AI application for recruitment: resume parsing tools

It can be exhaustive and challenging to amplify or innovate the recruitment process at a scale. Especially for startups, HRtech products, and large organizations, a competent resume parsing solution can unlock a lot of value. With Deep Learning, NLP, and Knowledge Graphs, AI can help evolve a resume-parsing tool to eliminate the need for manual screening.

In this article, you will find must-to-know information related to AI resume parsing solutions, including:

• What is an AI resume parsing software?

• Benefits of having an AI resume parser in a company

• Top resume-parsing software providers in the market

• Comparing the best resume parsing software for 2024

What is an AI resume parsing software?

A resume parsing software, also known as a resume analyzer, helps analyze, extract, and classify information from resumes and CVs. It complements the recruitment process from sourcing to storing CV information as per a  company’s processes.

AI in a resume parsing tool can enhance the recruitment process. Artificial intelligence can leverage technologies such as Optical Character Recognition (OCR), Large Learning Models (LLMs), and Natural Language Processing (NLP)  to enhance resume parsing for more efficiency.

With AI, resume parsing tools can extract and structure data from resumes in a standardized format. It involves processing resumes in various formats (PDF, Word, etc.) and identifying essential information from documents, including candidate information and credentials that can meet job role needs.

Perks of implementing AI resume parser in recruitment

AI has been known to enhance existing business processes for the better. In recruitment, AI resume parsing tools can improve the efficacy of resume screening and, therefore, overall hiring. Here are several perks of implementing the AI-based resume-parsing software:

• Faster screening for HR teams & agencies:

For an average job vacancy, almost 250 candidates send their resumes, out of which 88% profiles are not considerable. With technologies such as OCR and Deep Learning, a resume analyzer can process such a volume of resumes effectively.

• Strategic assistance for recruitment teams:

AI resume parser is a tool that can process a large number of resumes within minutes. Such a tool can innovate the recruitment process of enterprises and agencies so that staff can focus on sophisticated responsibilities.

• API integrations for advancements of company practices:

A resume-parsing solution can boost the talent acquisition processes with ready-to-integrate APIs. Enterprises can integrate these APIs with their existing platform to leverage AI advancements without modifying their proven workflows.

• Supporting different formats and languages:

A smarter resume parsing tool can also help you process candidate profiles in any format or language. Whether candidates use a simple MS Word template or a complex tool like Canva, AI-based resume parsing can extract and process the information from it.

• Recruitment data and operational statistics:

An AI recruitment solution that gathers and stores information from different resumes and market analysis can build a database that can be easily searched and predicted. From finding the right candidate to predicting the best match using AI, resume parsing software can help companies.

How does AI-based resume parsing work?

AI-based resume parsing is backed by several AI subsets, including Machine Learning, Deep Learning, Natural Language Processing, and Knowledge Graphs. Here are the working of an AI resume parser from a technical standpoint:

1. Preprocessing resumes and CVs:

• Resumes and CVs can be in different document formats, such as PDFs, Word, and images. Optical Character Recognition (OCR) is the ability of Computer Vision to recognize text in such documents and make it accessible. 

• AI can also analyze these documents to understand information through different areas of the document such as executive summary, contact information, work experience, skills, and education.

2. Understanding the candidate profiles

• AI resume parsers can leverage Natural Language Processing (NLP) to process the text information gathered through OCR. NLP can translate every word of a resume into an individual token, eliminate redundant information, and understand the specifics with the use of Named Entity Recognition (NER).

• NER can help understand person names, contact information, company names, project descriptions, skills, and other specifics, while Natural Language Processing can gather the meaning behind sentences, paragraphs, and grammar.

3. Information extraction:

• AI can also help extract the key information through profiles while parsing them using specific keywords and patterns that can create structured data for dates, phone numbers, titles, and email addresses. Machine Learning models can effectively extract this information to match the candidates against job role requirements.

4. Cleaning and storing the data in a structured manner:

• ML can not only extract the necessary information but also clean and filter the extracted data. These filtered data can then be saved into the knowledge base. It can translate unstructured data into structured data in JSON or XML.

5. Semantic analysis to match candidates:

• AI-based resume parsing is smarter than traditional resume parsing software, as AI-based matchmaking outperforms the mere keyword comparison. Semantic analysis ensures that the candidate's skills & experience match with job requirements beyond just the keywords.

Evaluating and Comparing Resume Parsing Software

There’s a variety of AI resume-parsing software out there. However, evaluating them further can be boiled down to identifying different areas to compare parsing tools. 

Here are some of the key areas to compare and identify the right solution:

• Identify the scope of implementing a resume parsing software.

• Realizing the strengths and weaknesses of different platforms.

• Comparing the match between an AI tool’s abilities and an organization’s needs and priorities.

• If the tool meets needs, identify the pricing model that is value for money and covers the necessary features.

• Evaluate integration compatibility with existing workflows and software solutions within the company.

• Try out the major shortlisted resume parsing software to compare the usability and decide which is the right choice.

In conclusion,

AI has a certain advantage when it comes to helping with resume parsing and recruitment. AI can make resume screening quicker, more cost-effective, and more quantitative for effective hiring operations. As long as applicants can’t find a way around and AI remains unbiased, resume parsing solutions can be an AI application that can help across any industry.