Ryan Currie.

Research

Five findings, both obvious and alarming.

In 2026 I completed a doctoral dissertation at Gonzaga University's School of Leadership Studies on a single question: how are leaders in enterprise technology organizations actually making sense of AI transformation?

Doctoral dissertation · 2026

Leadership for the AI-Native Skills Economy: Affirming Human Potential in a Symbiotic Age

Gonzaga University · School of Leadership Studies · Honors, 3.98

Download PDF Cite this

  1. 01

    Leadership is shifting from direction to sensemaking

    The leaders navigating AI transformation most effectively are not issuing confident mandates. They are helping their organizations make sense of a landscape that changes before the last explanation has been absorbed.

    What it means for you

    The core competency of AI-era leadership is interpretation, not instruction. Hire and promote for it accordingly.

  2. 02

    Productivity gains are real but unevenly institutionalized

    Leaders reported genuine improvements in what they could accomplish. Those improvements lived in individual workflows, not in organizational systems. The organization was not getting smarter as a whole.

    What it means for you

    Individual people with access and initiative are moving faster while everyone else stays put. That gap is a leadership failure waiting to surface.

  3. 03

    Tool access is outrunning learning infrastructure

    Organizations are deploying AI capabilities ahead of the structures, culture, and support that would let people develop real competency with those tools. The tools arrive. The learning does not.

    What it means for you

    Surface adoption masks actual capability gaps. Licence counts are not a maturity metric.

  4. 04

    Learning is happening in the flow of work, but scattered

    When it works, embedded learning at the moment of real work is profoundly effective. When it fails, which is most of the time in most organizations, it fails because nobody made it intentional.

    What it means for you

    Leaders are letting learning happen by accident rather than designing conditions where it compounds.

  5. 05

    Skill formation is outpacing credential systems

    People are developing new capabilities in AI-mediated work faster than any formal system is recognizing them. The signals employers use to trust workers are becoming disconnected from what people can actually do.

    What it means for you

    This is the most structurally serious of the five. The gap does not close on its own. It widens.

Also in the library

Patent

Learning content generation and assessment utilizing structured skill data

Microsoft, MS# 503676-US01.

Framework

The Human at Scale model

Six disciplines: Identity, Judgment, Systems, Learning, Capability, Human Potential. A diagnostic you can run on your own organization.

Coming

Talks, slides, and citable extracts

Placeholder until there is something real to put here.