Adaptive Coherence as Institutional Design: A Framework for Governing Under Uncertaintyالتماسك التكيفي في تصميم المؤسسات: إطار لإدارة الحكم في ظل عدم اليقين

Abstract

This paper introduces the concept of adaptive coherence as a framework for institutional design under conditions of rapid change. Adaptive coherence holds that stable systems do not require fixed policy outputs. They require durable meta-principles, legitimate procedures, and intelligible mechanisms for revision. The failure mode avoided by adaptive coherence is brittle rigidity: institutional forms that persist by suppressing adaptation, accumulating the gap between structure and function quietly until rupture becomes inevitable. The paper positions this framework in relation to established institutional theory, particularly Pierson’s account of path dependence, Mahoney and Thelen’s typology of gradual institutional change, and North’s foundational distinction between formal rules and informal constraints, arguing that adaptive coherence offers a prescriptive architecture that complements these largely descriptive accounts. The Gulf development transition, specifically Saudi Arabia’s Vision 2030, is used as an empirical case: a large-scale institutional project explicitly committed to adaptive revision of policy instruments while maintaining durable higher-order goals. Artificial intelligence governance is then developed as the most demanding contemporary test of the framework. The paper concludes that adaptive coherence offers a more defensible standard for evaluating institutional performance than either stability, which confuses continuity of form with functional adequacy, or flexibility, which confuses revision with coherence.

I. Introduction

What does it mean for an institution to be well designed? Two answers dominate both academic and policy discourse. The first emphasizes stability: well designed institutions are predictable, rule-bound, and resistant to capture. The second emphasizes flexibility: well designed institutions can adapt to changing conditions, learn from error, and revise their instruments as circumstances evolve. Both answers, in their pure forms, are inadequate. A purely stable institution becomes brittle; its form persists while its function quietly decays. A purely flexible institution becomes arbitrary; its revisions reflect the power of whoever can access the revision process rather than any principled standard.

This paper proposes a third answer: adaptive coherence. An adaptively coherent institution maintains continuity at the level of meta-principles, procedures, and accountability structures while allowing lower-level policy instruments to remain revisable. Coherence is preserved, but it is located at the right level of the system: not in specific outputs, which must change as conditions change, but in the standards, processes, and criteria that govern how outputs are chosen, revised, and replaced.

The distinction has practical stakes. Governance frameworks for rapidly changing environments, including AI regulation, development finance, climate policy, and the institutional transitions underway in the Gulf, routinely face the charge that they must choose between stability and adaptability. This paper argues that the charge presents a false choice that disappears when coherence is correctly located.

The paper proceeds as follows. Section II reviews the relevant institutional theory literature. Section III develops the core framework: the distinction between brittle rigidity and adaptive coherence, the concept of false stability, and the specification of what must remain stable versus what can remain revisable. Section IV addresses the capture problem, the most serious objection to adaptive institutional design. Section V develops the Gulf development transition as an empirical case study. Section VI applies the framework to artificial intelligence governance as the most demanding contemporary test. Section VII concludes with implications for institutional design evaluation.

II. Literature Review: Stability, Change, and the Gap Between Them

Path dependence and the limits of stability-centered theory

Paul Pierson’s work on path dependence in political institutions provides the most influential account of why institutions are resistant to change.[1] Pierson identifies three mechanisms of institutional lock-in: increasing returns (institutions become more valuable as they spread, making alternatives less attractive), adaptive expectations (actors make commitments premised on institutional continuation, raising the cost of exit), and the political mobilization of beneficiaries (those who benefit from existing arrangements resist change more effectively than potential beneficiaries of alternatives can mobilize for it).

Path dependence explains why institutions persist long after their functional adequacy has declined. It is, however, primarily a descriptive account. It tells us why institutions are sticky, not which forms of institutional continuity are desirable and which represent pathological lock-in. Adaptive coherence addresses this prescriptive gap directly: path dependence at the level of meta-principles and procedures is desirable and should be actively maintained; path dependence at the level of specific policy instruments is dangerous and should be structurally resisted through sunset clauses, review intervals, and explicit revision mechanisms.

