Artificial intelligence in business: a few reminders
Definition of AI
According to IBM, artificial intelligence (AI) refers to systems or machines that mimic human intelligence to perform tasks and that can iteratively improve based on the information they collect. AI supports humans on several levels: speech recognition, decision-making, problem-solving and autonomous learning.
How can we distinguish an AI tool from a simple automation tool?
An HRIS tool can be considered an AI tool when it uses technologies that simulate human capabilities such as learning, decision-making and pattern recognition. AI-enabled software incorporates at least one of the following functionalities:
- Automate a process by analysing historical data, company rules and employee behaviour.
- Forecasting and planning using predictive algorithms, based on past trends and predicted events.
- Understand and process requests formulated in natural language (e.g. via e-mails or chat messages) and respond appropriately (NLP).
- Analyse large amounts of data using machine learning techniques.
- Learn and improve over time by incorporating feedback to refine its suggestions.
Benefits of AI for businesses and employees
AI enables businesses to automate repetitive tasks, improve the accuracy of processes and speed up data analysis. Thanks to massive data analysis, AI fosters business innovation and offers new prospects for developing new products and services. For employees, AI lightens the workload, enables them to work on higher added-value tasks and provides decision-making tools.
The limits of AI in HR
Algorithmic and ethical biases
Although powerful, AI systems can reproduce and amplify the biases present in the data used to train them. If historical data contains biases, the algorithm may perpetuate them, leading to biased decisions in recruitment or talent management. For example, an AI system might favour male candidates even though this preference is unjustified and unwanted.
These algorithmic biases raise issues of fairness and discrimination. Biased decisions can exclude qualified candidates or disadvantage certain employees. This can affect diversity and inclusiveness within the company. Automated decision-making processes must be transparent, fair and impartial, and HR must be able to explain to candidates how and why certain decisions are made by AI.
Data protection issues
The use of AI in HR involves the collection and processing of large amounts of personal data. To comply with RGPD regulations, companies must ensure that this data is protected and respect the rights of individuals (right to be forgotten, explicit consent). Companies must be transparent about how data is collected, used and protected.
However, AIs are vulnerable to cyber-attacks, which can lead to breaches of sensitive data. Employees' personal information can be exposed (bank details and medical records) which can cause significant damage and affect the company's reputation. To guarantee the security and confidentiality of employee data, employers must implement encryption technologies and a policy for managing access to tools.
Technological and human limitations
Implementing HRIS and AI tools can be complex and costly for the human resources department. Companies have to invest in solutions, then train staff and call on external experts for training.
At the same time, AI algorithms can be opaque and can alter the understanding of the decisions taken. This opacity raises issues of trust and accountability. Employees and managers may be reluctant to rely on systems whose operation they do not understand.
Change management
Human Resources Managers need to familiarise themselves with these new technologies in order to integrate them into their day-to-day work. A learning period may be necessary, as some employees may question traditional methods. To avoid resistance to change, managers have a role to play in raising awareness and demonstrating the benefits of AI. Training courses can be offered to help overcome any reluctance.
