Automating Document Intelligence in Statutory City Planning

• URL: http://arxiv.org/abs/2603.13245v1
• Date: Fri, 20 Feb 2026 15:19:12 GMT
• Title: Automating Document Intelligence in Statutory City Planning
• Abstract summary: UK planning authorities face a legislative conflict between the Planning Act, which mandates public access to application documents, and the Data Protection Act, which requires protection of personal information.<n>This paper presents an integrated AI system designed to address these challenges.<n>The system automates the identification and redaction of personal information, extracts key metadata from planning documents, and analyzes architectural drawings for specified features.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: UK planning authorities face a legislative conflict between the Planning Act, which mandates public access to application documents, and the Data Protection Act, which requires protection of personal information. This situation creates a manually intensive workload for processing large document volumes, diverting planning officers to administrative tasks and creating legal compliance risks. This paper presents an integrated AI system designed to address these challenges. The system automates the identification and redaction of personal information, extracts key metadata from planning documents, and analyzes architectural drawings for specified features. It operates with an AI-in-the-Loop (AI2L) design, presenting all suggestions for review and confirmation by planning officers directly within their existing software; no action is committed without explicit human approval. The system is designed to improve its performance over time by learning from this human oversight through active learning prioritization rather than autoapproval. The system is currently being piloted at four diverse UK local authorities. The paper details the system design, the AI2L workflow, and the evaluation framework used in the pilot. Additionally, it describes a preliminary Return on Investment (ROI) model developed to quantify potential savings and secure partner participation. This work provides a case study on deploying AI to reduce administrative burden and manage compliance risk in a public sector environment.

Related papers

• Governance by Design: Architecting Agentic AI for Organizational Learning and Scalable Autonomy [0.3499870393443268]
  Agentic AI systems can pursue goals through multi-step planning and tool-mediated action with limited direct supervision.<n>This transition introduces tensions in implementation, scaling, and governance.<n>We show that governance is implemented through concrete architectural and working arrangements that determine what the system is allowed to do.
  arXiv  Detail & Related papers  (2026-04-17T09:03:42Z)
• LPS-Bench: Benchmarking Safety Awareness of Computer-Use Agents in Long-Horizon Planning under Benign and Adversarial Scenarios [51.52395368061729]
  We present LPS-Bench, a benchmark that evaluates the planning-time safety awareness of MCP-based CUAs under long-horizon tasks.<n> Experiments reveal substantial deficiencies in existing CUAs' ability to maintain safe behavior.<n>We propose mitigation strategies to improve long-horizon planning safety in MCP-based CUA systems.
  arXiv  Detail & Related papers  (2026-02-03T08:40:24Z)
• The AI Agent Index [8.48525754659057]
  Agentic AI systems can plan and execute complex tasks with limited human involvement.<n>There is currently no structured framework for documenting the technical components, intended uses, and safety features of agentic systems.<n>The AI Agent Index is the first public database to document information about currently deployed agentic AI systems.
  arXiv  Detail & Related papers  (2025-02-03T18:59:13Z)
• Developing an Ontology for AI Act Fundamental Rights Impact Assessments [0.0]
  The recently published EU Artificial Intelligence Act (AI Act) regulates the use of AI technologies.<n>One of its novel requirements is the obligation to conduct a Fundamental Rights Impact Assessment (FRIA)<n>We present our novel representation of the FRIA as an ontology based on semantic web standards.
  arXiv  Detail & Related papers  (2024-12-20T00:37:33Z)
• Agent-Oriented Planning in Multi-Agent Systems [54.429028104022066]
  We propose AOP, a novel framework for agent-oriented planning in multi-agent systems.<n>In this study, we identify three critical design principles of agent-oriented planning, including solvability, completeness, and non-redundancy.<n> Extensive experiments demonstrate the advancement of AOP in solving real-world problems compared to both single-agent systems and existing planning strategies for multi-agent systems.
  arXiv  Detail & Related papers  (2024-10-03T04:07:51Z)
• Design of a Quality Management System based on the EU Artificial Intelligence Act [0.0]
  The EU AI Act mandates that providers and deployers of high-risk AI systems establish a quality management system (QMS) This paper introduces a new design concept and prototype for a QMS as a microservice Software as a Service web application.
  arXiv  Detail & Related papers  (2024-08-08T12:14:02Z)
• Ask-before-Plan: Proactive Language Agents for Real-World Planning [68.08024918064503]
  Proactive Agent Planning requires language agents to predict clarification needs based on user-agent conversation and agent-environment interaction. We propose a novel multi-agent framework, Clarification-Execution-Planning (textttCEP), which consists of three agents specialized in clarification, execution, and planning.
  arXiv  Detail & Related papers  (2024-06-18T14:07:28Z)
• Harnessing AI for efficient analysis of complex policy documents: a case study of Executive Order 14110 [44.99833362998488]
  Policy documents, such as legislation, regulations, and executive orders, are crucial in shaping society. This study aims to evaluate the potential of AI in streamlining policy analysis and to identify the strengths and limitations of current AI approaches.
  arXiv  Detail & Related papers  (2024-06-10T11:19:28Z)
• The Foundations of Computational Management: A Systematic Approach to Task Automation for the Integration of Artificial Intelligence into Existing Workflows [55.2480439325792]
  This article introduces Computational Management, a systematic approach to task automation. The article offers three easy step-by-step procedures to begin the process of implementing AI within a workflow.
  arXiv  Detail & Related papers  (2024-02-07T01:45:14Z)
• Automated Process Planning Based on a Semantic Capability Model and SMT [50.76251195257306]
  In research of manufacturing systems and autonomous robots, the term capability is used for a machine-interpretable specification of a system function. We present an approach that combines these two topics: starting from a semantic capability model, an AI planning problem is automatically generated.
  arXiv  Detail & Related papers  (2023-12-14T10:37:34Z)
• Compliance Generation for Privacy Documents under GDPR: A Roadmap for Implementing Automation and Machine Learning [2.1485350418225244]
  Privatech project focuses on corporations and law firms as agents of compliance. Data processors must implement accountability measures to assess and document compliance. We provide a roadmap for compliance assessment and generation by identifying compliance issues.
  arXiv  Detail & Related papers  (2020-12-23T14:46:51Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.