systems.com Summary
  21. 21. © 2018 Harbinger Systems | www.harbinger-systems.com 21 Recap AI in HRTech • Higher adoption of AI in Talent acquisition, Training and development, Performance Management and Time and Attendance Challenges • Access to data from multiple sources • Provide continuous training to underlying AI models • ONE-SIZE-FITS-ALL solution approach not applicable for all organizations Key to success • Supporting applications or custom solutions for sourcing and processing of internal and external data
  22. 22. © 2018 Harbinger Systems | www.harbinger-systems.com QnA Please use Question Box
  23. 23. © 2018 Harbinger Systems | www.harbinger-systems.com Thank you 23 Contact Us Shrikant Pattathil – shrikant@harbingergroup.com Maheshkumar Kharade – maheshkumar@harbingergroup.com
  24. 24. © 2018 Harbinger Systems | www.harbinger-systems.com 24 Use Case – NLP based Resume Parser “Harbinger’s talent management executive needs to hire a candidate with a particular skill set. For every job position, they receive 1000s of resumes having a lot of variability and ambiguity in the language used. In order to match every CV against open job positions, its a time-consuming process as they use conventional resume parsing tools. Most of the resume parsers available today are rule-based and fails to 'understand' the resumes in the context of a given job position”
  25. 25. © 2018 Harbinger Systems | www.harbinger-systems.com Demo

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