Towards the AI State: Anticipatory Governance as the New Operating System for Global Growth

The present paper examines the widening institutional gap of the 21st century, characterized by a structural mismatch between the exponential velocity of technological change and the analog inertia of 20th-century state administrations. As the global economic center of gravity shifts toward the global majority, current governance structures face a volatility tax caused by reactive, siloed, and linear processing. The paper proposes a transition to Anticipatory Governance as a new institutional operating system designed to navigate the modern "polycrisis" of climate volatility, AI disruption, and societal fragmentation. The framework is built upon three foundational pillars: the institutionalization of Strategic Foresight into budgeting and legislation; the creation of an evidence-based science-policy interface to ensure multidisciplinary agility; and the implementation of Human-Centric AI Governance through tools like Algorithmic Impact Assessments (AIA). A four-stage Public Administration Maturity Model is developed to guide to the policy makers for implementing their Anticipatory Governance systems.

Keywords: Anticipatory Governance, Artificial Intelligence, Polycrisis, Strategic Foresight, Digital Transformation

1. The Institutional Crisis of the 21st Century

The global economic landscape has undergone a tectonic shift during the first quarter of the 21st century, moving from a unipolar framework toward a multipolar reality dominated by the "Global Majority." This transition is evidenced by the ascent of the BRICS nations, whose combined potential in terms of economic volume, resource extraction, and population now represents the largest share of global productivity (National Centre, 2025). However, a fundamental paradox defines this era: while investments in physical infrastructure, digital platforms, and human capital are accelerating at exponential rates, the institutional operating systems designed to steer, regulate, and stabilize this growth remain anchored in 20th-century "analog" paradigms. These legacy systems, characterized by linear processing, bureaucratic silos, and reactive crisis management, are increasingly incapable of navigating the "polycrisis" of technological disruption, climate volatility, and societal fragmentation.

The current governance architectures face a critical juncture. The mismatch between the velocity of technological change and the inertia of state administrations has created a ‘volatility tax’ on global growth. Traditional bureaucracies are often structured to respond to shocks only after they have manifested, a strategy that is increasingly risky in an age of viral pandemics, unchecked Artificial Intelligence (AI) development, and rapid climate tipping points (WEF, 2025). Without a radical transformation of the state itself - rebooting public administration to become future-oriented, agile, and anticipatory – the full potential of the Global Majority will remain suppressed by rigid, 20th-century frameworks that erode trust and exacerbate inequality.

To address this, the proposed "New Platform for Global Growth" must prioritize investment in the public sector's cognitive and administrative capacity. This is not merely an exercise in digitization, but a structural shift toward a new operating system for the state. By transitioning from a reactive "Analog Model" to an "Anticipatory Governance Ecosystem," governments can unlock a "stability dividend" that lowers risk premiums for investors and ensures that technological advancement translates into sustainable human well-being.

2. The Mismatch of Speed, Scale, and Scope

The core challenge facing global stability is a threefold structural mismatch in how public administrations interact with modern disruptions.

2.1 The Speed Mismatch: Linear Bureaucracy vs. Exponential Change

Traditional public administration operates on linear cycles. Legislative processes, regulatory assessments, and budgetary planning often take years to conclude. In contrast, the unmanned revolution, quantum computing, and generative AI are evolving on exponential curves. This speed gap means that by the time a regulatory framework is enacted, the technology it governs has often moved several generations forward (OECD, 2025). This lag creates a vacuum of oversight, leading to either reckless adoption or stifling prohibition, both of which hinder sustainable growth.

2.2 The Scope Mismatch: Siloed Governance vs. Systemic Challenges

Analog states are typically organized into thematic silos—ministries of health, agriculture, energy, or labor. However, contemporary challenges are inherently cross-cutting and systemic. For instance, the management of water resources in the context of climate change is simultaneously a matter of agricultural productivity, public health, energy security, and industrial policy. When these issues are addressed through fragmented frameworks, the resulting policies often conflict, leading to inefficiencies and "policy conflicts" that undermine national development strategies (OECD, 2022).

2.3 The Scale Mismatch: Reactive Response vs. Proactive Resilience

The "Analog State" is essentially a reactive entity. It builds flood defenses after a flood; it updates pandemic protocols after a virus has spread; it regulates financial markets after a crash. In the 21^st century, the scale and connectivity of global systems mean that localized shocks can cascade into global catastrophes in days. The cost of being reactive is no longer sustainable. Evidence from sovereign bond markets suggests that investors demand significantly higher risk premiums from nations with low governance effectiveness and political instability, as they are perceived as less capable of absorbing and rebounding from shocks (BCAM, 2025).

