SCOPE - Structured Collaboration for Optimizing AI Performance in Enterprises

AAAI 2026 Workshop AIGOV Submission17 Authors

Keywords: AI adoption frameworks, responsible AI, socio-technical systems, AI governance, organizational transformation, cross-functional collaboration, AI readiness assessment, feedback loops, piloting and scaling, leadership in AI, continuous learning, ethical AI implementation, AI lifecycle management, agile AI development, MLOps and AI operations, AI evaluation and metrics, data governance and quality, continuous learning systems, AI change management, human-centered AI, AI literacy and skill development, organizational learning, change leadership, culture of innovation, stakeholder engagement, trustworthy AI, transparency and accountability, AI risk management, model reliability and oversight, reproducibility in AI, foundation model evaluation

TL;DR: SCOPE is a five-pillar framework that helps organizations turn AI strategy into sustainable, enterprise-wide impact.

Abstract: Artificial-intelligence (AI) projects promise transformative gains, yet fewer than one in five organizations reports enterprise-wide success. To close this execution gap, we introduce SCOPE — a five-pillar framework that translates strategy into sustainable AI impact through Structured Collaboration, Cross-functional Involvement, Ongoing Feedback Loops, Piloting & Scaling, and Leadership Endorsement. SCOPE integrates technical rigour with organisational governance, offering (i) a systematic readiness assessment, (ii) an AI-opportunity radar that prioritises high-feasibility use-cases, and (iii) a continuous-learning cycle that couples human and machine feedback. By sequencing small-footprint pilots before enterprise roll-out, the framework reduces time-to-value while maintaining ethical, legal, and risk controls. Comparative analysis of existing AI-adoption models highlights SCOPE’s broader coverage of culture, skills, and cross-departmental accountability, closing critical gaps in current practice. We conclude that treating AI adoption as an iterative, socio-technical programme, rather than a series of isolated technical projects, is essential for achieving resilient, organisation-wide AI maturity.

Submission Number: 17