Artificial intelligence (AI) is reshaping many aspects of modern life, and job application processes are no exception. Companies are increasingly turning to AI-powered tools to streamline recruitment, manage large applicant pools and improve efficiency. However, this shift has sparked a mix of praise and criticism as job seekers and employers evaluate the pros and cons of AI’s involvement. This interesting topic came to us from NBC Bay Area in their article, “AI is supposed to make applying to jobs easier — but it might be creating another problem.”

One of the primary advantages of AI in recruitment is its ability to save time. Hiring managers often receive hundreds of applications for a single position, making it difficult to review each one manually.

AI also reduces certain biases in hiring. Traditional recruitment methods can sometimes be influenced by unconscious human biases related to age, gender or ethnicity. Properly designed AI tools can focus solely on objective data such as skills, qualifications and work experience. This approach has the potential to promote fairness and diversity in the hiring process.

Despite its benefits, AI in job applications has its limitations and drawbacks. A major concern is that AI systems are only as good as the data they are trained on. If historical data contains biases, AI tools can inadvertently perpetuate them.

Another issue is the heavy reliance on keyword matching in resume screening. Job seekers who do not optimize their resumes with the exact keywords from a job posting may be unfairly filtered out, even if they possess the required skills. This reliance on automated tools can lead to qualified candidates being overlooked.

The integration of AI in job applications is a double-edged sword. While AI brings efficiency, speed and the potential for greater fairness, its limitations must be addressed. Employers should view AI as a tool to support, rather than replace, human decision-making. Combining AI’s capabilities with human oversight can help ensure that recruitment processes remain fair, transparent and effective.

The real challenge is that most organizations have little knowledge on how AI systems make decisions. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.