In response, many organizations are launching tools and launching pilots. Some of this activity is necessary. Much of this, however, misses the deeper point. Many leaders are asking: how will AI change? The better question is: what kind of leadership will we build to guide AI?

That distinction is important because technology alone does not shape outcomes. Leadership decisions are made—defining the systems, rules, and capabilities that organizations choose to build and use in their work.

Here are three ways to strengthen what humans can bring to the table in the age of AI.

Don’t let fear dampen ambition

The promise of AI lies in bold experimentation. Even in the most sophisticated organizations, however, fear keeps it quiet. So there is tension. Leaders are asking their people to make bold AI experiments, while launching efficiency programs Employees interpret that as the precursors to job cuts. When people feel exposed, they play less. Breakthrough ideas give way to micro use cases and companies refine the model today instead of creating tomorrow.

what to do: Leaders can reduce fear by creating a protected space for AI experimentation, shielded from the short-term pressure of efficiency. Research has found that such psychological safety critical to performance. Teams that feel safe identify problems earlier, challenge assumptions more freely, and learn faster. If leaders want bold thinking, they must lower the perceived cost of offering it. Otherwise, AI may improve efficiency as the reimagining period progresses.

History proves the point. When Siemens and Toyota reinventing their production systems, they clearly protect jobs. What companies give in short-term savings, they get in long-term innovation. People are motivated to take risks because they believe that the benefits of productivity will be shared, not stolen.

Creating opportunities for people to learn is another way to help reduce fear and free people to think beyond the easy to do. That’s the thought behind it CEO Satya Nadella’s effort to instill a “learn it all” thinking of Microsoft; it makes it okay to not know everything and contributes to product and strategy successes. Another way is to offer regular time for generative work, like Google’s “20% time” practice, where engineers are encouraged to explore personal projects that help the company. AdSense and Google Newsamong other products, started this way.

Use AI as input, not default

From the wheel to the AI ​​agent yesterday, every invention has been supplemented or replaced human actions. The danger is when people rely so much on the tool that they stop thinking.

As access to AI models and computing power spread, analytical advantages eroded. That makes the distinct human ability to interpret context, evaluate trade-offs, understand stakeholder impacts, and question outputs all the more valuable. Stanford’s Human-Centered Artificial Intelligence The institute found that teams that combine AI recommendations with expert management often outperform fully automated systems. Or, as my son’s first grade teacher said: being smart is knowing that a tomato is a fruit. Wisdom is knowing not to put tomatoes in a fruit salad.

What to do: Designing decision-making to ensure that AI informs judgment rather than replaces it. For major decisions, leaders should require teams to document the human reasoning behind AI-informed decisions, making the logic clear so it can be tested. Over time, this builds recognition and institutional memory, and ensures that people take responsibility for their calls, rather than blaming models. Teams can also develop structural resistance as a counterweight to AI overreliance by asking questions like, “What needs to be true for this to hold?”

Put people at the center of value judgments

Ethical leadership in the age of AI is about deciding, clearly and repeatedly, where optimization must stop and human responsibility must begin. Among the questions to be considered: What decisions should algorithms be allowed to make? Who is liable if an AI-based decision causes harm?

What to do: It is important for leaders to say what lines should never be crossed. Embed management workflows, ensuring people make the most important decisions; training managers to evaluate what is possible versus what is responsible.

Judgment, behavior and values ​​cannot be outsourced to AI. These capabilities must be built, then nurtured, so that they become second nature—starting from the top but embedded throughout the organization. In business, trade-offs are inevitable; in the age of AI, they need to be intentional.

Leaders who get this moment right won’t deploy AI tools just because they can; they do so in a way that utilizes psychological safety, human judgment, and ethical clarity. Efficiency without empathy not progress. Innovation without judgment is not leadership.

AI will not decide the future. Leaders – and history will not forgive the difference.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of luck.