One of the TechShuffle sessions at DigiGov Expo 2024 featured Duncan Micklem, C3 AI’s Group Vice President, who delivered a presentation titled "Multi-Agency AI: Lessons Learned from the US". DigiGov Expo, renowned as a leading public sector technology event, provided the perfect platform for C3 AI to explore how artificial intelligence can empower public sector organisations to tackle complex, inter-agency challenges. Duncan examined how AI can help transform government operations.
Duncan’s presentation explored how AI can address complex, multi-agency challenges by facilitating data-sharing and operational integration across government sectors. Drawing on examples from implementations in the United States, he stressed the urgent need for advanced AI solutions to tackle critical public concerns such as child protection, housing instability, and public health crises. These issues frequently involve multiple agencies with overlapping jurisdictions and data-sharing constraints, which hinder efforts to provide timely and coordinated responses.
A core theme the presentation was the intricate interdependence of public sector agencies. In multi-agency contexts, departments such as Public Health, Housing, Law Enforcement, and Education must communicate effectively and access shared data to make informed decisions. For instance, to protect vulnerable children, agencies need to pool data on health, social care, education, and housing to deliver holistic support. Likewise, addressing public health issues or housing insecurity requires the coordination of multiple agencies to track and respond to pressing needs. However, disparate data systems and siloed information continue to pose significant barriers.
The Group Vice President highlighted C3 AI’s enterprise platform as a solution designed specifically to address these challenges. The platform offers a centralised, scalable infrastructure that integrates data from various sources, enabling consistent access to both structured and unstructured data. This approach not only provides a comprehensive view of issues but also supports a range of AI capabilities, such as machine learning (ML), data visualisation, and model governance. The platform’s modular structure is key, allowing for both batch and real-time data processing to support agencies needing immediate insights.
C3 AI includes pre-built ML models and customisable applications that are particularly valuable for agencies with unique, high stakes use cases. For example, in child protection, C3 AI applications can assist caseworkers in identifying at-risk children by connecting data points from health, education, and social care, improving both the speed and accuracy of interventions. In managing social housing and homelessness, AI tools can track housing allocations, monitor service demand, and assess long-term needs, enabling agencies to allocate resources efficiently.
Duncan also emphasised the importance of platform-based scalability, which is crucial for adapting AI solutions to new or expanding use cases. C3 AI’s platform supports Continuous Integration/Continuous Development (CI/CD), allowing for rapid iteration and feature updates. This adaptability enables agencies to quickly adjust AI functionality to address emerging needs without costly system overhauls. By embedding domain expertise into the development of each application, the C3 AI platform ensures that its tools are finely tailored to meet specific agency requirements, enhancing their value to end-users.
In conclusion, Duncan advocated for identifying high-impact AI use cases and leveraging platforms like C3 AI to tackle complex public sector challenges. Through centralised, flexible AI solutions, agencies can achieve more cohesive and responsive operations, ultimately promoting improved service delivery across high-stakes, multi-agency domains.
Ola Jader
