How AI supports Talent Acquisation

5 best ways AI/ML supports Talent Acquisition

What is AI and Basics of AI in hiring process

In this era of cutthroat corporate competition, organizations often face some critical challenges when it comes to sourcing and attract top talent. Traditional methods of talent hunting are now facing a struggle to keep up with the demands of the digital age. However, the emergence of Artificial Intelligence (AI) and Machine Learning (ML) has changed the recruitment possibilities. By integrating AI/ML technologies, talent acquisition is undergoing a transformative shift, offering solutions to effectively identify and attract the best-suited candidates.

Brief Insight of Artificial Intelligence (AI)

Artificial Intelligence is intelligence demonstrated by computers in replace of human intelligence.

John McCarthy is considered as the father of Artificial Intelligence. He was an American computer scientist. He is one of the founders of Artificial Intelligence, together with Alan Turing, Marvin Minsky, Allen Newell, and Herbert A.

The job market has undergone a significant downfall when it comes to Layoffs on a global level, companies are now expanding their interest towards AI to seek the best talent to drive their success.

“We have been able to recruit profiles with the support of AI that we probably wouldn’t have hired just on their CV. Like a tech profile for marketing, or a finance profile for sales.” 

Eva Azoulay, Global Vice-President of Human Resources

“In our organization, we wholeheartedly embrace cutting-edge AI technologies that not only optimize and elevate our hiring processes but also cultivate robust and meaningful candidate relationships.”

Mayank Kakkar, Human Resources Manager at NexGen IOT Solutions

Recent AI research by Avanade and Forbes Insights found that 87% of senior executives believe that artificial intelligence is important to achieving overall business objectives. It has become increasingly prevalent in the hiring process, with many organizations using it to streamline and improve their recruitment processes.

An estimated 88% of businesses worldwide already use AI for recruitment and sourcing in some capacity, and 79%  of recruiters believe AI is or will soon be advanced enough to make hiring decisions. 

What is Machine Learning

Artificial Intelligence

Machine learning (ML) is a subset of artificial intelligence (AI) which focuses on developing algorithms and models that enable computers to learn from data and make predictions or decisions without being explicitly programmed. It does so by learning from data — text, numbers or for example photos.

5 ways in which technology is contributing to recruitment

  1. Programmatic job advertising: Letting potential candidates know about the job requirement is a foremost task of recruiters. Job posting or Job Advertisements helps in notifying the candidates about the active  job opening of the organization. You must be wondering how AI/ML does that? Let me throw some light on this. In the case of LinkedIn, ML picks the key skills from the Job Description and notify the candidates who have work around those skills to let them know about the job opening.
  1. Candidate sourcing and screening: One of the most important and time consuming tasks for recruiters to get qualified candidates with skillset supporting Job Description but with the support of machine learning, this process has become speedy and accurate. ML helps in learning through Job Descriptions and pulls out the more aligned or most relevant profile (CV’s) only. Due to which, this whole process has been less time consuming and more accurate. 
  1. Candidate assessment: Candidate Assessment is used to assess the candidate’s skillset to check the compatibility with the job requirement. It is one of the important aspects of the hiring process. There are different tools which not only support in accessing a candidate’s skills but also their personality and intelligence.
  1. Interview automation: AI/ML has shown massive progress in the space of automated interviews. Nowadays, Robots or AI are designed in a way that they can interview candidates by replacing recruiters. It helped make the time and energy consuming process easy for the hiring team of the organization.
  1. Candidate engagement: Candidates need to be engaged with the hiring department throughout the whole process but hiring companies don’t have the time to continuously communicate with candidates. Therefore they use technologies that mimic real life conversations through which candidates can learn more about the company and position before they even talk to recruiters.

Benefits of using Machine Learning during hiring process

  1. Effective Candidate Sourcing: Companies are utilizing these technologies to pull out promising candidates from a large talent pool. Without using technologies like Machine Learning (ML), there might be some chances to overlook top talent and make wrong hiring decisions. Therefore, integrating Machine Learning is crucial to mitigate these risks and ensure the selection of the best candidates.
  1. Accuracy: Incorporating Machine Learning in the hiring process allows organizations to improve the accuracy of result and present reliable data and more importantly minimizing the scope for human errors. By leveraging Machine Learning, organizations can enhance the reliability of their hiring decisions and avoid mistakes.
  1. Efficiency: It  ensures to speed up every stage of the recruitment cycle, efficiently crafting job descriptions, screening resumes, assessing candidates, scheduling assessments and interviews, and making informed hiring decisions.

Risk associated with using Machine Learning during hiring process

  1. Adaption of new technology: Implementation of any new technology can lead to some problems. Organizations must take time to make a choice of appropriate tool determining the support it can provide to our recruitment process.
  1. Errors: Recognizing that no tool can achieve 100% accuracy, organizations need to evaluate the trade-offs before adopting a tool, while also acknowledging the potential for errors and the importance of human involvement to avoid overlooking promising candidates.
  1. Candidate Backout: Machine learning tools optimize the hiring process and can enhance the candidate experience but it is crucial to strike a balance. Over-reliance on AI-driven tools for communication may frustrate candidates and diminish their interest in the application process. Therefore, it is important to maintain a blend of AI tools and human interaction to ensure effective candidate management.

How can AI make work easy for Recruiters?

Given the recent announcement by IBM, there are many ways to utilize AI and tools like Chat GPT to reduce the workforce of recruiters or hiring staff of the company. Activities done by hiring staff like creating perfect Job Descriptions (JD) or Managing interviews which are time and energy consuming. Now, it can be done in less time and with more accuracy with the help of tools like Chat GPT, Virtual Meeting setups like zoom, Google Meet, Microsoft Team, etc.

Platforms like these not only help in bridging the interviewer and the candidate but also support in other ways. For instance, Blocking the calendar, Call Recording, Screen Sharing and many more.

Summing up, AI can extend great help in supporting the hiring process from start to finish with more efficiency and accuracy while hiring organizations can utilize their time in managing these technologies. 

Conclusion:

AI has emerged as a powerful accessory in the field of talent acquisition, offering numerous benefits and transforming the way hiring organizations identify, evaluate, and hire top talent. By leveraging AI technology, recruiters can streamline their processes, enhance decision-making, and retain the best candidates for their organizations. With AI as a partner, organizations can optimize their talent acquisition efforts, saving time, reducing bias, and ultimately driving business success. As AI continues to evolve and advance, its impact on talent acquisition is expected to grow, further changing the way organizations attract and engage with their future workforce.

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