Table 1 shows the shortcomings of the analog state in dealing with three mismatches and the requirement for anticipatory governance in the wake of polycrisis and emerging opportunities.

Table 1: Analog State vs. Anticipatory Governance across three mismatches

Source: Analysis synthesized from OECD and UN governance frameworks

The transition from an analog state to anticipatory governance represents a shift from reactive, siloed institutions to an agile, systemic operating system. In terms of speed, the analog state relies on linear, multi-year policy cycles that often fail to keep pace with exponential change; conversely, anticipatory governance requires agile and iterative oversight. Regarding scope, traditional governance is limited by departmental silos and fragmented data, whereas the new model utilizes systemic, "phenomenon-based" taskforces. The benchmark for scale shows the analog state operating through reactive, ex-post crisis management, while anticipatory governance emphasizes proactive, ex-ante stress-testing and foresight. Finally, the data use layer distinguishes the two by moving from a reliance on historical benchmarks and descriptive statistics toward the use of predictive analytics and horizon scanning to navigate multiple plausible futures. In today’s ever more complex and uncertain global affairs, the anticipatory governance suggests governance to be more evidence-based drawing on advanced data analytics and artificial intelligence. Given this background, the following sections describe the key pillars to constitute foundations for the new anticipatory governance systems.

3. Foundations of the New Anticipatory Governance Systems

Addressing the mismatches described above, the present paper suggests three key pillars for constructing the future governance systems, including:

1.     Institutionalizing Strategic Foresight

2.     Evidence-based Agility and the Science-Policy Interface

3.     Human-Centric AI Governance

3.1 Institutionalizing Strategic Foresight

The first pillar of the new governance operating system is the institutionalization of Strategic Foresight and Risk Analysis. This moves beyond ad-hoc planning to embed anticipation and long-term thinking into the core functions of government, specifically budgeting and legislation.

Resolving the Speed Mismatch through Anticipation

Anticipatory governance is not about predicting a single future but about building the capacity to navigate multiple, non-linear plausible futures. By mapping black swan (rare, high-impact) and gray rhino (obvious, high-probability) events, such as infrastructure breakdowns, AI misalignment, or sudden demographic shifts, governments can stress-test their development strategies against extreme scenarios. This creates a predictable environment for long-term capital, as investors recognize that the state has already accounted for potential disruptions in its fiscal and regulatory planning (BCAM, 2025).

As an example, the Finnish model can be considered as an early step towards this institutionalization. As a standing permanent committee, the Committee for the Future of the Finnish Parliament acts as a guard against short-sightedness (EPTA, 2013). Unlike standard committees, it does not focus on specific legislation but on broad trends and systemic shifts, such as the future of work, sustainable growth, and the endurance of the welfare society. Its "power of vision" allows it to produce reports that the government is legally required to respond to, ensuring that long-term insights are integrated into the executive branch's policy agenda.

The Role of Foresight in Economic Resilience

Sustained GDP growth in the global majority requires more than just capital. It also requires visionary power that bridges the gap between scientific research and political action. In Spain, the National Office of Foresight and Strategy connects long-term trends directly to the "España 2050" strategy, which aims to close the productivity and per-capita income gap with the most advanced EU economies (National Office of Foresight and Strategy, 2025). By setting 50 quantitative targets and 200 policy actions, Spain uses foresight as a structural reform tool to modernize its productive fabric and business culture (STIP Compass, 2025).

The UAE Vision 2031 is a 10-year strategic plan (spanning 2021–2031) aimed at economic diversification and establishing global leadership. A central component of this initiative is the Future Foresight Strategy, which involves building future models for critical sectors such as health, education, and the environment to harmonize government policies. The UAE utilizes a specific technological mechanism to drive this vision, which includes the following initiatives:

• AI-enabled Strategic Intelligence Hub: The state has adopted the World Economic Forum’s Strategic Intelligence Platform to align national resources with future global trends.
• Predictive Governance: The Ministry of Cabinet Affairs uses these foresight units to move the public sector from a reactive bottleneck to a proactive driver of prosperity.

