A Data-Driven Framework for Digital Transformation in Smart Cities: Integrating AI, Dashboards, and IoT Readiness

Area of Science:

• Public Administration
• Artificial Intelligence
• Digital Transformation

Background:

• Public administrations face increasing pressure to enhance service efficiency and citizen-centricity.
• Alignment with Environmental, Social, and Governance (ESG) criteria and UN Sustainable Development Goals (UN SDGs) is a growing priority.
• Existing methods for evaluating digital transformation (DT) in the public sector require innovative, automated solutions.

Purpose of the Study:

• To propose an innovative methodology for the automatic evaluation of digital transformation (DT) levels in public sector organizations.
• To integrate traditional assessment techniques with advanced Artificial Intelligence (AI) models for a comprehensive evaluation.
• To validate the proposed methodology in a real-world case study within local public administrations.

Main Methods:

• A dual approach combining expert surveys with AI-based models, including neural networks and transformer architectures.
• Development of a domain-specific corpus using survey data and organizational websites for model training.
• Application and validation of the methodology using real-world data from local public administrations in the Valencian Community, Spain.

Main Results:

• The proposed methodology demonstrated effective performance in assessing the digital transformation (DT) level of public organizations.
• AI-based models, trained on a custom corpus, successfully estimated DT levels, complementing traditional survey methods.
• The study confirmed the potential for international scalability due to the methodology's modular structure and dual-source data foundation.

Conclusions:

• The integration of AI and traditional methods offers an effective solution for automatically evaluating public sector digital transformation (DT).
• The methodology's modularity and data foundation support its adaptability to different administrative and regulatory contexts.
• Technologies like IoT, sensor networks, and AI analytics are crucial for developing resilient, agile, and sustainable Smart City models.