5 challenges of AI in recruitment
AI in recruitment faces challenges such as bias in algorithms, lack of transparency in decision-making processes, data privacy concerns, difficulty in assessing soft skills, and resistance from employees to AI-driven hiring processes. These obstacles must be addressed to ensure the successful integration of AI in recruitment practices. Overcoming these challenges will be crucial in leveraging the benefits of AI technology to improve the efficiency and effectiveness of recruitment processes. The recruitment industry must navigate these complexities to harness the full potential of AI in transforming talent acquisition and management.
AI can save recruiters time, but using the technology to find new employees can also present various challenges. HR leaders should be aware of these problems before relying on AI to carry out important recruiting tasks. Some of the recruiting tasks AI can help with are resume screening, talent pool development, and candidate experience. However, problems such as AI bias, data security and governance, candidate experience, and pressure to use AI could negatively affect a company's recruiting efforts and even open up the organization to legal action.
Challenges of Using AI in Recruitment
Bias
Bias has become a major point of discussion, and some states, including California and Texas, are considering moving forward with bills that would impose rules on companies' AI use, including using AI for recruiting. HR departments might use AI for resume screening, where a tech scans resumes for keywords related to qualifications, work experience, and education. These kinds of AI tools also carry out talent pool development by scanning platforms such as LinkedIn for potential job candidates. Using these tools comes with potential dangers. For example, biased tools might search LinkedIn only for people who have attended specific colleges and ignore candidates that don't fit that criteria but would also be a good fit, said Will Howard, director of HR research and advisory services at McLean & Company. Job candidates have alleged that AI systems have rejected candidates based on race, age, and disabilities. In addition, HR leaders might not know the origin of the data AI uses to carry out its processes, and that data could lead to bias. Training for a company's AI is usually conducted by third-party vendors who train their software based on data points from various organizations. That data can be biased, which leads to the AI making biased decisions. When working with AI vendors, HR leaders should inquire about the technology's bias detection capabilities.
Data Security and Ownership
HR leaders might find a third-party vendor has granted wider access to their company's data than they previously believed. HR leaders should clarify data questions with their third-party vendor. A company's organizational data might be fed back into the AI model, which is then learning from it.
Data Governance
Because AI technology is relatively new, an organization might not yet have put proper data safeguards in place. HR departments handle a large amount of sensitive data, so HR leaders must consider strong AI governance. Collaboration among HR leaders, the chief data officer, the chief information security officer, and the company's legal counsel is essential to avoid privacy issues.
Candidate Experience
Chatbots can potentially save HR staff time by answering candidate questions and addressing them more quickly than a recruiter can. However, AI can also negatively affect the candidate's experience. Some candidates might prefer speaking with a human being. HR and other leaders must make it a priority to inform job candidates about how they're using AI to avoid creating trust issues.
Pressure to Use AI
AI is currently everywhere in the tech world, and HR may face pressure from other leaders at the company to use it, without considering whether it's the best solution to a problem. HR should start by asking, "What problem are we trying to solve?" Using AI can hinder personal connections with candidates, and HR leaders should approach AI tools with skepticism and consider the impact on the overall recruitment process.