India@2047 is a long-term strategic roadmap (2022–2047) focused on achieving high growth and navigating a "triple transition". This 25-year plan is designed to transform India's development agenda and modernize its institutional frameworks. Key initiatives of the program include the NITI Aayog Policy Dynamo, which acts as the central "policy dynamo," driving strategies such as "Strategy for New India @ 75" to align administrative capacity with economic goals. In addition, the “Strategic Growth” initiative focuses on scaling the economy while ensuring that technological advancement translates into sustainable human well-being (PMINDIA, 2022).

Among the multiple governmental intiatives in Russia, Gostech, the Unified State Cloud Platform, can be considered an example. Gostech is the technological "backbone" of Russia’s digital transformation, designed to consolidate all government information systems into a single, secure cloud infrastructure. Before the Gostech initiative, different ministries operated on isolated platforms with fragmented data. Following its initiation, Gostech provides a unified data layer that allows for "systemic scope," where services from different departments (e.g., taxes, healthcare, and social security) are integrated. Gostech allows for the rapid development of digital services using low-code tools, meaning the state can respond to new societal needs at a much higher speed than traditional bureaucratic cycles allowed (GOVTECH, 2025).

3.2 Evidence-based Agility and the Science-Policy Interface

The second pillar focuses on resolving the scope mismatch by anchoring policy in a strengthened science-policy interface. In an era where misinformation and polycrisis complexity can paralyze decision-making, governance must be reality-based and multidisciplinary. The success of the second pillar is dependent on the integration of the multidisciplinary research into decision-making and data-driven proactiveness as a driver of growth.

Integrating Multidisciplinary Research into Decision-Making

Evidence-based agility requires new institutional models like "Foresight–Science Joint Units" (National Centre, 2025). These units transform science from an optional, ad-hoc input into a structural pillar of governance. This involves integrating expertise from AI, behavioral science, economics, and environmental studies directly into the core drafting of legislation and budgets. This approach ensures that growth strategies are resilient to the cascading effects of systemic challenges.

In Brazil, the Center of Management and Strategic Studies (CGEE) has illustrated the evolution of this model. CGEE is shifting its focus from simple "optimization" of existing systems to a "contingency" approach that embraces uncertainty and complexity (Cagnin, 2014). By acting as a bridge between the state and the scientific community, CGEE uses future-oriented debates to trigger imagination and expand the collective understanding of the present, reorienting the National Innovation System to address common societal challenges.

Data-Driven Proactiveness as a Driver of Growth

The OECD Digital Government Policy Framework identifies "proactiveness" as one of its six critical dimensions (OECD Digital Government Index, 2025). A proactive government uses predictive analytics and shared data platforms to anticipate citizen needs before they are explicitly requested. For example, Kazakhstan has moved from a reactive "e-government" model to a proactive state where citizens receive benefits and services automatically via mobile platforms based on data triggers (UN DESA, 2025). This level of administrative efficiency significantly reduces the friction of economic activity, allowing for a more responsive and inclusive growth model.

The transition to a data-driven public sector is not merely about service delivery; it is about accountability. Blockchain technology and open data portals, as explored in various Global Majority contexts, allow for real-time monitoring of natural resource management and public procurement, reducing the corruption risks that often deter foreign direct investment (FDI) in emerging markets.

3.3 Human-Centric AI Governance

As a general-purpose technology (GPT), AI has the potential to fundamentally reshape global productivity, but it also introduces existential risks that require a new model of oversight.

The Polycentric Governance Model

Given the "AI Dilemma" – where governments must simultaneously exploit AI for efficiency (e.g., smart cities, personalized education) and protect citizens from algorithmic bias or rights erosion – a "Polycentric Governance" model is essential. Polycentric governance involves multiple, overlapping centers of authority that coordinate through flexible networks of state and non-state actors, including the private sector, academia, and civil society (PRISM, 2025).

This model is particularly effective for AI because it avoids the rigidity of top-down global treaties while preventing a fragmented regulation. By involving multiple stakeholders in the co-creation of ethical frameworks, governments can ensure that AI serves human needs while maintaining the agility needed to keep pace with innovation.

Algorithmic Impact Assessments (AIA) and Public Trust

A critical tool for operationalizing the human-centric AI governance is the Algorithmic Impact Assessment (AIA). The Canadian AIA model, which supports the Treasury Board's Directive on Automated Decision-Making, provides a mandatory risk assessment framework for all automated systems in the public sector. The AIA determines an impact level (I through IV) based on 65 risk questions and 41 mitigation questions, covering areas such as rights, health, well-being, and economic interests (Canada, 2025). Table 2 illustrates the Canadian Algorithmic Impact Assessment Model.

