Women Executives Use AI Differently — and Better, Coach Says

Women adopt generative AI at lower rates than men, according to research published by Harvard Business School. But an executive coach who has worked with dozens of senior leaders argues that adoption rates are the wrong measure — and that many senior women are not slower because they resist technology. They are more deliberate about how they use it.

"They don't begin with AI. They begin with themselves," writes the author, who teaches and coaches executives. "Many senior-level women aren't slower to adopt AI because they're resistant to technology."

That distinction carries practical weight for corporate AI programs. AI does not understand what matters most in a given situation. It does not know an organization's history, political realities, stakeholder relationships, or the human consequences surrounding a decision. Experienced leaders recognize that judgment remains their responsibility. In the author's framing, AI use that showcases this wisdom will "expand, challenge, and strengthen their thinking without ever replacing it."

Across her coaching work, the author identified four habits in executive women's AI use that consistently produce better outcomes.

1. Define the problem before asking AI to solve it

The most effective AI users do not start by asking the tool what to do. They clarify the problem and define what success looks like first. Recent research from McKinsey and Boston Consulting Group, conducted independently, reaches the same conclusion: AI initiatives are far more likely to create value when leaders begin with a clearly defined business problem and establish measurable outcomes before using the tools. Organizations that start with the tool often struggle to move beyond experimentation because they never determine how to evaluate success.

One example: Lisa, a senior risk executive at a private equity firm, faced a difficult conversation after reporting a colleague for violating compliance rules. Before opening her AI tool, she defined her objective — remain professional while setting firm boundaries. Only then did she ask AI to suggest approaches that were respectful but direct. The difference wasn't a better prompt. Lisa had already done the thinking AI couldn't do.

2. Use AI to build relationship intelligence, not just documents

Many senior women leaders use AI for something more sophisticated than drafting emails. Over time, they build a living record of stakeholder priorities, communication preferences, concerns, and lessons from previous interactions. Rather than approaching each conversation as a blank slate, they use AI to identify patterns, anticipate reactions, and surface overlooked perspectives.

Emerging research supports the underlying capability. A study published in Science found that AI can help people synthesize competing viewpoints, identify common ground, and uncover perspectives individuals struggle to articulate independently. Microsoft researchers similarly found that AI-assisted reflection helped people prepare more thoughtfully for important meetings by encouraging them to reconsider assumptions and adapt their communication.

Two cautions apply. Leaders should anonymize personal or confidential information for security purposes. And because today's AI memory systems remain imperfect, they should regularly review and update stored information.

Anya, who leads process management at an international pharmaceutical company, maintained an evolving record of senior stakeholders — their priorities, past concerns, and communication styles. Before introducing a company-wide technology initiative, she asked AI to think through how each executive was likely to experience the proposal and what competing priorities they might bring. Rather than asking AI what to say, she used it to tailor how she presented information.

3. Let AI prepare while keeping judgment for yourself

Gathering information and making a decision are different jobs. AI can organize research, identify patterns, summarize evidence, and generate alternatives. It cannot determine which trade-offs are worth making or which consequences are acceptable.

A study of more than 100 strategic business decisions found that decision quality was highest when analytical reasoning and intuition worked together, particularly in dynamic environments. Research published in Nature Reviews Psychology concludes that AI is most useful as a decision-support tool, not a substitute for human judgment, because its outputs reflect distinct biases, reasoning failures, and other limitations.

Rolanda, a major gifts officer at a university, used AI to organize research, identify themes, and refine early drafts of an important donor report. She deliberately stopped short of letting AI write the final version. The report reflected years of trust, shared history, and personal connection — only she could determine what deserved emphasis and what tone would strengthen the relationship. AI prepared the work; Rolanda decided what she was willing to stand behind.

4. Don't ask AI to agree with you — ask it to challenge you

Perhaps the most sophisticated use the author observed is asking AI to disagree. Decades of decision research show that deliberately exposing assumptions to challenge leads to better decisions, and newer studies incorporating AI show the tools make that discipline available on demand — offering counterarguments, questioning assumptions, and introducing alternative viewpoints that reduce conformity to dominant opinions.

Caitlin, a government official leading a proposal for a new water treatment plant, used AI exactly this way. She asked it to challenge her assumptions and identify concerns she had failed to anticipate. The resulting counterarguments strengthened both the proposal and her communication strategy before objections surfaced publicly.

The so-what

Business leaders often measure AI success by adoption rates, productivity gains, or speed. Those metrics miss something more important, the author argues: the leaders getting the greatest value from AI are not handing over their judgment — they are using AI to sharpen it. In her words, the future competitive advantage won't belong to the people who ask AI the most questions. It will belong to the people who know which questions only they can answer.