LinkedIn Optimization in the Age of Artificial Intelligence

As 94% of recruiters use LinkedIn to search for potential candidates (Rangel, 2014), creating an effective LinkedIn profile becomes a critical task for job seekers. While there is an array of strategies for LinkedIn optimization regarding verbal and visual content and Search Engine Optimization (SEO) (Berk, 2013; Cooper, 2014; Thies, 2012), few of them address LinkedIn optimization in terms of AI recruiting. With the deployment of Talent Search system at LinkedIn, the features of this AI recruiting system, including intelligent query understanding, the mutual interest matches between recruiters and candidates, and the personalized preference models of recruiters (Geyik et al., 2018; Ha-Thuc et al., 2015; Ha-Thuc et al., 2016; Ozcaglar et al., 2019), brings both opportunities and challenges to job seekers. Thus, this study proposes novel LinkedIn optimization strategies, such as modeling their profiles after current employees in target companies and using standard words in the profiles, to help candidates address the challenges brought by the tide of Artificial Intelligence.

Why Do you Need an Effective LinkedIn Profile?

Resume VS. LinkedIn Profile

As a traditionally required document in job seeking, a paper or electronic-based resume presents a person’s background, skills, and accomplishments. While resumes used to play an important role in job seeking, nowadays, the LinkedIn profile is becoming an emerging genre in recruitment. Compared to the resume, a LinkedIn profile can add a personal touch and provide networking opportunities that a resume may not reflect (LinkedIn, 2018). 

The Wide Use of LinkedIn Profile

LinkedIn is the leading global social networking site for professionals, with more than 660 million users in more than 200 countries and territories(LinkedIn, 2020). As 94% of recruiters use LinkedIn to search for potential candidates (Rangel, 2014), creating an effective LinkedIn profile becomes a critical task for job seekers.

Traditional Strategies for LinkedIn Optimization

Many scholars have already conducted research on traditional strategies for LinkedIn optimization (Berk, 2013; Cooper, 2014), such as Verbal and visual content modification and Search Engine Optimization (SEO), which increases the visibility of a profile in the search engine and therefore directs more browsing traffic to the profile. However, few of them analyze the LinkedIn profile with the implementation of AI-based recruiting tools. Thus, there exists a scarcity of research in AI-based LinkedIn optimization strategies.

What Changes Brought by the AI?

Over the last decade, as AI advanced at a break-neck pace, LinkedIn has been adopting Artificial Intelligence in the design of its recruiting system, called Talent Search System, also known as LinkedIn advanced recruiting system). The innovative functions include intelligent query understanding, mutual interest matches between recruiters and candidates and intelligent professional network, etc (Guo et al., 2019). 

  1. The intelligent query understanding allows the system to use the AI model to infer the user’s intent based on the input, which can help employers better locate employees in the job market. 
  2. The mutual interest matches between recruiters and candidates recommend potential job seekers to employers as well as potential companies to job applicants through the AI prediction based on the data provided by employers and job seekers. 
  3. The intelligent professional network enables users to endorse others’ skills, which helps establish the credibility of the job seekers. Besides, it also recommends job applicants potential occupational connections that they may be interested in establishing based on their backgrounds (Guo, et al., 2019).

What Concerns Brought by AI?

The application of the AI recruitment system is a double-edged sword. While it brings an array of benefits for employers and job applicants, it also brings some concerns in terms of accuracy, privacy, and ethics. 

  1. Accuracy Concern: AI-based “black box” models may cause information mismatch, leading to competent job seekers being filtered out. 
  2. Privacy Concern: AI can be used to portray the job seekers, which may cause personal information leakage.
  3. Ethical Concern: Employers may use an AI-based system to infer job seekers’ confidential information according to their profiles, which may bring discrimination towards them. 

How to Create an Effective LinkedIn Profile?

Given the previous discussion, I propose the following strategies for you to create an effective LinkedIn Profile to meet the new requirements brought by the AI recruiting system.

    1. Model profiles after current employees in target companies

With the implementation of the mutual interest matches between recruiters and candidates, LinkedIn provides a list of potential candidates for the companies according to the existing data provided by the company. Thus, if you model your profile after the format of current employees’ profiles, your chance of receiving an interview will be increased.

     2. Use standard words in the profiles

If you use standard words in your profile, it will make the profile easier to process for the AI-based recruiting system. For instance, using “software engineer” instead of “coder” may increase the probability that your profile gets sent to an employer

     3. Connect with experts in the target field and follow professional groups

Because of the establishment of an intelligent professional network, connecting with experts in the target field and following professional groups can increase the credibility of your profile. It may also improve the chance that your profile gets pushed to hiring groups by the AI recruiting system.

In summary, adopting these strategies for LinkedIn optimization may help you create an effective profile and embrace the challenges and opportunities in the job market brought by AI recruiting.


Blog post written by Chenxing Xie, NC State University, Mar 23, 2020. Featured photo image by Evangeline Shaw on Unsplash

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