(Yicai) Feb. 26 -- Everyone was quietly waiting for their flight in the airport waiting room, talking softly, with occasional children’s laughter. Suddenly, a 20-something girl jumped up and screamed, "I'm going to die, don't force me, you're all going to die..." She began throwing things, stepped on them, fell down, and cried bitterly. The motherly person next to her hugged her, probably because she had lost emotional control. The faces of those around her showed sympathy, but stayed silent. Anxiety is said to be omnipresent in modern society, uncertainty, oppression in the social environment... When ordinary people view such a scene, they should experience sympathy and their hearts should be touched.

In the course of waiting, I saw an email from Elon Musk to US federal employees on social media: “All federal employees will shortly receive an email requesting to understand what they got done last week. Failure to respond will be taken as a resignation,” Musk wrote.

According to a copy of the email provided to AFP, federal workers were asked to submit “approx. 5 bullets of what you accomplished last week”! Someone receiving the email asked, "How should I go about doing this?" "Is my reply also being reviewed by AI?" I couldn't help but wonder how a superior would respond to this. In view of the rapid penetration of AI how everyone has to talk about AI applications, a topic that has been lingering recently returned to mind: How can our ancient rubric of leadership adapt and transform in this AI era so that we can find our own place and develop others?

Out of a habit stemming from many years of training, I always think about solutions in terms of why, what, and how.

What is the logic underlying reconstruction of leadership in the age of AI? Just imagine what changes will be brought about when an enterprise adds the input of this electrical AI force.

1.The decision-making process, which has a direct nexus with leadership, has undergone a thorough transformation. The traditional ‘quarterly business plan’ has entered into ‘real-time iteration’ and the traditional SWOT analysis is being supplanted by a dynamic risk prediction model, as otherwise any enterprise will be superseded by competitors with a faster market response. The error rate from reliance on conventional business intuition will be 47 percent higher than that of AI-enhanced decision-making, MIT research from 2023 shows. This is a decision-making precipice.

2.With this electrical AI force, the cognitive dimension has performed a leap. The average human working memory has four decision variables, whereas AI can process 200+ variable interactions at the same time. The traditional leader's experiential intuition has now fallen by the wayside and needs to turn instead into data intuition.

3.This new power input will completely alter the structure of organizational effectiveness. Simply laying off employees cannot solve this problem. Rebuilding the organizational structure to adapt to the new intelligent scheduling must be the orientation. A team will thus change into a fluid state, and it will be necessary to redesign positions and capability models, and practice timely and more flexible job scheduling, pivoting from a pure human resources versus AI competitive mode, to a mutually-empowering human resources and AI one, since this will otherwise precipitate a talent drain.

What specific leadership features need to change? Let's wield the keep/stop/start tool while we ponder this.

What needs to be retained? The first thing that springs to mind is human insight, trust between people, and empathy, which are beyond the ken of machines. They are also the cohesion of the team, and they constitute the ‘emotional operating system’ of human-machine collaboration. AI consultants can generate logically rigorous solutions but cannot capture the anxious looks of employees, and AI consultants cannot judge whether a small action of the other party will bring subtle changes in negotiations. Secondly, in crisis management, such as public relations crises, sudden AI downtime, and compliance conflicts, moral judgment, values, and risk assessment instincts bestowed by human evolution are needed to play a role.

What we must discard: It is not difficult to see from the previous reasons for change that the worship of empiricism and the authority to monopolize information are past their sell-by date. Let's adduce a small everyday vignette. A mother dealt with her child saying that Universal Studios was closed that day, and the child picked up the phone and then told her mother KIMI had said it was open today. The end is imaginable. The democratization of knowledge acquisition has come to us. At the same time, the single linear decision-making process of the past and the complex system decision-making possible with the blessing of AI can no longer coexist. Finally, think about what components we need to acquire. We need to develop new knowledge, such as how to collaborate with humans and machines, operate data asset capabilities, and govern intelligent applications. These are all abilities that bosses will have to learn and practice, including new evolutionary needs that we don’t even know about yet.

So, what should we do?

The improvement of self-ability always starts with self-cognition, breaking the reliance on experience, crafting the basic cognitive framework of the AI ​​era, understanding AI, using AI, and turning ourselves into ‘dual-core processors,’ training the decision-making fusion of human intuition (right brain) and AI reasoning (left brain), and developing the habit of using AI.

Rebuilding the ‘knowledge graph’: As the CEO of a consulting company, I cherish a small goal. I plan to reorganize the experience and knowledge I have amassed over the years with the help of AI models, fashion my knowledge base into a more structured, cutting-edge, and comprehensive form, and transform personal experience into structured cognitive assets able to be enhanced by AI. It was hard to imagine the workload of doing this before, but now, with the blessing of AI, I am actually looking forward to it.

In addition to the above, much content and many tools are available for exploring and practicing two-way empowerment, human-machine integration, upgrades of decision-making mechanisms, reshaping of organizational structures, and setting redlines for AI decision-making within an enterprise so that one may become an AI-enabled leader. Confronting novelties, transformation of behavioral modes may not be a standardized path able to be achieved, but thoughts and practices can indeed always speed up.

Finally, in the process of swift change, don’t forget the qualities that leaders have to keep: respect people’s dignity and the need to understand the truth, foster trust between people, improve oneself, bring goodwill and trust to the people around one, and uphold moral values. Employees should have no need to prove their innocence to AI, and AI should not become a big stick in the hands of bosses, but we must rather work together to achieve greater creativity and embrace a bigger world. Let’s encourage one other!

The author is Li Jing, the special researcher at the IFF Institute.