AI_in_HR_Presentation Part 1 2024 0703.pdf

AI In HR

1. The Evolution of HR: Embracing
Artificial Intelligence
Exploring the impact of AI on Human Resources
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2. Introduction
Artificial Intelligence (AI) refers to the simulation
of human intelligence in machines programmed to
think and learn like humans. AI encompasses
various technologies, including machine learning,
natural language processing, and robotic process
automation. In the HR domain, AI is
revolutionizing how we attract, hire, engage, and
retain talent, making processes more efficient and
data-driven.
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3. Historical Context
•Traditionally, HR functions relied heavily on
manual processes, intuition, and subjective
decision-making. The advent of technology
brought about the first wave of automation with
HRIS systems, streamlining tasks such as payroll,
benefits administration, and record-keeping.
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4. Early Days -
Paper and
Pen
•In the early days, HR functions were entirely
manual, relying on paper and pen for record-
keeping, attendance tracking, and other
administrative tasks. This method was labor-
intensive, prone to errors, and inefficient.
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5. Timestamp Machines
•With the industrial era, timestamp machines
were introduced to log employee working hours,
offering a more accurate way to track attendance.
This was a significant improvement, but still
required manual data entry and management.
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6. HRIS (Human Resource Information
Systems)
•The advent of computer technology in the
1980s brought the first wave of HR automation.
HRIS systems digitized basic HR functions like
payroll, benefits administration, and employee
records, improving accuracy and efficiency.
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7. HRMS (Human Resource Management
Systems)
•The 1990s and early 2000s saw the emergence
of more sophisticated HRMS, integrating
multiple HR functions into a single system,
improving efficiency and data management.
These systems allowed for better data analysis
and reporting capabilities.
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8. Digitalization and Advanced Tools
Biometric Systems: Introduction of
biometric systems (fingerprint and
retina scans) for more secure and
accurate attendance tracking.
GPS-Based Attendance: For remote
and field employees, GPS-based
attendance systems provided a way to
log working hours and locations.
Timesheets and Project Allocation:
Automated timesheets and project
allocation systems emerged, helping
organizations manage work hours and
assign tasks based on skill assessments.
Succession Planning: Tools for
succession planning and talent
management became more prevalent,
aiding in the identification and
development of future leaders.
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9. Data Mining and Analytics
in the Mid-2010s
•In the mid-2010s, HR began leveraging data mining
and analytics to gain insights into employee
performance, turnover rates, and recruitment
efficacy. Data mining involved extracting useful
patterns and knowledge from large sets of data,
while data analytics involved applying statistical and
computational techniques to interpret this data.
This era marked the transition from gut-feeling
decisions to data-driven strategies, enabling HR
professionals to make more informed decisions
based on empirical evidence.
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10. Transformation to AI
•Today, these practices have evolved into more sophisticated AI-driven
analytics. AI not only processes data but also predicts outcomes and provides
actionable insights, making HR strategies more proactive than reactive. For
example, AI can analyze employee engagement surveys to predict potential
turnover and suggest interventions to retain key talent.
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11. Current Trends
AI-powered tools like chatbots, predictive analytics, and automated resume screeners are becoming commonplace in
HR departments worldwide. These tools streamline various HR functions, from recruitment to employee engagement,
and help HR professionals focus on more strategic tasks. The integration of AI in HR brings numerous benefits,
including increased efficiency, improved decision-making, enhanced employee experiences, and the ability to process
large volumes of data quickly.
AI in Recruitment: AI is used for
resume screening, interview
scheduling, and candidate assessment,
reducing the time and effort involved
in hiring.
AI in Performance Management:
AI systems track and evaluate
employee performance, provide
continuous feedback, and predict
future performance trends.
AI in Learning and Development:
AI-driven platforms offer personalized
learning paths, identify skill gaps, and
recommend training programs.
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12. Conclusion
AI is not just a buzzword; it's transforming HR from a
transactional function to a strategic partner in business
success. By embracing AI, HR professionals can focus
more on strategic initiatives and less on routine tasks.
Stay tuned as we delve deeper into how AI is reshaping
various HR functions, from recruitment to employee
engagement, in the upcoming articles.
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