Make HOW Matter: Aligning Human Leaders in the Age of AI

The Failure Gap Between Agreement and Alignment

Julie described the failure gap as “the space between agreement and alignment.”

In agreement, leaders have enthusiasm. They think something is a great idea. They may even say it is a top priority. But agreement does not always lead to action.

When leaders stay in agreement, they do not reprioritize. They do not shift where assets are going or where investments are going. They do not change how they lead, and they do not help their colleagues lean in and make the change that is necessary.

That is especially true with AI.

Many leadership teams are saying, “Yes, we need to do AI.” But they are not getting aligned around what they need to do differently as leaders. They are not asking how they need to lead differently in order to bring AI into the organization in a meaningful way.

Why Knowing the Why and the What Is Not Enough

Organizations often know why they need to change. The why may be a mission, vision, purpose, board directive, competitive threat, market change, or customer expectation.

Organizations also tend to know what they need to do. Transformations usually come with detailed plans, strategies, timelines, and investments.

But knowing the why and the what is insufficient.

Julie explained that organizations also need to know how to lead differently in order to lead the organization into the future.

For AI adoption, that means leaders need to stop treating AI only as something that changes what other people do. They need to ask how AI changes how they lead.

AI Is Not Just About Making Other People More Efficient

Julie shared that many leaders are willing to ask questions like:

How can AI make loan processing more efficient?

How can AI make recruiting processes go faster?

How can AI take cost out of something in the organization?

How can AI change what other people do?

But they are not asking a more confronting question:

How can AI help me to be a better leader?

That is a fundamentally different question for senior leaders to ask.

It is far more confronting to ask how this new technology can help you become a better leader than it is to ask how AI can make other people more efficient.

Julie compared this moment to the shift that happened in the 1990s, when PCs and desktops began changing professional work. At that time, many senior leaders were willing to invest in what other people did differently. They sent secretaries, administrative assistants, data entry people, new hires, and younger employees to learn how to use computers.

But many senior leaders did not want to put their own hands on the keyboard.

Typing felt like a low-level task. It was not something senior leaders thought they needed to do.

By the end of the 1990s, everything had changed. Leaders who had taken the time to learn the technology could make decisions faster and work differently. Leaders who did not keep up struggled to stay relevant.

Julie argued that AI is creating a similar leadership moment today.

Leaders Need to Get Their Hands on the Keyboard

Julie emphasized that leaders need to become users of AI tools, not just investors in them.

They do not need to become prompt engineers. But they should know enough to get in there, ask good questions, experiment, and play with the tools that are emerging.

As Julie put it, prompt writing may be for 2026 what typing was for 1996.

Leaders should have the basics. Even if they are figuratively “two-finger typing,” they need to understand what it means to use AI.

That personal experience matters. Leaders who are not using AI do not have the fluency to ask better questions of vendors, colleagues, and teams. They do not have the language to talk about how AI is being brought into decision-making processes. They may not understand where human oversight is needed or how to maintain accountability.

Julie described this through the lens of ethical AI, accountability, and transparency. When leaders build fluency, they are better able to think about human accountability, data use, and who is impacted by AI-enabled decisions.

Today’s AI Is the Worst AI You Will Ever Use

Julie acknowledged that AI does not do everything perfectly.

But she also offered an important lens for leaders who are waiting because they think the technology is not there yet.

The AI that leaders are using today is the worst AI they are ever going to use.

It is getting better every single day. The astronomical advances happening every day, every week, and every month mean that whatever you are using today is literally the worst it will ever be.

That does not mean leaders should ignore limitations. It does not mean they should dismiss risk. It means the technology is not the main limitation.

The bigger challenge is that leaders are not getting activated around AI.

Some leaders are being left behind because they are not willing to lean in and learn. They say the technology is not there yet. But Julie argued that it is already capable of helping leaders be better leaders today.

AI Adoption Requires a Leadership Mindset Shift

Julie described several mindsets and group dynamics that are holding leaders back.

One is the belief that AI is “just Google on steroids.” Julie shared that this was her own view 18 months ago. She had to interrupt her own leadership habits and routines and decide to learn more about AI because other people seemed to be doing much more with it.

Another mindset is that AI is best for rote tasks.

This belief sends a cultural signal that AI is for people who do routine things, and not for leaders whose jobs are complex, busy, and different every day.

Julie shared that she has heard leaders say, “I don’t have the same day twice. So how can AI possibly help me?”

That is a deeply held mindset. It suggests that AI is useful for routine work like loan processing or low-level customer service, but not for complex leadership work.

Julie argued that making this mindset visible and being willing to talk about it can go a long way toward making AI more normalized within an organization’s culture.

As long as leaders orient toward AI as something for lower-level work, they send a signal that AI is not for people who want to move up or hold senior-level jobs.

Leaders Cannot Wait for AI to Be Perfect

Another mindset Julie named is, “I can’t use it if it isn’t perfect.”

She compared this to the early days of spreadsheets. When people first used spreadsheet applications, they would enter numbers, use a sum function, and then pull out a calculator to check whether the spreadsheet got the right answer.