Table 2: Canadian Algorithmic Impact Assessment Model

Source: Treasury Board of Canada AIA Framework (Canada, 2025)

The publication of these assessments on Open Government Portals is a key driver of public trust. When citizens understand how, why, and when algorithms are making decisions that affect them, they are more likely to engage with digital government services, further driving efficiency and growth.

4. Specific Implementation Proposals for the Global Majority

To operationalize the "Future-Oriented Governance Ecosystem" across diverse national contexts, from Least Developed Countries (LDCs) to OECD and BRICS nations, the present study proposes three scalable measures:

1.     Establishing Strategic Foresight as a governmental core function

2.     Deploying algorithmic impact assessment task forces

3.     Creating a future-oriented public administration maturity model   

4.1 Establishing ‘Strategic Foresight Units (SFU)’ at the Center of Government

Following the success of countries like Finland and Spain, all nations should establish Strategic Foresight Units within an appropriate government structure, such as at the Prime Minister’s or President’s office. These units should not be large bureaucracies but ‘lean’ hubs that connect long-term trends directly to national planning and budgeting. In the UAE, the Ministry of Cabinet Affairs has launched the Future Foresight Strategy, which involves building future models for health, education, and the environment to harmonize government policies (UAE, 2025b). This is not a ‘luxury’ for wealthy nations; for the Global South, a Foresight unit is a low-cost, high-impact institutional change that allows for better alignment of limited resources with future realities.

4.2 Deploying ‘Algorithmic Impact Assessment’ Task Forces

To safely integrate AI into the global economy, governments should adopt the Canadian and Kazakhstani models of institutionalized AI oversight. Kazakhstan’s creation of a Ministry of Artificial Intelligence and Digital Development illustrates how a centralized body can coordinate ethical guidelines, supercomputer infrastructure, and "icebreaker projects" across 10 key areas including healthcare, cybersecurity, and robotics (Interfax, 2025). Task forces within these ministries can perform Algorithmic Impact Assessments to ensure that the platform economy remains trusted and inclusive, protecting citizens from behavioral manipulation and illegal data collection.

4.3 Creating a ‘Future-Oriented Public Administration Maturity Model’

A universal playbook should be developed through international cooperation (e.g., BRICS Think Tanks Council or UN platforms) to allow nations to self-assess their readiness in foresight, systems thinking, and AI governance (National Centre, 2025) This maturity model would offer adaptable pathways for different institutional stages, ensuring that "future-readiness" is accessible to all. Table 3 shows the four stages of the public administration stages.

Table 3: Public Administration Maturity Stages

Source: Derived from OECD and UN maturity indicators

The evolution of public administration maturity follows a trajectory from rigid, reactive legacy systems to integrated, future-oriented ecosystems. In Stage 1 (Fragmented), the state remains an analog entity defined by linear policy cycles, departmental silos, and reactive, ex-post crisis management. Transitioning to Stage 2 (Digital), the focus shifts toward transactional efficiency and online service delivery; however, while platforms are digitized, the governance logic remains anchored in historical benchmarks and descriptive statistics. Stage 3 (Proactive) marks a critical shift toward predictive, user-centric governance, utilizing integrated data and predictive analytics to automate service delivery and anticipate citizen needs before they are explicitly requested. Finally, Stage 4 (Anticipatory) represents a fully systemic and resilient state where departmental silos are replaced by cross-cutting task forces, and Strategic Foresight is embedded into all policy and budget cycles to navigate multiple plausible futures.

5. The Economic Rationale: The Stability Dividend

The shift toward anticipatory governance is not merely an administrative improvement; it is an economic imperative. By reducing the volatility of the policy environment, governments can unlock a stability dividend that manifests through several channels, like lowering the sovereign risk premium, enhancing productivity through long-term planning, and harmonizing the global platform economy.

5.1 Lowering the Sovereign Risk Premium

The risk premium associated with sovereign debt is heavily influenced by the market's perception of a government's effectiveness. Research into the bond markets of emerging economies confirms that credible monetary and fiscal policies, transparent governance, and political stability translate into narrower spreads and steadier credit ratings. When a state demonstrates that it has institutionalized Foresight to mitigate future risks (e.g., climate disasters or energy transitions), it provides a safe store of value for investors, reducing the precautionary saving motive and encouraging productive investment.

