March 12, 2024 at 11:32PM
Summary:
HUD encountered operational challenges during the US Government shutdown leading to the deployment of Robotic Process Automation (RPA) and Artificial Intelligence/Machine Learning (AI/ML). RPA was used to automate monitoring of housing contracts, addressing fragilities in HUD’s legacy systems. AI/ML and big data analysis were employed to understand federal regulation impacts on HR and procurement, informing corrective actions for modernization.
From the meeting notes, it is evident that the U.S. Department of Housing and Urban Development (HUD) faced operational challenges due to legacy systems and government shutdowns. Here are the key takeaways:
1. Use of RPA to Address Operational Challenges:
– HUD implemented Robotic Process Automation (RPA) to automate the monitoring of housing contract expirations, overcoming the constraints of its outdated systems.
– Swift implementation of RPA demonstrated significant progress towards operational resilience and efficiency, with a UiPath bot deployed in less than 90 days.
2. Applying AI/ML and Big Data for HR and Procurement Transformation:
– The challenges in federal acquisition regulations and HR recruitment practices were addressed using AI/ML and big data analysis.
– Leveraging AI/ML capabilities such as LiveObjects allowed HUD to ingest and analyze a vast amount of procurement and HR data to identify bottlenecks and optimize processes.
– The insights derived from AI/ML enabled HUD to improve acquisition and hiring workflows, ensuring accountability, and enhancing stakeholder experiences with government services.
These takeaways highlight the successful application of RPA, AI/ML, and big data to address operational and regulatory challenges at HUD. Additionally, it sets the stage for further exploration of leveraging AI, ML, and RPA for digital transformation in the FinTech Platform in FHA Catalyst.