Lack of Gender-Diverse Partnership: Is It the Woman or the Firm?

<b><i>Data-Driven Research by ALM Intelligence Suggests Three Reasons Why Gender-Diverse Partnership Fails</b></i><p>It is now common knowledge that female headcount within the ranks of Big Law partnership, both equity and non-equity, has held steady for the past few years at around 20%. The obvious question is, why?

5 minute read December 01, 2017 at 12:04 AM
By
Daniella Isaacson
Lack of Gender-Diverse Partnership: Is It the Woman or the Firm?

It is now common knowledge that female headcount within the ranks of Big Law partnership, both equity and non-equity, has held steady for the past few years at around 20%.

This premium content is locked for LawJournalNewsletters subscribers only

ENJOY UNLIMITED ACCESS TO THE SINGLE SOURCE OF OBJECTIVE LEGAL ANALYSIS, PRACTICAL INSIGHTS, AND NEWS IN LawJournalNewsletters

  • Stay current on the latest information, rulings, regulations, and trends
  • Includes practical, must-have information on copyrights, royalties, AI, and more
  • Tap into expert guidance from top entertainment lawyers and experts

Already have an account? Sign In Now

For enterprise-wide or corporate access, please contact Customer Service at [email protected] or call 1-877-256-2473.

NOT FOR REPRINT

© 2026 ALM Global, LLC, All Rights Reserved. Request academic re-use from www.copyright.com. All other uses, submit a request to [email protected]. For more information visit Asset & Logo Licensing.

Continue Reading

Most firms are aiming their newest tools at the work they already do — pouring their most powerful technology into running the same tasks a little faster. But when everyone automates the same tasks at once, no one pulls ahead. That reaches the future a little faster while leaving a firm’s largest opportunity untouched — and that opportunity isn’t doing more of the existing work, but transforming how the high-value work gets done.

June 01, 2026

Artificial intelligence is rapidly embedding itself into legal workflows, but much of the conversation treats all use cases as if they carry the same level of risk, even if they do not. The more useful question is not whether AI works, but where it can be safely applied and where it cannot.

June 01, 2026