As AI becomes more and more incorporated into the functioning of organizations in various areas, from customer service to decision making, the role of management is changing significantly. Traditional management theories, which have been the primary source of leadership guidance for organizations, may no longer be sufficient to address the complexities associated with AI. As a result, a fundamental shift in new management theories that are specifically designed to address the demands of the age of AI emerges.

First, the implementation of AI has increased the speed of decision making in organizations. With computers powered by AI that can handle large amounts of data in a lightning-fast manner, managers are confronted with the difficult task of making informed decisions amidst the flood of real-time information. Traditional management theories, such as Taylorism or Scientific Management, focus on linear structures and centralized decision-making processes.

However, with the advent of AI, where decisions can be made through machine-learning algorithms and prescriptive analytics, a more decentralized and flexible approach to management is necessary. For example, companies like Google and Amazon have adopted a data-driven culture of decision-making, which involves employees at every level taking part in the process of building artificial intelligence-versed solutions that influence their decisions.

Also, it is becoming mandatory for the organizational processes to include AI which leads to the re-evaluation of the traditional leadership and management processes. In traditional management theories, the attention of the scholars is often directed at command-and-control systems, where the managers impose authority over the employees and employees are only expected to follow the directives given. On the other hand, in the AI-driven world with less human intervention, managers are expected to play the roles of facilitators and mentors.

To build an organization where employees are continuously leaning and being adaptive to change, business leaders must foster a culture where workers are encouraged to collaborate with these systems instead of perceiving them as threats to their job security. For instance, companies like IBM have implemented AI-based tools, such as Watson, to augment the capabilities of their workforce, enabling employees to focus on higher-value tasks while AI handles repetitive tasks. Such system gives customers and workforce the opportunity to do more complex matters, while AI handles all the mundane tasks.
 

Furthermore, the ethical implications of AI adoption in organizations emphazsize the need for new management theories that prioritize transparency, accountability, and ethical decision-making. As AI algorithms become increasingly autonomous and pervasive, there is a growing concern regarding bias, privacy infringements, and unintended consequences. Traditional management theories may not adequately address these ethical dilemmas, as they often prioritize efficiency and productivity over ethical considerations. Therefore, new management theories must incorporate principles of responsible AI governance, such as fairness, interpretability, and accountability. For instance, companies like Microsoft have established dedicated teams tasked with ensuring the ethical use of AI across their products and services, demonstrating a commitment to responsible AI stewardship.

Additionally, the proliferation of AI-powered automation raises questions about the future of work and the role of human labor in organizations. While AI has the potential to streamline operations and increase efficiency, it also poses a threat to jobs traditionally performed by humans. In this context, new management theories must address the socio-economic implications of AI-driven automation and advocate for strategies to mitigate potential job displacement. For instance, proponents of universal basic income (UBI) argue that providing a guaranteed income to all citizens could offset the negative impacts of automation on employment and ensure economic security in the age of AI.

In summary, AI brings the ‘revolution’ or ‘paradigm shift’ in the way the companies are managed and run. The classical business theories, coming from the industrial era point of view, can hardly be regarded as relevant due to the fact that AI has been proven to be highly complex and new things about it continue to emerge.

Consequently, management theories must be developed that serve as guidelines for ramping up agility, transparency, governance ethics, and human-AI collaboration. These new management theories reinventing leadership, organizational design, decision-making process, and future of work are instrumental in the ability for enterprises to survive and create an environment that benefits the overall good of human society in the world of AI.

The author is the Founder and CEO of Hungry Workhorse, a digital, culture, and customer experience transformation consulting firm. He is a Fellow at the US-based Institute for Digital Transformation. He is the Chair of the Digital Transformation IT Governance Committee of FINEX Academy. He teaches strategic management and digital transformation in the MBA Program of De La Salle University. The author may be emailed at [email protected]