Gradual institutional change and the varieties of revision

Mahoney and Thelen’s typology of gradual institutional change identifies four modes through which institutions transform without appearing to: conversion (old institutions acquire new functions), layering (new elements are attached to old structures, gradually changing the overall character), displacement (new institutions rise while old ones decline), and drift (institutions fail to adapt to changing environments and their functions gradually erode).[2]

This typology is analytically powerful but again primarily descriptive. Mahoney and Thelen explain how change happens in institutions that are formally unchanged. They do not prescribe how institutions should be designed to manage change intentionally. Adaptive coherence differs from all four of their modes: it describes a proactive institutional architecture for managing revision under principled constraints, rather than the unplanned transformations their typology documents.

The most relevant mode for the adaptive coherence framework is drift, the failure that results when institutions do not adapt to changing environments. Drift is what adaptive coherence is designed to prevent. But the solution adaptive coherence proposes is not simply “change instruments more often.” It is “build the meta-level infrastructure that makes principled instrument revision possible, visible, and legitimate.” Without that infrastructure, the alternative to drift is not adaptive coherence; it is conversion or capture.

North on formal rules and informal constraints

Douglass North’s foundational distinction between formal rules (laws, regulations, constitutions) and informal constraints (conventions, norms, self-imposed codes of conduct) is essential background for the adaptive coherence framework.[3] North argued that informal constraints often outlast formal rule changes, and that the mismatch between changing formal rules and persisting informal constraints explains many institutional failures. That argument maps directly onto the adaptive coherence problem.

The meta-principles and procedures that adaptive coherence designates as the stable layer of institutions are not purely formal rules in North’s sense. They include the informal norms, conventions, and behavioral expectations that give formal procedures their authority. An institution can have technically sound revision mechanisms that fail in practice because the informal culture of the organization treats revision as a threat rather than a tool. Adaptive coherence must therefore be understood as a property of both formal structure and informal culture, a point returned to in the Gulf case study.

Streeck on institutional tensions under capitalism

Wolfgang Streeck’s analysis of how capitalist institutions evolve under competitive pressure adds a political economy dimension.[4] Streeck argues that institutions designed to balance efficiency and distributional concerns are systematically eroded by competitive pressures that favor efficiency over distribution, and that this erosion is not random but directional. Institutions that serve distributional purposes face a constant headwind.

This has direct implications for adaptive coherence. An institution designed to maintain adaptive coherence, especially in a domain where incumbent interests benefit from institutional rigidity, will face systematic pressure to abandon its revision mechanisms precisely when those mechanisms would threaten existing arrangements. The design of adaptive institutions must account for the political economy of their own maintenance: the meta-principles and procedures that constitute the stable layer must be protected not just structurally but politically, through the kinds of public visibility, accountability chains, and interest-group architecture that make their erosion visible and costly.

III. The Adaptive Coherence Framework

The core distinction

The fundamental move in the adaptive coherence framework is locating coherence correctly within a system.

Brittle rigidity places coherence at the output level. Specific policies, regulations, and institutional structures are treated as the embodiment of the system’s commitments. Stability is equated with continuity of particular instruments. The failure mode follows: mismatch accumulates between institutional form and real-world conditions, visible initially as declining functional performance, eventually resolving in rupture. The brittleness is not immediately visible because the form persists. This is path dependence, in Pierson’s sense, working against necessary adaptation.

Adaptive coherence places coherence at the meta-principle and procedural level. The criteria for policy selection and evaluation, the procedures for evidence assessment and deliberation, the standards for revision, review, and exit, and the accountability chains that outlast individual administrations remain stable. Specific instruments remain revisable. The failure risk is much lower, because the system can revise instruments before mismatch becomes catastrophic. Revision is not a sign of weakness but the normal operation of a healthy adaptive system.

Where coherence lives, at the level of outputs or at the level of meta-principles, determines whether an institution can sustain legitimacy through change or loses legitimacy with each revision. An institution whose structured flexibility is visible and procedurally principled can revise without losing authority. An institution that equates continuity with legitimacy loses both when revision becomes unavoidable.

