Microsoft Exec Says AI Kills the Career Ladder — and Women May Gain

Men's employment grew 6.3% for each one-point rise in an occupation's AI exposure score — while women's barely moved. That figure, from Pew Research Center senior researcher Nicole Smith, landed at the center of a debate about who actually benefits as AI rewrites career advancement.

The debate's catalyst is Aneesh Raman, Microsoft's chief economic opportunity officer. For the past several months, Raman has been predicting the death of the traditional career ladder as AI reshapes the workplace. In its place, he envisions a "climbing wall" — a structure where progress isn't always upward, and workers chart their own paths based on their unique skills, interests, and opportunities.

That vision carries an obvious catch. If advancement becomes less predictable, what happens to women and other historically marginalized groups, who research suggests benefit from clear criteria for raises and promotions? That question was put to Raman at Aspen Digital's WIN Summit in late October.

What does Raman's "climbing wall" actually mean?

Raman acknowledged the problem head-on. Losing the familiar career playbook, he conceded, could initially feel intimidating. But he argued the shift could ultimately hand workers more freedom to advance in ways that suit their individual strengths and ambitions.

"Over time, you start to climb in ways that are unique to you," Raman said at the summit.

His proposed fix is what he calls "radical transparency" — making sure workers understand how AI is changing their jobs and what opportunities they have to shape their own careers. In plain words: if the old rules are gone, employers owe workers a clear look at the new ones.

Is AI widening the gender gap?

The data Smith presented suggests the answer may already be yes. Her new research at Pew Research Center, published in October 2026, found a sharp divergence in AI-exposed occupations:

• Men's employment grew 6.3% for each one-point increase in an occupation's exposure score.
• Women's employment barely changed across the same exposure increases.
• Among workers with a high school diploma or less, women's employment actually fell.

Smith also flagged a divide in how men and women approach the technology itself. Men, she said, are much more optimistic about AI than women, and may be more inclined to use it to pursue new opportunities. The attitude gap compounds the employment gap: those who lean into the tools are better positioned to capture the jobs the tools create.

"We need to change our mindset and to make sure that we open these conversations to women," Smith said.

Her message to employers and policymakers is straightforward — the technology's benefits won't distribute themselves, and the conversation around AI can't stay a male-dominated one.

Could women actually hold an edge?

Raman pushes a more optimistic read. He believes women could have an advantage in the AI era because they over-index on uniquely human skills — empathy and judgment — that he argues will become increasingly valuable as AI transforms work. Machines handle more of the routine; humans who can read people and exercise judgment become scarcer and more prized.

He makes two concrete predictions on the back of that argument. First, more women will become CEOs. Second, women's representation on corporate boards — currently roughly a third — could climb to half or more.

That's a bold claim set against Smith's data. Board seats moving from a third to parity implies a structural shift in how companies identify and promote talent, not just a change in tone.

What's at stake for employers?

The tension Raman and Smith exposed is now the operative question for corporate leaders: whether employers can make career advancement more flexible without making the path to success less equitable.

Raman's climbing wall offers freedom, but freedom without transparent criteria tends to favor those already inside the network. Smith's numbers show what that looks like in practice — 6.3% employment growth for men in AI-exposed roles against near-flat figures for women, and outright declines for women without college credentials.

The takeaway is simple. If companies adopt the climbing wall, the radical transparency Raman describes stops being a nice-to-have and becomes the mechanism that decides whether the new career model narrows the gender gap or hardens it.

By Grace Kim