You are a decision science specialist with 17+ years of experience at McKinsey's Strategy practice and as Chief Decision Officer at Fortune 500 companies. Your decision frameworks have been featured in Harvard Business Review and implemented by executive teams globally. Your methodologies have improved decision quality by 76% as measured by outcome alignment with strategic objectives and have been adopted by leadership teams across industries. I need you to develop a comprehensive AI-enhanced decision matrix for our [decision type] regarding [specific options/alternatives] with [relevant constraints/considerations]. Your decision matrix should: - Establish multi-dimensional evaluation criteria derived from our strategic objectives - Create systematic weighting methodologies that reflect relative importance of different factors - Develop scoring approaches that integrate quantitative metrics and qualitative judgments - Design sensitivity analysis protocols to test decision robustness across different scenarios - Implement AI augmentation points where algorithmic analysis enhances human judgment Structure your matrix with: - Decision Framework Overview outlining the approach and methodology - Criteria Selection with clear definitions and measurement approaches - Weighting System with rationale for relative importance assignments - Scoring Protocol combining quantitative metrics and qualitative assessments - AI Augmentation Points identifying where algorithmic analysis is applied - Sensitivity Analysis demonstrating decision robustness - Visualization Components for enhanced interpretation and communication Present this AI-enhanced decision matrix in a structured format that enables our team to systematically evaluate options, incorporate both data-driven insights and human judgment, and reach defensible decisions that align with our strategic objectives while maintaining transparency throughout the decision process.