Research on artificial intelligence, human responsibility, and the communities it shapes.

The research practice of Zachary Rossmiller at the University of Montana.

AI is impacting Montana and our rural and tribal communities. The work here examines what that means — for adoption, for governance, for the systems it runs on, and for its environmental footprint.

Research Themes
intersected studies

Four overlapping threads.

I.
Governance of AI in Institutions
Risk-tiered frameworks for the evaluation, registration, and deployment of AI-assisted systems within institutional settings. Particular attention to operational feasibility within existing compliance regimes, and to the structural question of accountability when systems are built, deployed, and silently updated.
II.
Digital Equity in Rural & Tribal Communities
Rural and tribal communities face persistent gaps in connectivity, compute access, and digital capacity that predate and outlast any single technology wave. This thread examines those gaps across Montana — broadband access, digital fluency, and workforce development — with particular attention to tribal colleges and the communities they serve.
III.
AI & the Environment
Data-center siting, energy infrastructure, and water-rights allocation across the Intermountain West, with current focus on Montana, Idaho, and Wyoming. Examines the physical, political, and economic conditions under which AI infrastructure lands in particular places.
IV.
AI Adoption & Organizational Change
Empirical study of the processes by which organizations evaluate, pilot, and deploy AI systems — navigating compliance, culture, and competing priorities. AI adoption is not a technology problem. It demands organizational change, and the human work of shifting culture, building trust, and leading through uncertainty.
Research Interests
the big questions

The big questions.

Q 1
How should organizations decide which AI tools are ready — and how they should be adopted?
The AI Production Readiness Framework is the first attempt at an answer: a four-dimension rubric, explicit escalation conditions, and graduated review proportional to risk rather than uniform across all tools. The goal is a process that is rigorous without being paralyzing.
Q 2
What is the true environmental cost of AI, and how does it compare to the other digital infrastructure we've already accepted?
Data centers powering TikTok, YouTube, and cloud storage draw the same water and grid capacity as those running AI workloads — but AI absorbs a disproportionate share of the scrutiny. This thread asks for honest accounting: not to excuse AI's footprint, but to understand it in proportion to the infrastructure society has already normalized.
Q 3
Where does AI infrastructure land, and under what conditions — water, land, and power — does it take root?
Fieldwork across Montana, Idaho, and Wyoming examines proposed and operational data-center sites against water-rights allocations, grid-interconnect queues, and land-use records. The Corridor Atlas is the working instrument of this research.
Q 4
How do we ensure rural and tribal communities are not left behind as AI reshapes access, opportunity, and participation?
The digital divide did not begin with AI and will not end with it. The question is whether this moment accelerates existing gaps or becomes an inflection point — and what investments in connectivity, fluency, and community capacity would actually be required to make the latter possible.
Q 5
How do we protect data sovereignty and land sovereignty for communities whose resources and information are most at risk?
AI systems trained on community data, and data centers sited on or near tribal lands, raise sovereignty questions that governance frameworks have not caught up to. This thread examines what meaningful protection looks like — not as compliance, but as a structural commitment to self-determination.
Q 6
How do we ensure skeptics have a voice — and a real path to seeing what AI can and cannot do?
Skepticism is not an obstacle to responsible AI adoption — it is a requirement of it. The harder question is how organizations create space for dissent while still moving forward, and how individuals who are uncertain or resistant find their way to informed participation on their own terms.
About
origin story

Rooted in Montana.

Growing up in rural Montana shaped the person I am. A deep belief in taking care of your neighbors, and in caring for the land you live on. Those values didn't stay in my hometown. They followed me to the University of Montana, and they show up in this work.

Serving UM means serving Montana. The rural communities, the tribal nations, the farmers, small business owners, and educators who are about to feel the economic, environmental, and human weight of an AI wave that is arriving whether they asked for it or not.

The research here is an attempt to understand that impact honestly, and to make sure the work translates into something useful. Education, tools, and decisions that leave Montana better than we found it.

Contact
correspondence welcome

The work is better with collaborators.

Electronic mail
zachary.rossmiller@umontana.edu
Affiliation
University of Montana · Office of the Chief Information Officer
Affiliated Lab
ICARELab.org
Website
zachrossmiller.com
Location
Missoula, Montana

The work here sits at the intersection of technology, policy, and people. Inquiries are welcome from researchers, organizations, and collaborators working on similar problems. Response times typical of a working administrator.