AI resume screening: One of the biggest challenges that HR practitioners face today is finding suitable people to recruit. In the past, this task has proven to be challenging, in part because of inefficient manual tasks that hamper the recruitment process and the lack of access to the right details.

Human Resource Processes and Challenges

In fact, 46% of employers and workplace managers described “finding the right candidate” as the biggest obstacle to recruiting today, based on research undertaken by LinkedIn.

To tackle these issues, new technologies have emerged in the HR tech ecosystem with robust solutions using Big Data, predictive analytics, and AI.

AI resume screening can help to automate and improve everything from job advertising to resume screening, scheduling and text recruitment in your recruitment process.

These new instruments offer us ways to resolve the limitations and prejudices inherent in the recruitment of automated, market-related processes, complex metrics, and even budget constraints.
By following this approach, recruiters can more efficiently choose candidates who submit their resumes during the job application process. This streamlined process eliminates the need for extensive rule-writing or reliance on fixed layout models, allowing for greater adaptability to evolving records over time.

Using an intelligent automation tool such as Gleematic, we can compare how to check resumes using various functions. The following are tips with names of functions in Gleematic A.I. Designer.

Gleematic A.I. Designer Functions

  1. The “If Variable” function under the “Variable” tab performs keyword searches in resumes based on a keyword list.
  2. The “Fuzzy Extract One” AI function, found under the “Text Analytics” function, conducts keyword searches in resumes based on a keyword list.
  3. The “Text Classifier” AI function, also located under the “Text Analytics” function, is employed for keyword searches in resumes based on a keyword list.
  4. Setting up the “If Variable in Variable” and “Text Classifier” functions may take more time as functions are required to clean up data in the keywords list and resumes.
  5. The “If Variable in Variable” does not allow for spelling errors or shortened spelling forms as compared to the “Text Classifier” and “Fuzzy Extract One”
  6. The “If Variable in Variable” function does not accommodate spelling errors or shortened forms compared to the “Text Classifier” and “Fuzzy Extract One.”
  7. Both the “If Variable in Variable” and “Text Classifier” functions offer greater customizability compared to the fixed algorithm of “Fuzzy Extract One.”
  8. Searching for multiple keywords with the “If Variable in Variable” function requires more effort, involving the creation of additional steps and selection of more sub-scripts within these steps.
  9. “Text Classifier” and “Fuzzy Extract One” allow greater flexibility in defining the list of keywords.
  10. “Fuzzy Extract One” and “Text Classifier” are faster methods for keyword matching compared to “If Variable in Variable,” as the technology behind these functions is more efficient.

Those are some differences between A.I. and “non-A.I” functions for vetting resumes. You can read our other articles here.

Written by : Zachary