What must be stable

What does the stable layer actually need to contain? Start with criteria for policy selection and evaluation: what counts as evidence that an instrument is working, and what specifically triggers review. Paired with that, the procedures for evidence assessment and deliberation: who participates, how disagreements get resolved, what standards govern the process. Then the standards for revision, review, and exit: explicit intervals, sunset clauses, criteria for retiring instruments that have stopped working. Two elements are hardest to build but most load-bearing. The first is accountability chains that outlast individual administrations, so that long-term commitments cannot simply be abandoned when leadership changes. The second is transparency requirements that make adaptation legible to the public, so that revision reads as principled rather than arbitrary. Without institutional memory mechanisms, revision becomes amnesia, and each generation of policymakers starts from scratch.

What can remain revisable

Specific tax structures and rates; specific regulatory frameworks and thresholds; specific monetary and fiscal instruments; specific industrial policy tools and targets; specific labor and market governance structures. These are the instruments chosen by applying the stable meta-level framework to specific contextual conditions. When conditions change, when the empirical evidence shifts, when the economy’s structure transforms, when external shocks alter the relevant constraints, these instruments should change. The stable layer is what ensures that the change is principled rather than arbitrary.

False stability

Many systems exhibiting surface continuity are not actually stable. They display what this paper calls false stability: institutional forms persisting while their function quietly decays.

False stability arises because institutional inertia, political incentives, and narrative management all favor the appearance of continuity. Elites invested in existing arrangements resist revision. Publics habituated to familiar policies prefer the familiar even when it no longer performs. Institutional actors protect the frameworks that justify their existence. The result is that the gap between institutional form and actual function widens quietly. When that gap becomes materially visible, through a crisis, a shock, or a sufficiently egregious performance failure, adjustment is no longer gradual. It is rupture.

What could have been managed as continuous adaptation becomes a crisis because false stability prevented the earlier, cheaper revisions. The classic examples include the collapse of the Bretton Woods system, which persisted in nominally fixed exchange rates after the conditions that made them workable had dissolved; the 2008 financial crisis, where regulatory frameworks maintained the form of oversight while financial innovation had rendered the substance obsolete; and the various fiscal crises of over-borrowed states, where deficit rules were maintained formally while being systematically circumvented informally.

False stability is not the same as genuine continuity. A system can persist without being legitimate. Persistence through inertia is not adaptive coherence; it is deferred brittleness. The distinction between adaptive coherence and false stability is empirically testable: does the system have functioning revision mechanisms that are actually used, or does it have revision mechanisms that are structurally blocked by the interests that benefit from inertia?

IV. The Capture Problem

The most serious objection to adaptive institutional design is the capture problem: if institutions can revise their instruments, powerful actors will capture the revision process and use it to serve their own interests rather than the institution’s stated purposes. Flexibility without sufficient constraints is not adaptive coherence. It is elite improvisation.

This objection is legitimate and must be addressed directly rather than dismissed. It is, in fact, the objection that motivated this paper’s argument. The contextual toolbox approach to economic policy, on which adaptive coherence builds, faces exactly this critique: if different tools fit different contexts, what prevents the selection of tools from becoming a post-hoc rationalization for serving incumbent interests?[5]

Adaptive coherence’s answer is architectural. The stable layer, the meta-principles and procedures, is precisely what distinguishes principled adaptation from capture. But the stable layer must itself be designed to resist capture, which requires four things.

First, public visibility of the revision process. Revisions made in public, with reasons stated, documented, and subject to challenge, are much harder to capture than revisions made administratively without notice. Transparency is not merely a democratic value; it is the structural mechanism that makes capture expensive.

Second, multi-stakeholder deliberation. Revision processes that include voices beyond the immediate implementing agency and the regulated parties are more resistant to capture than bilateral negotiations between regulator and regulated. The role of academic economists, civil society organizations, international institutions, and other actors with stakes in institutional performance but no direct benefit from specific outcomes matters structurally, not just symbolically.

Third, accountability chains that outlast individual administrations. Capture works by aligning the interests of the current administration with the interests of the capturing party. Long-term accountability chains, including parliamentary oversight, judicial review, international monitoring, and historical audit, break this alignment by making current administrations accountable to standards they did not set and successors they cannot control.

Fourth, explicit criteria for revision. When the criteria for determining that an instrument needs revision are public, specific, and agreed upon in advance, the bar for demonstrating that a revision serves the criteria rather than private interests is clearly set. Revisions that cannot meet the stated criteria face a public accountability burden.

