Enacting StatGPT: Experimenting with AI-enabled Performance Management
A new journal paper from Data-Smart City Solutions, published in the International Journal on Smart and Sustainable Cities.
Abstract
Municipal governments stand at a critical inflection point where traditional performance management approaches are fundamentally inadequate for addressing current governance challenges. While the promise of artificial intelligence (AI) dominates discussions about the future of government, many municipal leaders remain uncertain about how to move from abstract potential to tangible impact. This paper cuts through the noise. It challenges conventional thinking about data-driven city management by proposing StatGPT, an AI-enabled transformation framework that fundamentally reimagines how cities measure, understand, and optimize their performance. It offers a strategic opinion derived from a series of intensive, expert-led workshops with senior city managers, data and innovation officers, and service delivery leads from across the United States. Instead of a theoretical exploration, this piece presents a practical vision for AI adoption, arguing that the most promising opportunities lie within three strategic pillars: moving from retrospective reporting to predictive performance intelligence, compliance-focused and optimization-oriented processes, and enhancing strategic communication and external engagement. We present pathways, including visions for unlocking visual data and modernizing service delivery, not as finalized blueprints, but as examples of the kind of focused, high impact thinking that can drive real-world transformation. This is a view from the field, intended as a call to action for leaders ready to harness AI as a tool for building a more responsive, efficient, and trusted government.
About the Author
Marcelle Momha
Marcelle Momha (she/her) is a computer scientist and AI policy specialist with hands-on experience implementing and leveraging emerging technologies to accelerate digital transformation. She designs tools, strategies and analytical frameworks to help governments, executives, and communities develop and deploy roadmaps for responsible AI adoption. Her research focuses on agentic AI, data privacy, and synthetic data standards. She is committed to bridging the digital divide by promoting AI literacy for all.
About the Author
Betsy Gardner
Betsy Gardner is the editor of Data-Smart City Solutions and the producer of the Data-Smart City Pod. Prior to this, Betsy worked in a variety of roles in higher education, focusing on deconstructing racial and gender inequality through research, writing, and facilitation. She also researched government spending and transparency at the Lincoln Institute of Land Policy. Betsy holds a master’s degree in Urban and Regional Policy from Northeastern University, a bachelor’s degree in Art History from Boston University, and a graduate certificate in Digital Storytelling from the Harvard Extension School.