Artificial intelligence (AI) is coming to human resources (HR). AI talent acquisition will be a natural step forward, and organizations need to prepare. This article will examine AI talent acquisition: How it can be used and some of the challenges AI poses. Let’s start by looking at how AI is being used in HR today.
A recent SHRM survey of 2,300 HR professionals from a variety of industries found an overall AI adoption rate of 25% in HR functions. Among organizations of 5,000 employees and above, the adoption rate is 38%. That broadly agrees with an MIT study finding that AI adoption is concentrated in large organizations.
AI adoption has so far focused on labor intensive tasks. In the SHRM survey, 65% of those who have adopted AI use it to generate job descriptions, while 42% use AI to target job postings to specialized audiences. About one-third use AI to review resumes, automate candidate searches, or communicate with candidates.
But AI is a long way from being powerful enough to tackle executive recruiting, as Korn Ferry reports. In fact, a Mercer survey of 477 HR executives found that just 14% of organizations are using AI talent acquisition tools in their “technology stack.”
Cost and efficiency. To date, the main reasons for using AI are to increase efficiency and cut costs. In large organizations, AI can be invaluable in screening a high volume of resumes, or for searching user profiles on sites like LinkedIn, to find qualified candidates. AI tools are also well suited to tasks like scheduling interviews.
With routine tasks taken care of, HR professionals can address more human-centered activities like ensuring a good fit between candidates, managers, and organizational culture. Enhancing human capabilities in this way is an example of what IBM calls “human centered AI.”
Candidate experience. Another benefit of AI talent acquisition, used properly, is an improved candidate experience. AI tools can keep candidates informed and answer questions as the process moves forward. This will be particularly helpful to large organizations that have many candidates going through the system at one time.
By keeping candidates informed and engaged, organizations maximize the chances of keeping top talent interested. Organizations need to be cautious of losing the “human touch,” though. Relying on chatbot responses and automated scheduling is no replacement for a human connection.
Bias in AI models or training data. One of the selling points of AI talent acquisition has been its ability to avoid human bias. Some have claimed that AI eliminates bias by looking for minimum qualifications only, without looking at schools, personal names, etc. In the SHRM survey, for example, about one-third of respondents believed that AI helped increase racial, gender, and educational diversity. But there are caveats to go with the promises.
In a Harvard Business School survey, 88% of HR executives reported that their AI tools reject qualified candidates. One of the problems is that AI can be too literal and has difficulty ranking the importance of different qualifications. Another problem reported was the rejection of candidates with explainable employment gaps. These issues could be addressed with human review, but in that case the claimed impartiality of AI would not live up to its promise.
More challenging is the problem of biased training data. Some AI tools have skewed candidate searches towards particular races or genders. Still other AI tools mimic historical hiring and promotion practices, which can perpetuate bias. AI talent acquisition must include careful review to identify and overcome these kinds of bias, both to widen the talent pool and to avoid legal consequences.
Readiness to adopt AI. Another challenge is preparing the organization to use AI. At the organizational level, readiness includes having a detailed plan for where and how AI will be implemented.
A common stumbling block is integrating systems while protecting sensitive data. That includes protecting private personal data and confidential business data, while giving AI tools access to the information they need to function at their best.
Preparing HR professionals to use AI is another challenge. Organizations need to prioritize learning and development, both in the use of AI tools and in interpreting the data sets AI generates.
In summary, AI talent acquisition is in the beginning phases of adoption. Most organizations use AI tools in HR for efficiency and cost reduction, not for deeper insights or improved results, but change is coming. If you would like to learn more, please contact us.
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TEP.Global not only has a combined 100 years of experience and expertise in people management, talent acquisition, executive assessment, but also deep knowledge in building teams and workplace culture in organizations of all sizes. For more information and insights, please contact us.
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