These are demanding requirements. They cannot be met by institutional design alone; they require the political will to build them and the ongoing political support to maintain them. But the capture objection does not defeat adaptive coherence. It specifies the conditions under which adaptive coherence is possible.

V. The Gulf Case: Vision 2030 as Adaptive Coherence at Scale

Saudi Arabia’s Vision 2030 program, launched in 2016 and substantially underway by the mid-2020s, provides a live, large-scale test of adaptive coherence in practice. It is worth examining closely because it is structurally better suited to the adaptive coherence framework than most OECD-context examples, and because the ways in which it falls short of adaptive coherence identify exactly where the framework’s requirements are most demanding.

Vision 2030 is explicitly designed around the distinction adaptive coherence proposes. Its higher-order commitments, including economic diversification away from hydrocarbon dependence, expanded private-sector employment, social modernization, and the development of a non-oil export economy, are treated as durable goals that persist across administrations and planning cycles. Its specific instruments, including labor nationalization ratios (Saudization targets), entertainment and tourism liberalization timelines, and sector-specific industrial targets in mining, tourism, logistics, and renewables, are explicitly treated as revisable based on performance data. When Saudization targets proved counterproductive in specific sectors, they were revised. When the giga-project portfolio was reprioritized, projects were scaled or paused without the overall development framework being destabilized.

This is adaptive coherence in practice: durable meta-level commitment to diversification and modernization, with instrument-level revision as a normal feature rather than a crisis response. The stakes are larger than policy performance. Vision 2030 is a test of whether a legitimacy transition, from resource-rent legitimacy to performance-and-diversification legitimacy, can be managed through adaptive institutional design rather than rupture.

Where Vision 2030 tests the capture objection most severely is in the transparency and multi-stakeholder requirements. The revision process for Vision 2030 instruments is largely internal to the state and its implementing agencies, with limited public visibility and weak mechanisms for challenge from outside the government. This creates exactly the capture risk the framework identifies: the flexibility of instruments becomes available for elite capture rather than principled adaptation. The Public Investment Fund’s portfolio choices, the giga-project budget allocations, and the sequencing of economic liberalization have all been revised in ways that are functionally justifiable but not publicly accountable in the way the adaptive coherence framework requires.

This is a useful case precisely because it shows adaptive coherence operating in the presence of its characteristic failure mode. The meta-level commitments are durable. The instruments are revisable. But the revision process lacks the public accountability mechanisms that distinguish principled revision from elite improvisation. The prescription is clear: build the transparency, deliberation, and accountability infrastructure that would convert Vision 2030 from a high-functioning adaptive system at risk of capture into a genuinely adaptive, coherent institutional architecture.

VI. AI Governance as Test Case for Adaptive Coherence

The most demanding contemporary test of the adaptive coherence framework is artificial intelligence governance. The technology evolves on a timescale measured in months. The institutions designed to govern it, including domestic regulatory agencies, international standards bodies, professional self-regulation, and intellectual property law, were designed for technologies whose capability frontier moved on a timescale measured in years or decades. The mismatch is structural, and it produces precisely the failure mode this paper has been describing: institutional forms that look stable while the gap between their assumptions and the underlying reality widens beyond the point where gradual revision can close it.

The dominant policy responses to AI fall into two categories that the adaptive coherence framework allows us to diagnose more precisely. The first is comprehensive ex ante regulation, of which the EU AI Act is the leading example: an attempt to specify in advance the categories of AI systems, the risks attached to each category, and the mandatory compliance procedures.[7] The second is light-touch sectoral regulation, which delegates AI governance to existing sector-specific authorities (the FDA for medical AI, the SEC for financial AI, the FAA for autonomous vehicles) and allows the underlying technology to evolve without dedicated horizontal oversight. Both approaches share a structural flaw the framework makes visible.

