by James Balzer
This essay introduces the Horizon Summit framework as a structured anticipatory governance approach. The heuristic of this framework is displayed in Figure 1.
The framework is situated within the growing field of anticipatory governance (Guston, 2014; Poli, 2017; Tõnurist & Orlik, 2025), which seeks to embed future-oriented reasoning into institutional decision-making. It accounts for historical vulnerabilities of policy ‘subjects’ that must be overcome (Horizon 1), scenarios that provide policy optionality and directionality to overcome these vulnerabilities (Horizon 2), and the long-term characteristics of these policy scenarios, including the preferred future (Horizon 3). See Figure 1 for more information.
The framework embeds a suite of six futures methodologies across these horizons – with each horizon comprising two methods each. Drawing on its first applications through the Odyssean Institute – regarding nuclear-risk resilience and AI governance in India – this essay reflects on lessons garnered through the application of the Horizon Summit framework to date, including its application in the broader horizon scanning and scenario mapping discourse.
Figure 1 – The Horizon Summit Framework
Exploring Anticipatory Governance
Anticipatory governance has become a prominent feature of policymaking (Tõnurist & Orlik, 2025). For example, In Chile, the Laboratorio de Gobierno’s Futures Lab integrates participatory foresight with experimental policy design, using scenario workshops to envision alternative futures for public service delivery (GobLab UAI, 2022). Similarly, Peru’s Visión Perú 2050 process, led by the National Centre for Strategic Planning (CEPLAN), demonstrates how foresight frameworks are being indigenised – embedding communal values and intercultural perspectives into long-term strategic planning (CEPLAN, 2019). Institutionalising anticipatory governance within the public sector allows foresight to be a continuous temporal practice, rather than merely a set of bespoke methodological tools, allowing policymakers to act from future-oriented logics instead of reacting solely to the urgencies of the present (Poli, 2017; Miller et al., 2018; Priebe et al., 2025).
However, anticipatory governance can often be overridden by short-termist political priorities and reactionary responses to crises – disconnecting anticipatory governance from durable implementation pathways (Miller et al., 2018; Priebe et al., 2025).
Policymakers must actively appreciate complexity, uncertainty and disruption in future-oriented policy design (Feduzi et al., 2022). The application of strategic foresight and anticipatory governance evades policy ‘lock-in’ that leads to dangerous path dependence towards the ‘used future’ (Goldstein et al., 2023; Inayatullah, 2008), resulting in the ‘euphoria-implementation-depression’ cycle outlined in Figure 2.
Figure 2 – Policy euphoria-implementation-depression cycle (Source: Cashore et al., 2024)
Overview of the Horizon Summit Framework
The Horizon Summit framework uses participatory horizon scanning designed to expose historical risk factors, articulate preferred, alternative and harmful policy scenarios and characterise the long-term implementation pathway for the preferred future (Figure 1). It enables participants to identify which institutional and societal capacities (mis)align with long-term policy goals, via the participatory workshops presented in Figure 3.
Figure 3 – A summary of the 6 workshops of the Horizon Summit framework
The framework’s relationship to the 3 horizons framework by Curry & Hodgson (2008) must be clarified. Curry & Hodgson (2008) do not map change through a sequential timeline but describe 3 simultaneous patterns of change – Horizon 1 as the dominant but declining system, Horizon 2 as the contested space of transition and innovation, and Horizon 3 as the currently marginal but emergent future vision.
The Horizon Summit does not reproduce this logic directly. Instead, it leverages Curry & Hodgson’s central normative commitments: the necessity to overcome business-as-usual assumptions (Horizon 1) and navigate medium-term disruption (Horizon 2) to achieve long-term systemic transformation (Horizon 3).
Therefore, the Horizon Summit shares the transformative ambition of Curry & Hodgson’s framework while deploying a more sequential diagnostic and generative structure that moves from historical risk mapping (Horizon 1) through scenario development (Horizon 2) to preferred future operationalisation (Horizon 3). This sequential approach is consistent with broader horizon scanning practice, including the environmental scanning tool by Hines et al. (2018), which emphasises the importance of structured analysis across different time horizons to surface emerging risks and opportunities that conventional planning processes overlook.
So while the Horizon Summit is distinct from Curry & Hodgson’s model, it is a reinterpretation combining Curry & Hodgson’s normative commitments, with an applied approach reflective of participatory horizon scanning posited by Hines et al. (2018).
Furthermore, the Horizon Summit framework has a specific focus on closing the deficit between foresight diagnosis and actionable policy pathways in anticipatory governance processes – a deficit explored by Priebe et al. (2025) and Caillol (2024).
