Demystifying copilot agents and computer use in low-code automation

Piridi, Sarat (2025) Demystifying copilot agents and computer use in low-code automation. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 2884-2893. ISSN 2582-8266

Copilot agents and computer use capabilities offer transformative potential in low-code automation environments by addressing longstanding challenges in traditional automation approaches. Historical limitations include brittle decision trees that collapse when business logic changes and RPA scripts that fail with minor UI updates, creating substantial technical debt and operational inefficiencies across industries. Microsoft's innovative solutions tackle these constraints by shifting from explicit instruction sets to goal-based directives, enabling systems to understand intent rather than following rigid scripted pathways. The technology harnesses advanced language models and multi-modal AI to create genuinely adaptive workflows that evolve with changing requirements. This goal-oriented article delivers adaptive decision-making, contextual awareness, and self-optimization capabilities previously unattainable with conventional automation tools. The technical foundations include natural language understanding, process reasoning engines, and sophisticated integration frameworks that collectively enable resilient enterprise automation. Organizations implementing these technologies experience marked improvements in development efficiency, operational resilience, and scalability while reducing maintenance burdens and technical debt. Implementation guidance derived from successful enterprise deployments highlights future implications for organizational structures, technology integration, and strategic adoption pathways.