What is NLP?

NLP stands for Natural Language Processing. It is a prominent subfield of AI (artificial intelligence) via which a computer understands the meaning of text and speech. Everyday uses of NLP include autocorrect on smartphones, voice-activated virtual assistants (Alexa, Siri, Google Assistant, etc), and autocomplete functions on text-based platforms. NLP analyzes unstructured data (ie resumés, interpersonal communications, and other documents) and delivers concise, relevant insights for back-end users, reducing time and cost. One text-based application of NLP in hiring includes automated resumé processing. The software can be programmed to scan applications to identify which ones best match the employer’s ideal candidate criteria, such as educational background, past experiences, and skills. 

The strategic significance of NLP

The larger an organization is, the harder it can be for the human resources department to devote the time and resources to make employees and candidates feel appreciated. NLP technologies allow human resources employees and recruiters to communicate and maintain relationships with employees and candidates at a scalable level. Many positions require candidates to complete multiple rounds of interviews; NLP can be integrated into the early stages of the interview process in order to better understand and identify the best of the candidate pool. NLP-enhanced automated interviews allow hiring managers to pick up on blind spots or behaviours that they may have otherwise missed. NLP tools can evaluate the candidate’s fit for the company through analyzing their word choice, speech patterns, and facial expressions, giving hiring managers insights that they may not have noticed on their own. 

Applications of NLP in various stages and functions of recruitment and HR


  • Identifying personal traits
  • Classifying and ranking applicants
  • Identifying gaps in records
  • Removing bias
  • Identifying fraud

Survey and feedback analysis

  • Sentiment analysis
  • Identifying conflict areas
  • Survey output analysis for structured and unstructured data

Succession and career development

  • Identifying growth potential 
  • Identifying training needs

Social media analysis

  • Monitoring social content and moderating as needed
  • Identifying potential talent
  • Identifying competence and interest areas
  • Behaviour trends
nlp for recruitment

Outcomes for candidates and employees

Many companies use natural language processing technology on the customer side in the form of virtual assistant chatbots on their websites. This familiar and intuitive communication format allows users to quickly find answers for their queries and streamlines the customer journey. This positive experience strengthens the company’s brand and saves money over the long term by automating responses to common customer questions.

While this is common practice across industries to maintain companies’ corporate brands, best-in-class companies leverage this same technology internally to boost their employer brand. Candidates cite long application processes as one of the biggest pain points in the job search. These inconvenient and convoluted processes often deter applicants from following through with their application. In turn, this negatively impacts employers’ candidate pipelines. 60% of applicants prematurely quit online applications that are too time consuming, with 69% abandoning a job application after 20 minutes. Easy to use communication tools, such as chatbots, streamline the application process and capture the attention of applicants who would have otherwise been disengaged or abandoned the form altogether. 

78% of applicants view candidate experience as an indicator of how an employer values its people. Streamlining the interview process with NLP and keeping candidates in the loop ensures that candidates have a positive impression of the company. This first impression is crucial, as positive onboarding experiences directly correlate to employee retention, performance, and engagement. 

Beyond hiring: training and other integrations of NLP for managers

NLP has applications in behavioural training for managers. For example, when it comes to letting someone go, many managers struggle to find the right approach. This can have consequences for the company. A frustrated former employee being vocal about their negative experiences would hurt the employer’s brand. Behavioural training NLP tools help managers to improve their communication skills and protect the employer brand. These enterprise tools, such as Talespin, combine NLP with AI, VR (virtual reality), and AR (augmented reality) to educate and empower human resources professionals. 

The continued need for human input

While NLP and other applications of artificial technology are highly effective at many HR-related functions, this technology cannot serve as a replacement for HR personnel. While these tools are efficient at unstructured data processing and the automation of routine tasks, computers still lack the sophistication to fully comprehend the full scope of nuance in language. Hiring managers must navigate complex social situations and employ dynamic decision making. Machines are unable to detect some of the more ambiguous elements of human interaction, such as sarcasm, ambivalence, colloquial or regional terms, and other common elements of interpersonal communication. 

The use of NLP tools by hiring managers and recruiter is akin to that of the autopilot function by pilots. While autopilot technology has proven itself to be reliable and efficient, it must always be monitored by pilots; a plane won’t fly without one. Similarly, NLP and other forms of automation in recruitment cannot replace the role of human resources and recruitment personnel. For candidates, feeling that they need to appease an AI as part of their application is a significant pain point. In a field that centres interpersonal collaboration and in circumstances where candidates’ and employees’ careers and livelihoods are at stake, decisions regarding hiring cannot be fully entrusted to machines that lack the capability to fully understand humans. These tools provide valuable insights, but human beings should always have the final say.

Final takeaways

NLP and other AI software provide managers with meaningful insights extrapolated from large datasets of unstructured information, automate routine processes in hiring, and empower human resources personnel to continually improve the quality of their communication and engagement with candidates and employees. While these tools unquestionably add value to the hiring process, AI and NLP lack the nuances of human intelligence and thus are not infallible. Accordingly, employers should seek to find the right balance between automation and NLP technology and input from human beings. This balance is essential to help employers make the most appropriate onboarding decisions for their business.