Written by Louise De Somere

AI can perform repetitive tasks faster and more accurately than humans. This increases the efficiency of HR processes and reduces the workload for HR professionals.

The first efficiency gain lies in automating time-consuming administrative tasks. AI tools can, for example, automatically screen and rank CVs based on relevant skills and experience. As a result, recruiters need to spend less time manually reviewing applications and can more quickly select the best candidates.

The second efficiency gain is the reduction of bias in decision-making. While people are often (unconsciously) influenced by prejudices, AI-based software can assess candidates and employees objectively based on competencies and performance, without taking irrelevant factors such as age or gender into account.

A third efficiency gain stems from AI’s ability to process large amounts of data from different sources quickly and accurately. For example, Workday’s AI-based performance evaluation system processes real-time data from various performance indicators such as objectives (OKRs), projects, customer feedback and team feedback. While it is a complex task for humans to combine all this information and draw accurate conclusions, AI does this automatically and without errors, enabling faster and better-informed decisions regarding compensation, promotions or training.

Finally, AI optimises HR strategies through the use of predictive analytics. This enables companies to better anticipate future workforce needs. A good example is an HR department in the retail sector that uses AI to predict which departments will need additional staff during peak hours. As a result, workforce planning becomes more efficient and overtime and workload can be managed more effectively.

AI offers significant efficiency gains for HR by automating repetitive tasks, reducing bias in decision-making, processing complex data quickly and optimising strategic workforce planning. This not only results in a lower workload for HR professionals, but also in faster, more objective and better-informed decisions that contribute to a more efficient and effective HR policy.

Although AI can reduce human bias, the opposite is also possible. For example, when the training data are biased. An AI system that learns from historical data containing bias or in which certain groups are underrepresented may continue to unconsciously disadvantage certain groups.

Transparency about how AI decisions are made is therefore crucial. Companies must regularly audit algorithms and diversify the data used to ensure fair outcomes.

In addition, explainability plays an important role. AI systems often function as a 'black box', making the decision-making process difficult to understand. This can be problematic in performance evaluations or recruitment processes, where candidates and employees have the right to understand the decisions that have been made. Implementing explainable AI systems and developing internal AI guidelines helps to increase transparency and build trust within organisations.

Want to learn more about how to promote transparency in your use of AI? Be sure to read our blog post as well: AI in HR: 4 ways to promote transparency.

In addition to bias and transparency, AI applications in HR also bring significant challenges in the area of privacy. Analysing and visualising complex employee data provides valuable insights, but can also lead to ethical concerns and infringements on employees’ privacy and autonomy.

One example is the use of AI to analyse work-related communication patterns, such as chats on internal platforms and meeting interactions, in order to measure productivity or team dynamics. While these analyses can provide valuable insights, they also raise privacy concerns, especially when employees are not aware of the extent and purpose of the data collection. This can lead to distrust and a feeling of constant surveillance in the workplace.

In addition, sensitive data may be unintentionally exposed and have adverse consequences. For example, when predicting turnover among high-performing employees, sharing such insights with managers may lead to unconscious behavioural changes, causing these employees to be less involved in strategic decisions or potentially overlooked for promotion opportunities.

The use of AI in HR offers numerous benefits, but it is crucial to fully understand the risks and handle them consciously and carefully. Incorrect use of AI can have harmful consequences for employees, such as the impact of incorrect decisions, and for the organisation, such as loss of trust among employees and reputational damage. Continuous monitoring and responsible implementation are therefore essential.

To use AI fairly and effectively, companies must critically evaluate their AI systems. Regular audits, diversity in training data and a combination of human and AI-driven decision-making help to mitigate risks. In addition, it is important to design AI systems in such a way that HR professionals can always review and adjust the final decisions.

It is also essential that HR professionals are trained in the use of AI and that employees are involved in its implementation. By integrating AI responsibly, companies can not only work more efficiently, but also ensure a fair and transparent HR policy.

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