The comprehensive ex ante approach locates coherence at the output level. It specifies the rules, the categories, the prohibited uses, and the compliance regimes as fixed outputs. This approach inherits the brittle-rigidity failure mode in concentrated form. The categories defined when the legislation was drafted will not match the systems that emerge two years after enactment. The risk classifications anchored to specific architectural features (parameter counts, training compute, modality combinations) will not track the risks of systems built on architectures the legislators could not anticipate. By the time the formal revision process produces an updated framework, the technology has moved again, and the cycle of mismatch repeats. The form of coherence, a comprehensive rulebook, is preserved while the function, actually governing the systems that exist, decays.

The light-touch sectoral approach locates no coherence at all. It accepts the absence of horizontal governance and assumes that sector-specific authorities will adapt their existing frameworks to AI applications within their domains. This may work for narrow applications that map cleanly onto existing sectoral categories. It systematically fails for general-purpose systems that operate across sectors, for emergent capabilities that did not exist when sectoral mandates were defined, and for harms that are distributed across sectors in ways no single regulator has authority to address. The failure mode here is not brittle rigidity. It is regulatory dispersion: the absence of a coherence anchor at any level above the sector.

The adaptive coherence framework specifies what a third approach would require. The stable layer of AI governance should consist not of fixed rules about specific systems but of meta-principles, procedures, and accountability structures that remain stable while the specific instruments adapt to the technology as it actually evolves.

What belongs in the stable layer: risk assessment criteria that are technology-agnostic and capability-anchored, focused on what kinds of harm are being measured and what threshold of evidence triggers regulatory engagement, rather than rules attached to specific architectural features that will not survive the next generation of systems. Evidence assessment procedures need to include independent technical audit capacity, with results made public and contestable; the audit function should be institutionally independent of both the developing companies and the regulatory agencies whose jurisdictions the findings would expand or contract. Standards for revision should specify both intervals (an annual horizontal review of major risk categories) and triggers (a documented capability shift in deployed systems above a pre-specified threshold initiates review automatically, regardless of calendar timing). Accountability chains must bind future administrations and successor agencies; the meta-layer’s stability cannot depend on the political continuity of whoever built it. And transparency requirements need to be sufficient to make capture visible. Industry capture of AI governance is the single most predictable failure mode of any framework that gives regulated parties significant input into rule design. The historical pattern from telecommunications, financial regulation, and pharmaceutical safety suggests that capture is the default outcome of regulatory architectures that lack public visibility into industry-regulator deliberation.

What remains revisable: the specific compliance requirements attached to specific capability thresholds; the categorical taxonomies used to organize system types for different oversight regimes; the specific instruments applied to specific risk profiles (pre-market approval, post-market surveillance, audit requirements, deployment restrictions); and the cooperation arrangements with international counterparts, which will need to evolve as other jurisdictions develop their own frameworks.

The capture problem applies here with unusual force. AI capability is concentrated in a small number of large firms whose technical expertise exceeds that of any plausible regulator. Regulatory frameworks built on industry consultation are at high risk of becoming framework expressions of industry preferences. The architectural answer the previous section developed, public visibility, multi-stakeholder deliberation, accountability chains, and explicit criteria, applies directly. AI governance at risk of capture is not adaptive coherence. It is industry self-regulation in regulatory clothing.

The Acemoglu and Robinson distinction between extractive and inclusive institutions is structurally relevant here.[6] Inclusive institutions distribute political and economic rights broadly, allow the many to participate in shaping the rules under which they live, and resist the concentration of power that allows a small group to extract rents from the rest. Extractive institutions concentrate authority and rents in narrow elites who shape the rules to preserve their position. The adaptive coherence framework is not a substitute for the inclusive/extractive distinction; it operates at a different level of analysis, specifying the architectural features of well-designed institutional change management rather than the political-economic distribution of power. But the two arguments are complementary. An institution can be inclusive in formal authority while exhibiting brittle rigidity in its operation; an institution can have functional revision mechanisms while remaining extractive in whose interests those mechanisms serve. The full institutional design problem requires both: inclusive distribution of authority and adaptive coherence in the architecture through which that authority operates. AI governance is the contemporary case where both requirements are simultaneously most demanding and least met.