By generating ‘pathways’ (Figure 4), the Horizon Summit is suited to circumstances of high uncertainty and high agency – complementing the growing ecosystem of anticipatory governance tools available to policymakers (see Miller et al., 2018; Tõnurist & Orlik, 2025). Where existing anticipatory governance initiatives excel at analysis, the Horizon Summit’s sequential six-workshop structure ensures diagnostic foresight is directly connected to implementation pathways – operationalising what Poli (2017) describes as an embedded institutional capacity, rather than a bespoke, occasional planning exercise.
Figure 4 – Comparing scenarios, forecasting and roadmaps, with pathways (Source: Sharpe et al., 2016).
The Framework in Practice
Horizon 1: Historical Governance Inequities and Risk Factors
The first horizon explores the historical inequities and risk factors that have defined a policy domain. Through Stakeholder Mapping and Domain Mapping, participants identify the historical power asymmetries of a policy domain; gleaning who is most affected but least empowered, and which multi-layered risk factors emerge for vulnerable groups. This includes exploring threat, exposure, and vulnerability as distinct but interacting risk factors, as per Roberts (2023):
- Threat refers to the seriousness of an external threat
- Exposure refers to whether a particular part of a society operations will become exposed to the threat
- Vulnerability refers to internal and external factors that are likely to exacerbate the threat
Figure 5 – Stakeholder mapping framework (Source: Cairns & Wright, 2018).
By using archetypes and personas – such as ‘context setters’ (high power, low interest) or ‘subjects’ (high interest, low power) participants can humanise abstract governance dynamics. This provides a richer substrate for later scenario building, grounding the process in lived experience and social structure (Cairns & Wright, 2018) (see Figure 5).
Subsequently, domain mapping of risk factors (Figure 7) focuses on the ‘subject’, as defined in Figure 6.
Figure 6 – Domain Mapping against factors of ‘risk’ (framework inspired by Hines et al., 2018)
Horizon 2: Developing Policy Scenarios
The second horizon shifts to envisioning and evaluating policy scenarios for the policy ‘subject’, accounting for the factors of risk analysed through domain mapping. Using Causal Layered Analysis (CLA) Incasting (Figure 7) (Inayatullah, 1998), participants surface not just the litany (characteristics), but also worldviews, narratives and metaphors (mentality) of different futures for the policy subject. This is done against variables of organisational and systemic policy capacity (Figure 8) (Wu et al., 2015; Howlett & Ramesh, 2016):
- Organisational Policy Capacity: The ability for public sector institutions to analyse, implement and evaluate their policy agenda.
- Systemic Policy Capacity: The ability for society-at-large to generate an authorising and enabling environment for a particular policy issue to be designed and implemented.
Figure 7 – Causal Layered Analysis (CLA) (Source: Inayatullah, 1998)
Figure 8 – Double variable scenario mapping heuristic for Horizon 2
Resultantly, each policy scenario in Figure 9 is analysed through the framework in Figure 9.
Figure 9 – CLA framework that each scenario is analysed through 
Building upon the breadth and depth of this scenario mapping, the workshop then applies the XLRM matrix. The XLRM framework is a core analytical tool within the Decision Making under Deep Uncertainty (DMDU) approach (Lempert, 2019). It stands for Exogenous factors (X), Levers (L), Relationships (R), and Metrics (M). Exogenous factors are external conditions outside the decision-maker’s control, such as climate or geopolitical trends. Levers are the policies or interventions that can be adjusted to influence outcomes. Relationships describe how these variables interact within a model or system, while Metrics define what success looks like – the criteria used to evaluate outcomes. Together, XLRM provides a structured way to organise the key elements of a complex problem before exploring how they behave under uncertainty.
The XLRM matrix was added to Horizon 2 to enable more robust optionality in scenario mapping, and provides space for transformative, exploratory futures within each scenario. It also supports the integration of the Horizon Summit into deliberative processes such as the Odyssean Process (see Dal Prá et al., 2023).
Horizon 3: Characteristics and actions to achieve the long-term preferred future
The third horizon operationalises the preferred future by working backwards – through stress testing and backcasting. While Horizon 1 and Horizon 2 focus on particular policy issues, Horizon 3 focuses on solutions to these issues (i.e. the preferred future)
Figure 10 – Stress testing framework (inspired by Australian Department of the Prime Minister and Cabinet, 2024).
Specifically, stress-testing methods are used to assess each of the Horizon 2 scenarios against factors of ‘resilience’ (Roberts, 2023). These factors of resilience are the (in)ability for a solution to absorb disruption to its trajectory, adapt to disruption and transform over time – ultimately being antifragile (Taleb, 2014) (see Figure 10)
Central to this horizon is the Absorb–Adapt–Transform resilience framework (Roberts, 2023). Participants define what these capacities look like in harmful, alternative, and preferred futures. They then develop qualitative indicators to monitor long-term trajectories, effectively creating a benchmark for long-term durability of the preferred future.
