While artificial intelligence may appear to be a recently emerged field, its roots can be traced back to the foundational work of Alan Turing in 1950, with the term itself first being coined in 1956. For decades, however, it remained largely confined to academic and research circles. It was not until the widespread adoption of tools such as ChatGPT, Microsoft Copilot and Google Gemini, that AI truly entered the daily consciousness of the broader public. This turning point has highlighted the power of what these technologies could achieve and how profoundly transformative they can be.

Unique digital technologies, such as AI, are disruptively changing our ways of working, reshaping business models as well as our society. They tend to grow exponentially far beyond what our linear-thinking brain can easily comprehend or anticipate. They bring innovation, and the advantages of leveraging AI are certainly substantial. In operations, for example, AI can streamline workflows, can automate routine tasks (and non-routine tasks!) thus reducing manual workload, expedite the decision-making process, enhance efficiency by minimizing errors, enabling the organization to become more agile. 

In the world of human resources, I witness these benefits on a daily basis. For instance, AI can identify candidates who are not actively seeking a new job but may be an excellent fit for the position; AI can detect potential risks of employee turnover by assessing trends in employee behavior, such as signs of dissatisfaction; AI can enhance employees’ capabilities by personalizing professional development and creating tailored training roadmaps and virtually coaching for any professional development. These are not hypothetical examples, they are already happening in many organizations around the world!

Yet, these advantages come with significant ethical challenges. I had an opportunity to attend the course on “Mitigating Artificial Intelligence Bias in the Workplace and Human Resources Practices” organized by ITC-ILO. During that course, one concept came up repeatedly and stayed with me: “garbage in-garbage out.” It captures, with disarming simplicity, one of the core risks of algorithm-based AI that operates by analyzing given data to identify patterns, which it uses to make predictions and inform decision making.

Let me offer an example from the HR world to further explain this concept. Consider a recruitment tool that is based on historical hiring data. If past hiring decisions advantaged candidates with uninterrupted career paths, then the algorithm will continue to disadvantage candidates who during their career took time off for caregiving reasons (disproportionately affecting women!) and candidates with health issues that caused employment gaps. Consequently, by feeding the machine with biased data, we scale discrimination behind the appearance of algorithmic neutrality: using biased data reproduces biased outcomes.

This reality helped me understand that the fundamental question is not whether an organization should adopt AI, this is inevitable, but it is how to do so responsibly in alignment with human values and respect for employees. So, I wonder: How can organizations harness AI’s immense potential while genuinely safeguarding human fundamental values?

For HR professionals like me, this is not merely a technical question, it is a responsibility. I genuinely believe that HR professionals are well positioned to champion a human-centered approach to AI, one where digital transformation does not come at the expense of fundamental values such as the right to be treated fairly and with dignity, the right to equal opportunity regardless of one’s background or life circumstances, and the right to transparency about the tools and processes.

So, what does this mean for us in practice? 

Concretely, this means taking deliberate steps to ensure that AI systems are used responsibly and equitably. AI tools should be assessed for potential bias before they are deployed, and their outputs should be reviewed on an ongoing basis to evaluate their fairness, diversity, and inclusiveness. 

Organizations should also be transparent about when and how AI tools are used so that staff members understand their role in decision-making processes. 

Before implementing AI systems, input from a range of stakeholders, particularly representatives of marginalized groups, should be considered to ensure that different perspectives are reflected. 

In addition, measures of success should extend beyond efficiency and effectiveness to include the fairness of outcomes and the broader impact of AI on people and communities.

However, HR professionals cannot carry this responsibility alone. A successful and ethical use of AI requires collective engagement from everyone: from embracing a mindset open to new digital ways of working, to establishing strong ethical organizational frameworks. It also means visionary leadership: leaders who understand that the goal of digital transformation is not efficiency for its own sake, but the creation of organizations that are more capable, and at the same time more equitable, and more humane. 

It is our collective responsibility to drive transformation forward while fiercely protecting the values, dignity, and human spirit that make our organizations worth building in the first place.