The implication is not that AI governance is structurally impossible. It is that the existing approaches are not solving the right problem. A governance framework adequate to the challenge would build the meta-level architecture this paper has specified, durable principles, legitimate procedures, transparent revision mechanisms, and capture-resistant accountability, and accept that the specific instruments must remain revisable on a timescale matched to the technology rather than to the regulatory cycle. This is a harder design problem than either comprehensive ex ante rules or sectoral delegation. It is also the only design that can produce coherence at the level the technology actually requires.

VII. Conclusion

Where coherence lives in an institution, at the output level or at the meta-principle and procedural level, has large consequences for institutional performance under conditions of rapid change.

Institutions that locate coherence at the output level become brittle. They preserve the form of their commitments while their function decays, accumulate the mismatch between structure and reality until it is too large to manage gradually, and then face rupture rather than revision. Institutions that locate coherence at the meta-principle level can revise their instruments as conditions change, maintain functional adequacy, and build legitimacy through visible, principled adaptation rather than losing it when change becomes unavoidable.

The existing institutional theory literature, Pierson on path dependence, Mahoney and Thelen on gradual change, North on formal and informal constraints, Streeck on capitalist institutional evolution, provides powerful descriptive tools for understanding how institutions change and resist change. Adaptive coherence extends this toolkit prescriptively. It specifies the architectural features that distinguish well-designed institutional change management from either pathological rigidity or principled-sounding capture.

Three implications follow for institutional design evaluation.

First, assess coherence at the right level. When evaluating whether an institution is performing well, the first question should not be “are its specific outputs consistent?” but “does it have functional meta-principles, review mechanisms, and accountability structures?” An institution with consistent outputs but no functional review mechanism is exhibiting false stability. An institution with variable outputs but principled and visible revision processes may be exhibiting adaptive coherence.

Second, build the capture-resistance architecture first. Adaptive institutions are vulnerable to capture precisely because their flexibility is an asset powerful actors can exploit. Transparency, multi-stakeholder deliberation, and long-term accountability mechanisms that make revision visible and principled are not optional enhancements. They are load-bearing components of the architecture. Adaptive design without them is not adaptive coherence; it is institutionalized elite improvisation.

Third, apply the framework to governance under rapid technological change. AI regulation, climate policy, and development finance are all domains where the specific instruments that make sense today will not make sense in five years, and where the failure mode of brittle rigidity, frameworks designed for today’s technology or today’s climate data, is obvious. The adaptive coherence framework specifies what institutional architecture makes principled revision possible rather than merely reactive.

The hardest institutional design problem is not choosing the right policy instrument. It is building the meta-level architecture that makes the choice of instruments principled, revisable, and publicly defensible as conditions change. That is the problem adaptive coherence is designed to solve. Whether any political system can hold the meta-layer stable while everything beneath it moves is the question this framework raises without settling.

Sources

[1] Pierson, Paul. Politics in Time: History, Institutions, and Social Analysis. Princeton University Press, 2004; Pierson, Paul. “Increasing Returns, Path Dependence, and the Study of Politics.” American Political Science Review, vol. 94, no. 2, 2000, pp. 251-267.

[2] Mahoney, James, and Kathleen Thelen, eds. Explaining Institutional Change: Ambiguity, Agency, and Power. Cambridge University Press, 2010, ch. 1.

[3] North, Douglass C. Institutions, Institutional Change and Economic Performance. Cambridge University Press, 1990.

[4] Streeck, Wolfgang. Buying Time: The Delayed Crisis of Democratic Capitalism. Verso, 2014; Streeck, Wolfgang. “Taking Capitalism Seriously: Towards an Institutionalist Approach to Contemporary Political Economy.” Socio-Economic Review, vol. 9, no. 1, 2011, pp. 137-167.

[5] Rodrik, Dani. Economics Rules: The Rights and Wrongs of the Dismal Science. W.W. Norton, 2015. Rodrik’s argument for model pluralism covers adjacent terrain; adaptive coherence extends it by specifying the institutional architecture that makes pluralism governable rather than arbitrary.

[6] Acemoglu, Daron, and James A. Robinson. Why Nations Fail: The Origins of Power, Prosperity, and Poverty. Crown, 2012.

[7] Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence (“Artificial Intelligence Act”). For analysis of the AI Act’s structural commitments, see Schaake, Marietje. The Tech Coup: How to Save Democracy from Silicon Valley. Princeton University Press, 2024.