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Revolutionising Recruitment: The Power of AI, ML, and Robotic Process Automation

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By Gopal Kulkarni CEO & COO of Kendra Business Technologies

Recruitment is one of the most important and challenging functions of human resources
(HR). Finding the right talent for the right role at the right time is crucial for any organisation’s success and growth. Especially in larger organisations, the challenges associated with orchestrating the entire talent acquisition process meticulously while meeting the organisation’s objectives in terms of quality of hires, cost of hiring, and time-to-hire are not trivial. Fortunately, some modern technologies are offering great help to address these challenges to a reasonable extent.

Key among these new technologies is Artificial intelligence (AI), machine learning (ML),
and robotic process automation (RPA) are three technologies that are transforming the
recruitment process by automating high-volume tasks, improving efficiency and
effectiveness, reducing bias and errors, and enhancing the candidate experience.

AI (Artificial Intelligence), ML (Machine Learning), and RPA (Robotic Process Automation)
have the potential to significantly transform talent acquisition in the coming days.

Here’s how each of these technologies can impact the talent acquisition process:
AI in Talent Acquisition:
AI can revolutionise talent acquisition by automating various repetitive and time-consuming tasks, improving efficiency, and enhancing decision-making. Here are some keyways AI can transform talent acquisition:
a. Resume Screening: AI-powered tools can analyse resumes and applications to identify
relevant skills, experience, and qualifications. This helps in shortlisting candidates more
accurately and quickly.
b. Candidate Sourcing: AI can scan various online platforms and social media to find
potential candidates that match specific job requirements. It can also assess candidate fit
based on their digital footprint.
c. Chatbots and Virtual Assistants: AI-powered chatbots and virtual assistants can handle initial candidate interactions, answer frequently asked questions, and schedule interviews, providing a seamless candidate experience.
d. Predictive Analytics: AI can analyse historical hiring data to predict future hiring needs, identify the most successful candidate profiles, and optimise recruitment strategies.

ML in Talent Acquisition:

Machine Learning complements AI by enabling systems to learn from data and improve their performance over time. ML can have the following impacts on talent acquisition:
a. Candidate Matching: ML algorithms can compare candidate profiles against job requirements, taking into account factors beyond keyword matching. This improves the
quality of candidate matches and reduces bias in the process.
b. Interview Analysis: ML can analyse interview recordings or transcripts to provide insights on candidate performance, highlighting strengths and areas for improvement.
c. Employee Retention: ML can analyse employee data to identify patterns and factors that contribute to employee turnover. This helps in designing strategies to retain top talent.

RPA in Talent Acquisition:
RPA involves automating repetitive and rule-based tasks using software robots, freeing up
recruiters time for more strategic activities. Here’s how RPA can transform talent acquisition:
a. Application Processing: RPA can automate data entry and validation tasks, extracting relevant information from resumes, applications, and other forms, and populating the recruitment system.
b. Onboarding Processes: RPA can streamline onboarding processes by automating tasks such as document verification, background checks, and provisioning new hires with
necessary resources.
c. Compliance and Reporting: RPA can ensure compliance with regulations by automating data gathering, validation, and reporting, reducing the risk of errors and improving efficiency.
d. Workflow Automation: RPA can automate workflows, such as interview scheduling,
communication with candidates, and feedback collection, improving process efficiency.
Overall, AI, ML, and RPA have the potential to enhance the speed, accuracy, and efficiency
of talent acquisition processes. They can help recruiters make more informed decisions,
improve candidate experiences, and optimise overall recruitment strategies. However, it’s important to strike a balance between automation and human involvement to maintain a
personalised touch and ensure ethical and unbiased practices.

Recent Statistical Trends
● According to a 2022 McKinsey Global Survey on AI, AI adoption has more than doubled since 2017, though the proportion of organisations using AI has plateaued between 50 and 60 percent for the past few years.
● A study by a recruitment technology company indicates that early AI recruitment adopters provide 75% less cost per resume screen, 4% more revenue per employee, and a 35% lower employee turnover rate.

Conclusion

AI, ML, and RPA are transforming the recruitment landscape by streamlining processes,
enhancing efficiency, and improving the overall candidate experience. These technologies
are not meant to replace human recruiters but rather empower them with valuable insights
and automated tools to make better, data-driven decisions. As the adoption of AI, ML, and
RPA continues to grow, it is crucial for organisations to strike a balance between leveraging
technology and maintaining a human touch throughout the recruitment process. The future
of recruitment lies in collaboration between humans and machines, harnessing the power of
technology to identify and attract the best talent.

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