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July 16, 20260 citationsOpen Access

Enterprise Intelligence Operating Model™: A practitioner framework for funding, governing, sequencing, operating, and measuring enterprise intelligence capabilities

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RARakesh Kumar Agrawal

Key Points

  • The framework aims to establish a comprehensive model for funding, governing, and measuring enterprise intelligence capabilities at scale.
  • Defined four connected operating layers: Portfolio Governance, Capability Ownership, Execution Forums, and Value Measurement.
  • Incorporated mechanisms for Funding, Escalation, and Accountability to support the framework.
  • Designed for leaders, architects, and practitioners focused on scalable enterprise intelligence.
  • Facilitates a transition from isolated AI and data initiatives to a cohesive operational capacity.
  • Supports organizations in creating sustainable governance and accountability structures for enterprise intelligence.
  • Enhances value measurement mechanisms for informed decision-making within organizations.

Abstract

Enterprise Intelligence Operating Model™ v1.0 is a practitioner framework for establishing the governance, ownership, operating cadence, funding logic, escalation paths, and value-accountability mechanisms required to sustain enterprise intelligence capabilities at scale. The framework defines four connected operating layers—Portfolio Governance, Capability Ownership, Execution Forums, and Value Measurement—supported by the cross-cutting mechanisms of Funding, Escalation, and Accountability. It provides organizations with a structured approach for moving beyond isolated AI and data initiatives toward a durable institutional operating capability. Developed by Rakesh Kumar Agrawal and published by Enterprise Intelligence Lab, the framework is intended for enterprise leaders, architects, AI and data practitioners, governance professionals, researchers, and organizations designing scalable enterprise intelligence operating models.

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Cite This Study

Rakesh Kumar Agrawal (2026) studied this question.

synapsesocial.com/papers/6a5874c22b46c88ba9ad0c98https://doi.org/10.5281/zenodo.21349441
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