They did not trust it yet.

Today, people generally trust that Excel can add up a column of numbers correctly. But they still check the data entry or complex formulas.

Julie encouraged leaders to orient toward AI in a similar way.

AI will give good answers if leaders ask the right questions. But leaders need to talk with colleagues and teams about how they are getting to AI-generated answers. Understanding the process helps leaders determine whether they are getting good quality answers.

Leaders who have never used AI do not have a framework for that. They do not yet understand the dynamic nature of AI, because it is generative and changing all the time.

AI as a Thought Partner, Not Just a Tool

During the keynote discussion, one participant shared that when AI is described as “a tool in your tool belt,” some leaders assume it is just another basic instrument, like a hammer. But when AI is positioned as a thought partner, strategic assistant, or advisor, leaders respond differently.

Julie connected that example to the mindset many senior leaders hold about their own complex thinking.

Many leaders believe they are in their roles because they are capable of solving big problems and thinking strategically. That mindset can make it harder for them to see AI as something that could help them lead better.

But shifting the language from tool to thought partner can help leaders move from agreement into alignment.

Change Management Is Not the Same as Leader Activation

Julie drew an important distinction between change management and leader activation.

Change management is about changing what people do. It is the work of helping people move from system A to system B, adopt a new process, or use a new platform.

Leader activation is different.

Leader activation is about helping leaders change how they lead.

In AI adoption, leaders do not need to learn every detail of every new system. But they do need to build fluency, model the way, create space for new connections, challenge legacy mindsets, share personal challenges and learning, and change the questions they are asking.

Julie shared the example of a CFO who went through an ERP implementation but still insisted that board reports be created in Excel. His team pulled data out of the ERP and put it into Excel for him. Then he complained that the organization was not getting its ROI.

The issue was not the system. The issue was that he had not activated his own change.

Julie sees the same pattern happening with AI. Leaders may invest in AI, defend AI to the board, and advocate for AI use among employees, while not using it themselves.

That creates a cultural gap.

Modeling the Way Builds Confidence

If leaders are not using AI, their people may be afraid to use it too.

Employees may worry that using AI will be seen as cheating, or that if they need help from AI, they do not belong in the room.

Julie noted that this fear is especially important for leaders to address. If senior leaders make their own AI use visible, they create confidence across the organization.

They can say, “Here is how I am using it to be a better leader.”

That helps people feel more comfortable saying, “I generated this report with the help of AI.”

When leaders model the way, they make AI use visible, appropriate, and normalized.

AI Is Revealing Bias in Workplace Culture

Julie also addressed bias as a deeply cultural issue emerging around AI activation.

She shared an example from Harvard where engineers submitted identical AI-generated code to independent observers for review. The female engineers were consistently rated lower than the male engineers.

Female engineers were more likely to be described as less capable or in need of help to solve complicated coding problems. Male engineers were more likely to be described as strategic, innovative, creative, and even brave for trying new tools.

Julie explained that these reactions reflect deeply held biases in organizations.

AI is not creating these biases. It is making them visible in a different way.

Leaders need to think about their own mindsets. They need to examine the assumptions they make about people who are visibly using AI to be more strategic, make better decisions, or improve their work.

Those assumptions drive culture.

If leaders want people to be comfortable and confident using AI, they need to be honest about how bias is showing up in the AI space.

Ethical AI Starts With Leadership Fluency

Julie connected ethical AI to three leadership activation practices:

Building fluency.

Sharing personal challenges and learning.

Changing the questions being asked.

Ethical AI is not only about tools, vendors, or policies. It is also about culture. It is about how organizations choose to use AI with employees, customers, and partners.

Julie described accountability as “human in the loop.” AI proposes. Humans decide.

Leaders need enough fluency to know where AI should be involved, where human oversight is required, and how accountability is maintained.

They also need to understand transparency. That includes what data is being used, how it is being used, and who is impacted.

When leaders do not have personal experience using AI, they may ask the same old habituated questions they have always asked vendors. They may not go the extra mile and think through what is different because the technology is AI.

That is a real risk.

The Ask for Leaders Is Small, but Meaningful

Julie was clear that leaders do not need to become superusers.

They do not need to bet their careers on AI overnight.

They need to come back tomorrow and try something a little different.

They need to incorporate a new asset into how they lead. They need to start thinking differently about what it means to use this emerging toolkit, partner, or thought partner to change how they lead.

Julie described this as “nudges, not shoves.”

Small shifts, done consistently over time, can change the world.

For leaders, that might mean spending a small amount of time learning what AI can do. It might mean trying prompts in a low-stakes way. It might mean making personal learning visible. It might mean asking different questions in meetings.

The goal is not perfection. The goal is activation.

To Go Far, Fast, Get Aligned

AI adoption is not only a technical transformation. It is a leadership transformation.

Organizations need leaders who are willing to build fluency, make their learning visible, challenge legacy mindsets, and ask how AI can help them become better leaders.

Julie closed with a reminder from Karrikins Group:

To go fast, go alone.

To go far, go together.

To go far, fast, get aligned.

That is how you Make HOW Matter.