TDNet Discover

The purpose of this mixed-methods capstone study is to develop a strategic and ethically grounded framework to guide the integration of artificial intelligence (AI) into federal information technology modernization initiatives. This study is anchored within the Federal Energy Regulatory Commission (FERC), which represents a broader set of federal agencies facing challenges related to legacy systems, inconsistent governance, organizational resistance, and the need for improved data-driven decision-making. Guided by Kotter’s 8-Step Change Model, the Technology Acceptance Model, and Rogers’ Diffusion of Innovations Theory, the study examines how organizational readiness, user acceptance, and system-level diffusion influence AI adoption in a mission-critical regulatory environment. Data will be collected through semi-structured interviews, stakeholder surveys, and document analysis to identify barriers, enablers, and ethical considerations affecting adoption. Analysis procedures will include thematic coding, descriptive statistics, and synthesis across data sources to develop a comprehensive framework that supports responsible AI integration. The anticipated results include actionable guidance for federal agencies on governance, workforce preparation, ethical safeguards, and change management strategies that promote sustainable AI adoption and enhance modernization outcomes.