Haier’s success is the result of a root-and-branch overhaul of its once-traditional management model. Led by Zhang Ruimin, Haier’s renegade chairman and CEO, the radical makeover focused on three objectives:

1. Turning every employee into an entrepreneur

1. Creating “zero distance” between employees and users

1. Making the company a power node in an ever-expanding, web-centric ecosystem

Even when an organization is led by a pioneering CEO like Jan Wallander or Zhang Ruimin, crafting a new management model is more about “discover and test” than “engineer and impose.

Successful efforts at building trust are often achieved through trial-and-error experimentation in the local setting in which they are to be used. Remember how Renick handled the problem of students losing their Hope Scholarships. He started small. He tried things and kept track of their effect, jettisoning or improving what didn’t work, incrementally expanding what did work, until he and his colleagues had essentially transformed a university. That’s what I mean by trial-and-error experimentation— modifying systems to better meet, in that case, student needs. A strategy like seeing, welcoming, and supporting can guide the search for tactics needed to build trust. But the process isn’t complete without further effort of developing tactics to implement the strategy, often through trial and error.

Building on our study findings that CEOs who lead through influence were the most effective, we followed up by conducting interviews to learn about the development advice and training these leaders had received. We asked leaders to describe how they made the journey to becoming the highly effective leaders they were. What emerged is that a leader’s evolution generally proceeds in iterative cycles, with steps forward often followed by backsliding into old habits and then a renewed effort at change. It’s a process of trial and error, and often of fits and starts, as the daily grind of immediate demands diverts attention from one’s inner work. Those who continue to progress in the journey typically go through a three-phase cycle.

First, they are confronted with a necessity for change either because they took on a new challenge that reveals the shortfalls in their leadership or through feedback from their higher-up, colleagues, or mentor.

There is a different way forward. Artificial intelligence doesn’t have to be what it is today. We don’t need to accept the logic of unprecedented scale and consumption to achieve advancement and progress. So much of what our society actually needs—better health care and education, clean air and clean water, a faster transition away from fossil fuels—can be assisted and advanced with, and sometimes even necessitates, significantly smaller AI models and a diversity of other approaches. AI alone won’t be enough, either: We’ll also need more social cohesion and global cooperation, some of the very things being challenged by the existing vision of AI development.