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References: AI Productivity Impact on IS Operations

  1. GitHub Copilot - Wikipedia - Comprehensive coverage of the dominant AI coding assistant including capabilities, controversies, and productivity studies. Foundation for the chapter's AI-in-development content.

  2. AIOps - Wikipedia - Detailed treatment of AI for IT operations including anomaly detection, alert correlation, and automated remediation. Anchors the chapter's AIOps section.

  3. Chatbot - Wikipedia - Coverage of conversational AI evolution from rule-based to LLM-powered virtual agents. Supports the chapter's help desk content.

  4. The AI-Powered Enterprise - Seth Earley - Lifetree Media - Practitioner reference on AI-driven productivity at the enterprise level, with concrete frameworks for measuring uplift; directly aligned with the chapter's measurement content.

  5. Co-Intelligence - Ethan Mollick - Portfolio - Accessible, research-grounded book on working effectively with AI; particularly strong on the change-management dimensions of AI-augmented teams.

  6. GitHub Copilot Productivity Research - GitHub - The original research study on Copilot's measured impact on developer productivity. Required reading for the chapter's measurement content.

  7. GitHub Copilot Documentation - GitHub - Authoritative documentation for the AI coding assistant including governance, content exclusions, and audit log capabilities.

  8. DORA State of DevOps Report - DORA / Google - Annual research on software delivery performance including the impact of AI tools on the four key DORA metrics. Pairs with the chapter's productivity-measurement content.

  9. ServiceNow Now Assist for ITSM - ServiceNow - Vendor reference for AI assistance embedded in the dominant ITSM platform. Concrete example for the chapter's AIOps and help-desk content.

  10. McKinsey State of AI Report - McKinsey - Annual industry survey on AI adoption, productivity uplift, and ROI patterns. Useful for the chapter's evaluate-level outcomes on productivity claims.