진화하는 에이전틱 테스트 - 사용자 참조 요약 컨텍스트 기반 UiPath 활용

This IDC Perspective is one in a series of IDC studies that examine agentic testing and leverage of both AI and ML for automated software quality (ASQ) solutions, providing vendor analysis and customer reference context for technology adoption and end-user buyer decision-making. We discuss UiPath's agentic testing as part of its intelligent process automation (IPA) portfolio, including its most recent updates moving into 2026, following its earlier product launches. UiPath's overall positioning, breadth, and focused product capability position the company for meeting pressing user needs across the emerging AI and ML testing landscape. We discuss UiPath relative to trends in user adoption demand for combined agentic testing and scaled enterprise execution ranging from performance testing to business application and accessibility testing. We do so in the context of a volatile economy in unprecedented ways with tariffs, ongoing flexible work, geopolitical upheaval, and unpredictability evolving into 2026-2027. We also include a summary of customer references, including a software simulation provider and a global bank."IDC sees adoption of AI and ML for testing, including agentic testing for AI assurance, enabling dynamic execution for high-quality software, innovation, and adaptive responsiveness to dynamically changing environments," said Melinda Ballou, research director, AI Assurance, ALM, Quality, and Portfolio Strategies service, IDC. "Our 2025 research shows that around 91% of organizations are piloting, using, or expanding use of AI for software testing. Key areas of focus include test process improvement insights, visual testing, test case creation, root cause analysis, test prioritization, and synthetic test data. As code creation increases rapidly with the use of code assistants, the role played by agentic testing increases dramatically. It is in part due to these trends that IDC has chosen to prioritize this area as one of several areas of focus for a series of end user-oriented updated vendor analysis that include customer summaries."

Executive Snapshot

Situation Overview

• Drivers for Agentic Testing to Increase Efficiency
• AI, Agentic, and Machine Learning Support for AI Assurance
• UiPath Test Cloud Overview
  • UiPath Release Update Summary - September 2025
• User Reference Summaries
  • Testing Challenges and Strategic Shift
  • Adoption of UiPath
  • Testing Strategy and Implementation
  • Agentic and Autonomous Testing Goals
  • DevOps and ALM Integration and Efficiencies
  • Bank Adoption of UiPath Testing Tools: GenAI and AI Agent Integration
    • Overview
    • Initial Challenges and Evaluation
    • GenAI Adoption
    • Transition to Agentic Automation
    • Infrastructure and Deployment
    • Organizational Enablement and Governance
    • Benefits and Outcomes
    • Key Products Used
    • Strategic Considerations
    • Advice to Peers and Forward-Looking Plans
• Challenges/Opportunities

Advice for the Technology Buyer

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• Related Research
• Synopsis