The Rural Broadband Association (University-Sponsored) / 2025

Addressing Food Insecurity with AI Workflow Optimization

Role

UX Researcher

Team

5 UX Researchers

Timeline

4 Months

Tools

OtterAI

Google Suite

Figjam

Skills

Literature Review

Stakeholder Interviews

Qualitative Analysis

Overview

Our project partner proposed the question of how can AI be deployed in rural spaces? Our goal was the implementation of AI into rural sectors such as agriculture, economy, healthcare, and workforce development to improve daily life. Our team chose to focus on food insecurity as a subset of the topics community and health.

The Problem

Food insecurity resources are hard to reach and organizational workflows are outdated…

Food insecurity resources are hard to reach and organizational workflows are outdated…

Rural households account for nearly one-sixth of households in the US that are food insecure.

Older adults, aged 65+, also face increased challenges in accessing food insecurity resources that require additional support in navigating related financial, mobility, and health care needs. Focusing on our local community in Michigan, our guiding research question was:

Rural households account for nearly one-sixth of households in the US that are food insecure.

Older adults, aged 65+, also face increased challenges in accessing food insecurity resources that require additional support in navigating related financial, mobility, and health care needs. Focusing on our local community in Michigan, our guiding research question was:

How might we leverage AI to improve organizational efficiency of food assistance organizations in rural Michigan so that services and programs can best serve older adults in need?

How might we leverage AI to improve organizational efficiency of food assistance organizations in rural Michigan so that services and programs can best serve older adults in need?

The Process

Researching the user workflow

A literature review was conducted to obtain background information on the current problem space. Information was gathered on current demographics, government policies, food organizations present in Michigan, and case studies for reducing food insecurity.

External data analysis was conducted to discover insights in poverty, income, demographics, and food program-related success.

A total of 8 semi-structured stakeholder interviews were conducted including food program coordinators, food insecurity researchers, an AI expert, and a farm-owner in rural Michigan.

Affinity note mapping was completed using a bottom-up approach to organize 455 interview notes into meta-clusters and 3 core themes.

Here are some of the meta-clusters and themes that were uncovered during the process.

What we uncovered

Michigan has supports to help older adults in need

Many food assistance programs and organizations in already exist in Michigan to support older adults at local and larger scales.

A key challenge is maintaining program operations

Specific challenges include applying/searching for grants, limited staffing, and sharing information to the people in need of support.

Open communication and collaboration is vital

Most programs currently work separately. Communication channels are limited or inefficient, such as multiple group chats and overlapping conversations.

We turned those insights into guiding recommendations

  1. Identify the gaps in services and resources

Local food pantries and food assistance programs are available in rural locations, though they may be limited in reach.

  1. Leverage AI to enhance communication

Strengthen partnerships through data collection, information sharing, and collaboration. 

  1. Empowering agency and choice

Reduce stigma faced by farmers and older adults when accessing food resources

Assessing our ideas

A comparative nested matrix was created to assess gaps in our solution compared to competing or related softwares, websites, programs, and products.

We then assessed the technical feasibility and organizational constraints of implementing an AI-powered solution in food spaces today using a usability scale.

The Solution

Consolidate resources and information into an AI platform for context-specific needs

Consolidate resources and information into an AI platform for context-specific needs

-> Automated web scraping to gather information on up-to-date and available resources

-> Retrieval-Augmented Generation (RAG) system to improve decision-making processes and reduce administrative burden

-> Communication hub for policy updates, grants, and contacts for outreach

Partnership with local broadband companies to provide discounts to nonprofits and food pantries

Partnership with local broadband companies to provide discounts to nonprofits and food pantries

-> Increase broadband access to rural areas, connecting rural communities while also laying additional broadband lines and increasing company customer base

-> Incentivize adoption of AI tool usage for information and resource sharing to members who participate

Impact

Our research project was selected by peers and faculty to be presented at the end-of-semester showcase in front of all stakeholders and class sections. Our project partner provided positive feedback regarding our solution and confirmed our findings as relevant to the current rural broadband space.

Learnings

Rather than directly targeting one population, we can make more impact by solving problems at a higher level.

Rather than directly targeting one population, we can make more impact by solving problems at a higher level.

After conducting background research and our first initial interviews, pain points trended more and more to the food organizations themselves rather than those accessing them. Although recognizing that we lacked interviews with older adults, we chose to conduct a strategic pivot, shifting the focus of our research question and solution to improving the food insecurity organizations and programs so they can better help the target population which they know best.

Still curious?
Let's connect!

Selina Lu. 2026.

Still curious?
Let's connect!

Selina Lu. 2026.

Still curious?
Let's connect!

Selina Lu. 2026.