Dr. Dariush Rahiminia  – Ascencia Malta Business School

In recent years, artificial intelligence (AI) has moved from being the subject of research to becoming a transformative force with significant impacts on the world of management. It is not merely a technological issue, but a change that touches leadership, organisation, and the relationship between companies and stakeholders. According to Brynjolfsson and McAfee (2017), AI marks the beginning of a “second machine age”, in which the ability to process data and learn from it profoundly reshapes decision-making processes.

One of the most relevant aspects concerns data management. In a global context characterised by economic and geopolitical volatility, managers need tools capable of rapidly interpreting complex information. Davenport and Ronanki (2018) emphasise that AI not only enables real-time data analysis but also supports the creation of predictive scenarios, making decisions more timely and informed. Far from replacing human judgement, these tools act as supports that expand leaders’ interpretative capacity.

The transformation also affects customer management. Today’s consumers expect personalised and immediate experiences, and AI represents the key lever to meet these demands. McKinsey (2021) has shown that companies integrating AI into customer management achieve an average 20% increase in customer satisfaction and a significant improvement in loyalty. However, intensive data use raises issues related to privacy and transparency, requiring managers to strike a balance between technological efficiency and social responsibility.

Another area undergoing major change is human resources management. Predictive algorithms are increasingly used to select talent, reduce turnover risks, and design customised training paths. Tambe, Cappelli and Yakubovich (2019) argue that AI can enhance HR processes but may also introduce systemic biases if not properly governed. Managers are therefore faced with a delicate task: governing innovation while safeguarding fairness and inclusion.

On the ethical and regulatory front, artificial intelligence has become central to international debate. The European Union has recently proposed the AI Act, aiming to guarantee transparency, safety, and accountability (European Commission, 2021). Other regions, such as the United States and China, have adopted different approaches, either emphasising innovation or national security. For global managers, this implies navigating across diverse regulatory environments while ensuring internal consistency. Governance, therefore, becomes a crucial element. As Floridi and Cowls (2019) note, the legitimacy of AI depends not only on its technical utility but also on the organisation’s ability to adopt shared ethical principles.

Concrete cases illustrate the scope of this transformation. Microsoft has introduced generative AI into its collaboration platforms, reducing employees’ time spent on repetitive tasks and freeing resources for strategic activities (Microsoft, 2023). Google, by contrast, uses AI to optimise energy efficiency in its data centres, demonstrating that the technology can contribute to environmental sustainability as well (Google, 2025). These examples show that AI is not just a tool for efficiency but also a driver of cultural innovation and social responsibility.

The question of the future then arises: will AI replace managers? The most realistic answer is no, at least not in a strict sense. Rather, it will force managers to redefine their roles and priorities. While AI handles analytical and repetitive tasks with efficiency, human value remains irreplaceable in areas linked to strategic vision, creativity, empathy, and the ability to drive change. As Wilson and Daugherty (2018) argue, AI will push leaders to focus on what is uniquely human, transforming them into facilitators who align technology and people in a shared direction.

In conclusion, artificial intelligence does not signal the end of management, but the beginning of a new phase. A phase that requires courage, openness to change, and constant attention to balancing innovation with human values. The companies of the future will not be measured solely by how quickly they adopt new technologies, but by how effectively they transform them into instruments for sustainable, inclusive, and shared growth.

References:

Brynjolfsson, E. and McAfee, A. (2017) Machine, Platform, Crowd: Harnessing Our Digital Future. New York: W. W. Norton & Company.

Davenport, T. and Ronanki, R. (2018) ‘Artificial Intelligence for the Real World’, Harvard Business Review, 96(1), pp. 108–116.

European Commission (2021) Proposal for a Regulation laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Brussels: European Union.

Floridi, L. and Cowls, J. (2019) ‘A Unified Framework of Five Principles for AI in Society’, Harvard Data Science Review, 1(1).

Google (2025) How much energy does Google’s AI use? We did the math

McKinsey & Company (2021) The state of AI in 2021.

Microsoft (2023) Introducing Copilot in Microsoft 365: your copilot for work.

Tambe, P., Cappelli, P. and Yakubovich, V. (2019) ‘Artificial Intelligence in Human Resources Management: Challenges and a Path Forward’, California Management Review, 61(4), pp. 15–42.

Wilson, H.J. and Daugherty, P.R. (2018) Human + Machine: Reimagining Work in the Age of AI. Boston: Harvard Business Review Press.