For example, in a recent Horizon Summit exploring the 2nd order impacts of a nuclear strike (see ‘Case 1’ below), qualitative indicators of the preferred future included the amount of prepositioned regional stockpiles of emergency equipment (absorb), R&D expenditure on UV resistant crops for a nuclear winter, in addition to the amount of government investments in seed banking systems (absorb), and the national quantity of genetically engineered seeds that can germinate under conditions of nuclear winter (transform).
Finally, backcasting is used to identify clear causal steps that would lead to the preferred future. This ideates specific actions required to achieve the preferred future developed in Horizon 2.
Backcasting for the preferred future is also done against the factors of resilience (Figure 11). This provides clear steps to implement policies that achieve the preferred future.
Figure 11 – Backcasting framework
Case Illustrations
Case 1: 2nd Order Impacts of a Nuclear Strike
The initial pilot of the Horizon Summit applied the framework to the second-order impacts of a hypothetical nuclear strike – a project conducted by the Odyssean Institute.
This exercise convened diverse participants – from humanitarian planners and resilience experts to supply chain analysts – to examine how current systems might fail under extreme stress (Horizon 1), what alternative configurations could enable adaptation (Horizon 2), and what pathways could lead to resilient, locally grounded recovery systems (Horizon 3). Horizon 1 workshops identified critical weaknesses in current humanitarian logistics and global trade dependencies; Horizon 2 sessions developed scenarios exploring decentralised, adaptive, and regionalised supply chains; and Horizon 3 activities involved backcasting and stress-testing possible long-term solutions such as micro-hubs, local volunteer networks and alternative food systems to determine their robustness under crisis conditions.
Specifically, the Horizon Summit identified actionable measures to address cascading, second-order impacts of a nuclear strike. Key measures included localised humanitarian logistics, diversified transport networks, and resilient food systems through strategies like seaweed-based nutrition, UV-tolerant crops and resilient seed banks. Governance measures emphasised whole-of-government continuity planning, gender-sensitive civil defence frameworks, and integrated data infrastructures for real-time decision-making. These outputs shifted participants’ approach from reactive crisis management to proactive resilience-building, embedding foresight into policy design.
Importantly, these findings are now being socialised with the UK Cabinet Office and UK Ministry of Defence to inform nuclear preparedness and shape their analytical approach to long-term nuclear risks. This engagement is influencing scenario exercises, continuity planning, and investment in resilient food and logistics systems, ensuring that UK policymakers integrate systemic foresight into national security strategies.
Case 2: AI Governance and Regulation in India
Another real-world case study was applying the Horizon Summit to exploring AI regulation futures in India, as a collaboration between the Odyssean Institute and Sustainable Living Lab (SL2).
The Horizon Summit exposed the asymmetries between India’s fast-moving technological sector and its slower institutional capacity for digital regulation. Stakeholder mapping and domain mapping (Horizon 1) revealed that while big tech and investors dominate near-term governance, long-term resilience depends on recalibrating the balance of influence between government, industry and society; particularly discerned by establishing the preferred future in Horizon 2 and backcasting in Horizon 3.
This revealed that India’s governance resilience hinges on its ability to absorb shocks (such as data misuse and job displacement), adapt through agile regulatory design, and transform by embedding inclusive, participatory mechanisms in AI oversight. The preferred future scenario, Harmony and Prosperity for All, illustrated how balanced collaboration between state, industry and society could sustain innovation while safeguarding equity and accountability. By contrast, alternative scenarios such as Technocratic Illusion and Big Society illuminated the risks of regulatory capture, over-regulation and societal fragmentation.
The Odyssean Institute and SL2 were able to socialise these findings at a preparatory event for the India AI Impact Summit 2026. This event was hosted by Intel Corporation and involved policymakers and industry professionals. Discussing the Horizon Summit framework with participants has spun out into a long-term ‘study group’ that intends to embed the framework into regulatory analysis practices that synergise the interests and outlooks of government and industry stakeholders in India.
Conclusion: Towards Anticipatory and Authorising Governance
While anticipatory governance frameworks are increasingly embedded in government institutions globally, the persistent gap between diagnostic foresight and actionable policy pathways remains a critical methodological challenge. The Horizon Summit directly addresses this gap, bridging analysis and implementation through a structured, participatory sequence that operationalises anticipatory reasoning across all three horizons.
The framework bridges historical inequities, with medium-term scenario orientation and long-term solution building, providing space to explore long-term opportunities through a lens of durability and sustainment under uncertainty. It prioritises robustness and continuity in volatile contexts, ensuring that opportunities are framed as pathways to resilience rather than aspirational leaps detached from systemic constraints.
However, future iterations could make this balance explicit, by clarifying resilience-driven opportunity mapping is not about limiting ambition but about embedding innovation within credible governance trajectories. Resultantly, the Horizon Summit advances anticipatory governance as both a defensive and enabling tool – equipping policymakers to navigate uncertainty and produce resilience.
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