Enterprise Digital Intelligence Capability Maturity Model (EDMM): Definitions, Framework, and Future Roadmap

The China Information and Communications Research Institute (CAICT) shares its research results on the Enterprise Digital Intelligence Capability Maturity Model (EDMM), covering the definitions of data middle platform, intelligent middle platform, and knowledge middle platform, the model’s capability modules, and assessment methods.

1. Background of Data Intelligence

Since the first big‑data white paper in 2014, CAICT has released seven editions, tracking the evolution from big data to data intelligence. The 2023 Data Intelligence White Paper upgrades the previous big‑data focus, emphasizing the convergence of data and AI to drive digital transformation.

Data intelligence extends traditional data processing by tightly coupling data with AI‑driven decision‑making, creating a feedback loop that enhances both data techniques and intelligent models.

2. Development Stages of Data Intelligence

The evolution is divided into three phases: (1) technology‑driven exploration before 2000, (2) data‑driven growth from 2000 to 2020, and (3) application‑driven integration in recent years, where big data and AI merge to form comprehensive data‑intelligent solutions.

3. Value and Significance

Data intelligence improves efficiency at enterprise, industry, and societal levels by automating processes, enabling semi‑automatic decision‑making, and enhancing resource allocation.

4. Foundations for Digital Transformation

The transformation rests on mature data and AI technologies, a five‑core data‑technology ecosystem, and a data‑element philosophy that highlights data’s strategic value.

5. Opportunities and Challenges

While digital transformation promises cost reduction, innovation, and better user experience, enterprises face challenges in goal definition, technology selection, scenario identification, capability building, and evaluation mechanisms.

6. EDMM Standard System

The model consists of four layers: (1) Data‑Intelligent Infrastructure, (2) Data‑Intelligent Middle Platform (data, intelligent, and knowledge middle platforms), (3) Data‑Intelligent Application Layer (generic, scenario‑driven, and industry‑specific applications), and (4) Long‑Term Mechanisms (data literacy, evaluation systems, talent development).

Key elements include:

Infrastructure layer that upgrades traditional data infrastructure to support data‑intelligent workloads.

Middle platform layer that supplies data, models, and knowledge to upper layers.

Application layer that translates middle‑platform capabilities into business value.

Long‑term mechanism that ensures sustained capability growth through talent training, assessment, and governance.

7. Detailed Sub‑Modules

Data‑Intelligent Infrastructure covers storage, computing, organization, and operation capabilities. The Data Middle Platform focuses on data architecture, development, service, governance, and operations. The Intelligent Middle Platform includes AI development, AI operation, AI service, AI security, resource management, and organizational support. The Knowledge Middle Platform aggregates, organizes, mines, and serves enterprise knowledge, enabling large‑model integration.

8. Application Scenarios

Applications are categorized as generic (visualization, analytics), scenario‑driven (digital marketing, intelligent risk control), and industry‑specific (finance, manufacturing, healthcare).

9. Long‑Term Mechanisms

Establishing data‑literacy evaluation models, talent frameworks, and multi‑level training programs ensures continuous improvement of digital intelligence capabilities.

10. Future Work Plan

The institute will refine the existing maturity model, evaluate its effectiveness, and expand standards for data, intelligent, and knowledge middle platforms, while continuing to develop assessment tools and talent cultivation pathways.

Overall, the EDMM provides a systematic framework for enterprises to assess, build, and sustain digital intelligence capabilities, guiding technology selection, capability development, and long‑term transformation success.