Economic evidence indicates that better-governed firms in emerging markets can achieve valuation premiums ranging from 20% to 27%. At the national level, the IMF has noted that improved policy frameworks have contributed approximately 0.5% to EM growth and reduced inflation by 0.6% compared to pre-2008 levels (BCAM, 2025).

5.2 Enhancing Productivity through Long-Term Planning

The "Spain 2050" strategy highlights that countries like Finland, Sweden, and Germany increased their productivity by 50% over 30 years through similar strategic shifts. If Spain matches this achievement through its 2050 plan, it could sustain an average annual GDP growth of 1.5%, even in the face of demographic aging (Futuros, 2025). In Kazakhstan, the "Generative Nation" strategy is projected to grow the economy by 30% through digitalization and AI-driven efficiency (Soysal, 2025).

The economic returns on anticipatory investment are particularly stark in the green transition. Every Euro spent toward a "Net Zero" pathway by 2050 is expected to yield 1.64 Euros in Italy and 1.28 Euros in Spain. Furthermore, cumulative savings from improved health and recovered productivity due to reduced polluting emissions could reach 614 billion Euros in Italy and 317 billion Euros in Spain (Enel, 2022).

5.3 Harmonizing the Global Platform Economy

By adopting shared standards for AI governance and digital connectivity, the Global Majority can unlock cross-border digital trade. Kazakhstan’s goal to increase IT service exports to $1 billion and create five "unicorns" (startups valued over $1 billion) is predicated on its status as a trusted, digitally sovereign state.⁶⁰ Harmonization through polycentric networks allows for the free flow of data and services while ensuring that local values and cultural identities are integrated into technological deployment (Liasko, 2025).

6. Navigating the Challenges of Implementation

Transitioning to an anticipatory governance system is not without friction. Governments must overcome significant internal and external barriers. Overcoming short-termism and risk aversion is one of them. Political cycles typically incentivize short-term thinking. Politicians are often inclined to focus on immediate problems that will resolve before the next election, neglecting the broader trends that will define the country’s future. To counter this, foresight must be "constitutionally protected" or institutionalized in a way that spans multiple parliaments, as seen in the Finnish model.

The capacity gap is another challenge to be overcome. Scarcity of specialized skills in public administration is a major bottleneck. Building anticipatory capacity requires investment in futures literate senior leaders and policymakers. While AI can augment Foresight by scanning large datasets for signals of change, it remains limited by concerns over quality, bias, and a lack of inductive reasoning. Therefore, human expertise remains the core of the system.

Finally, it is crucial to avoid the global fragmentation. The global quantum community and AI landscape remain fragmented. Nearly 60% of researchers are not part of international collaborations, restricting knowledge exchange. There is a risk that clamors of AI sovereignty could lead to a fragmented digital world, where different regional standards prevent a unified platform for growth. Multilateral platforms like the BRICS Open Dialogue or UN-led initiatives are critical to ensuring that the benefits of emerging technologies are shared inclusively and that the "quantum divide" does not leave the Global South behind.

7. Conclusion: A New Social Contract for Global Growth

The transformation from an "Analog State" to an "Anticipatory Governance" ecosystem represents the single most important investment for the Global Majority in the 21^st century. This shift moves the public sector from a reactive bottleneck to a proactive driver of prosperity. By institutionalizing Strategic Foresight, anchoring policy in multidisciplined evidence, and governing AI through inclusive, polycentric networks, we can create a state that is agile, trustworthy, and human enough to sustain global growth.

Ultimately, the "New Platform for Global Growth" is not just about the technologies developed, but the government that wields them. A future-oriented state provides the "stability dividend" required for long-term investment and the social safeguards required for human well-being. As the center of gravity shifts toward the Global South and East, the nations that successfully reboot their administrative operating systems will be the ones to lead the next era of global development. This is the path beyond the analog state – a path toward a more resilient, inclusive, and sustainable future for all.

References

1.     BCAM (2025). From Fragility to Resilience: How Policy and Governance are Redefining Emerging Markets, Boston Common Asset Management, https://bostoncommonasset.com/how-policy-and-governance-are-redefining-emerging-markets/ (accessed December 25, 2025).

