AI Agent Operational Lift for Mibs | Marriott Inclusion And Belonging Society in Provo, Utah

What MIBS Does

The Marriott Inclusion and Belonging Society (MIBS) is a university-affiliated student organization at Brigham Young University, founded in 2021. It operates within the Marriott School of Business with a mission to foster diversity, equity, and inclusion (DEI) in business education and future careers. MIBS likely manages a large membership (5,001-10,000 students), coordinating events, workshops, mentorship programs, and corporate partnerships to create an inclusive community and prepare students for diverse workplaces. Its operations are educational, programmatic, and community-focused, relying on volunteer student leadership and university support.

Why AI Matters at This Scale

For a student society of this size, traditional manual methods for engagement, training, and mentorship matching become inefficient and limit impact. AI matters because it provides the tools to personalize the experience for thousands of individual students, a task impossible for a small staff. It can analyze vast amounts of feedback to understand what works, predict which students might disengage, and automate administrative tasks. This allows MIBS leadership to shift from logistical coordination to strategic, high-touch community building. In the competitive landscape of student organizations and career preparation, leveraging AI can make MIBS's programs more effective, measurable, and scalable, directly supporting its core mission of creating belonging.

Concrete AI Opportunities with ROI Framing

1. Personalized DEI Learning Pathways: An AI-driven platform could assess a student's background, interests, and knowledge gaps to recommend tailored DEI micro-courses and resources. ROI: Increases training completion rates and depth of understanding, leading to a more skilled membership base, which enhances the society's value proposition to corporate partners seeking diverse talent.

2. Predictive Engagement & Retention Analytics: By analyzing event attendance, platform logins, and survey responses, AI models can identify students at risk of disengagement and trigger personalized outreach. ROI: Directly boosts active membership and event participation, maximizing the utility of limited program budgets and strengthening the community's core.

3. AI-Powered Mentor & Opportunity Matching: Moving beyond basic filters, an AI algorithm could match students with alumni mentors, internships, or project teams based on nuanced profile data, career goals, and complementary skills. ROI: Improves mentorship satisfaction and career outcomes, creating powerful success stories that attract new members, retain existing ones, and justify sponsorship funding.

Deployment Risks Specific to This Size Band

Organizations within the 5,001-10,000 person size band, especially in an educational context, face unique AI deployment risks. Data Governance and Privacy is paramount, as student data is highly sensitive and regulated (e.g., FERPA). Any AI system must be meticulously designed for compliance. Integration with Legacy University Systems is a major technical hurdle; the society likely depends on university IT infrastructure (learning management systems, email) that may not have open APIs for AI tools. Funding and Resource Scarcity is acute. While large, the society likely operates on a limited budget without a dedicated IT team, making costly AI development or SaaS subscriptions prohibitive. Finally, Change Management across a large, volunteer-driven student leadership team can be difficult, requiring clear demonstrations of value to ensure adoption and consistent use.