3 Challenges with AI Integration in HR

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Integrating artificial intelligence into the workplace can be empowering. In fact, CMSWire reports that 64% of HR practitioners are more confident and secure in AI-generated advice. After all, AI can optimize application processes — like condensing multiple steps into one smart form that can immediately be fed into programs for assessment. Some AI programs can even extract insights from feedback. HR practitioners can then use these insights to improve employee experiences and increase retention.

In spite of these, AI application in human resources is not without its flaws. AI’s reliance on patterns and databases makes it objective. However, this objectivity can also restrict HR processes. Below we discuss a few challenges that AI integration may cause in HR — and how you can address them.

AI Biases in HR Recruitment

Many believe that AI recruitment tools eliminate hiring bias because they use data to objectively pick out candidates. This is helpful when hiring, as LHH notes that diversity and inclusivity are important. A diverse and inclusive hiring process can help broaden your talent pool. It also helps the company recruit individuals with skills that the company’s current workforce doesn’t have yet.

Yet though AI can technically reduce hiring bias, it’s not a perfect solution. AI relies on data from humans, making AI recruitment tools highly likely to adopt the biases rife in human-prepared data. To deal with this challenge, companies must first work on improving the quality of the data sets they feed to AI. This is something Unilever did after they realized that their AI tool was only hiring candidates from a select number of universities.

Attacks on AI HR Systems

Since AI-powered HR tools depend on data which may include employees’ personal identifiable information (PII), they often face data privacy attacks. This can put employees at risk if hackers exploit their PII for malicious goals. Data breach technology also keeps developing, making attacks even more unpredictable.

To protect employee data as much as possible, cyber security must be reinforced and updated. Fortunately, there are solutions you can turn to. Business.com mentions that cloud human capital management systems all use security analysis and tools to protect HR operations and data. With the purpose of building layers of protection, some of these security measures involve multiple passwords for authentication or require the use of company-issued and encrypted devices.

Lack of Human Emotion in Teams Management

Another downside to AI is that it can’t process emotions. In interviews, emotions and non-verbal cues in interviews often help us choose the right candidates based on their compatibility with workplace culture and values. Rather than choosing between artificial and human intelligence, opt for collaborative intelligence.

In HR, you can apply the concept of collaborative intelligence in how you delegate tasks. Assign jobs that require human discernment to HR practitioners — the assigned worker, in this case, has to read nonverbal cues or tap into their emotional intelligence. AI can remain as a supporting mechanism that focuses on optimizing HR-related procedures that do not require emotion reading. For example, Randstad uses an AI virtual assistant to efficiently schedule interviews and takes care of simple legal questions that do not need interpretation. The interviewing HR manager can then take care of questions meant to gauge the character and concerns of the interviewee.

Adopting AI into HR systems may be full of challenges and limitations. By learning more about them, you can reap the benefits of AI integration without minding too much its risks and drawbacks.

AI Time Journal Staff Writers report on the AI technology advancements and opportunities across industries to leverage AI.

About AITJ Staff Writer

AI Time Journal Staff Writers report on the AI technology advancements and opportunities across industries to leverage AI.

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