2.     Cagnin, C. (2014). STI Foresight in Brazil, Foresight and STI Governance, vol. 8, issue 2, pp. 44-56 DOI:10.17323/1995-459X.2014.2.44.56 (accessed December 25, 2025).

3.     Canada (2025). Algorithmic Impact Assessment tool, Canada.ca, https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/algorithmic-impact-assessment.html (accessed December 25, 2025).

4.     Enel (2022). Net Zero E-conomy 2050: Decarbonization roadmaps for Europe – focus on Italy and Spain, Enel Group, https://www.enel.com/content/dam/enel-com/documenti/azienda/storie/net-zero-e-conomy-2050.pdf (accessed December 25, 2025).

5.     EPTA (2013). Finland – The Committee of the Future, Comparative Table of Parliamentary TA Institutions, European Parliamentary Technology Assessment, https://eptanetwork.org/static-html/comparative-table/countryreport/finland.html (accessed December 25, 2025).

6.     Futuros (2025). BEING MORE PRODUCTIVE TO GROW BETTER, National Office of Foresight and Strategy, Spain https://futuros.gob.es/sites/default/files/esp2050/pdf/en/Spain_2050_1.pdf (accessed December 25, 2025).

7.     GOVTECH (2025). Development of Government Information Systems Using “GovTech” Platform https://platform.gov.ru/en/documents/development-of-government-information-systems-using-the-govtech-platform/  (accessed December 25, 2025).

8.     Interfax (2024). Kazakh govt adopts AI Development Concept until 2029, https://interfax.com/newsroom/top-stories/104292/ (accessed December 25, 2025).

9.     Liasko, E. (2025). Key IT Trends in Kazakhstan 2025, interview with Mr. Roman Yashin, Global CIO, https://globalcio.com/longread/Digital-Strategies-of-Kazakhstan/ (accessed December 25, 2025).

10. National Centre (2025). Open Dialogue: Brief for participants, National Centre Russia, https://tokyo.mid.ru/upload/iblock/1c9/y18wdi55l2ynl44tzsqizyfwk0o4encs.pdf (accessed December 25, 2025).

11. National Office of Foresight and Strategy (2025). National Office of Foresight and Strategy of the Government of Spain - Oficina Nacional de Prospectiva y Estrategia, https://futuros.gob.es/en (accessed December 25, 2025).

12. OECD (2022). Anticipatory Innovation Governance Model in Finland: Towards a new way of governing, Reform Support, https://reform-support.ec.europa.eu/system/files/2022-11/Anticipatory%20Innovation%20Governance%20Model%20in%20Finland.pdf (accessed December 25, 2025).

13. OECD Digital Government Index (2025). https://goingdigital.oecd.org/en/indicator/58 (accessed December 25, 2025).

14. PMINDIA (2022). NITI Aayog: Transforming India’s Development Agenda, https://www.pmindia.gov.in/en/major_initiatives/niti-aayog-transforming-indias-development-agenda/ (accessed December 25, 2025).

15. PRISM (2025). Polycentric Governance Models, Sustainability Directory, https://prism.sustainability-directory.com/term/polycentric-governance-models/ (accessed December 25, 2025).

16. Soysal, D. (2025). Digital Bridge 2025 Astana: Kazakhstan’s Leadership In The Digital Era, Euroasia Review, https://www.eurasiareview.com/11102025-digital-bridge-2025-astana-kazakhstans-leadership-in-the-digital-era-oped/ (accessed December 25, 2025).

17. UAE (2025). We-The-UAE-2031-Vision, https://u.ae/en/about-the-uae/strategies-initiatives-and-awards/strategies-plans-and-visions/innovation-and-future-shaping/we-the-uae-2031-vision (accessed December 25, 2025).

18. UAE (2025b). UEA Government Future Foresight Strategy, https://u.ae/fi/about-the-uae/strategies-initiatives-and-awards/strategies-plans-and-visions/innovation-and-future-shaping/future-foresight (accessed December 25, 2025).

19. UN DESA (2025). Kazakhstan's Digital Evolution: From eGov to AI Governance, UN Department of Social and Economic Affairs, https://publicadministration.desa.un.org/blog/kazakhstans-digital-evolution-egov-ai-governance (accessed December 25, 2025).

20. WEF (2025). What is anticipatory governance, and can it help us today? https://www.weforum.org/stories/2025/03/anticipatory-governance-for-a-risky-world/ (accessed December 25, 2025).