Governments don’t need more data. Data has been more abundant than ever. Yet, there is still a crucial gap in synthesis, whereby governments are not set up in ways that allow the creation and sharing of knowledge — let alone the important process of synthesising information from multiple sources to generate relevant actions. In this publication, the concept of “Generative Shared Intelligence” (GSI) offers a model for addressing multidimensional problems in governance, emphasising the need for more flexible and collaborative structures designed for the sole purpose of sharing intelligence.

Governments are no strangers to complexity and unpredictability. The notion of a “polycrisis,” where multiple crises overlap and intensify, has become a defining feature of contemporary governance. Traditional administrative methods, designed for more stable and predictable environments, are increasingly inadequate. Governments must now adopt dynamic and adaptive strategies to manage both immediate crises and long-term systemic shifts.

The interconnected nature of global challenges necessitates a dual focus on rapid response and sustained strategic planning. This requires governments to be flexible, avoiding the pitfalls of siloed thinking and rigid bureaucratic processes. The ability to pivot quickly and effectively reallocate resources is crucial in this volatile landscape.

This paper discusses: 

• Dynamic contexts as the new normal
• The central role of intelligence
• A philosophy of open, engaged government
• Generative approaches to governance
• Operationalising generative shared intelligence
• Renewal of democracy through shared intelligence
• Balancing complexity and simplicity

To implement GSI, governments can adopt a range of strategies:

1. Intelligent centres of government: Establishing agile, networked structures at the core of government to orchestrate knowledge and resources effectively.
2. Whole-of-Government action: Creating horizontal clusters for key missions, such as achieving net zero emissions or pandemic response, breaking down traditional silos.
3. Modernised public finance: Linking financial practices to impact, using data and investment models to track and optimise outcomes.
4. Digital infrastructures: Building standardised, flexible digital systems to support efficient governance and public services.
5. Mesh organisation: Forming partnerships across government tiers and sectors, with shared responsibilities and mutual accountability.
6. Innovation and learning: Embracing continuous learning and experimentation to discover better solutions and inform policy.
7. A relational state: Enhancing collaboration with citizens, leveraging lived experiences and insights to improve public services.
8. Richer public engagement: Utilising a wide array of participatory methods, from budgeting to citizens’ assemblies, to develop inclusive decision-making.
9. Fit-for-purpose institutions: Continuously adapting and designing institutions to meet contemporary challenges effectively.
10. Risk management and foresight: Proactively scanning for potential crises and opportunities.
11. Synthesis and holistic thought: Integrating diverse forms of intelligence to guide comprehensive and informed action.
12. Skills and training: Investing in the skills and capacity of government officials to enhance decision-making and implementation.

Governing with generative shared intelligence (GSI) should be the defining goal for all governments, a mindset and method that runs through everything they do.