GRF · Innovation Nexus
Experimental governance
Experimental governance lets authorities test new rules, technologies or services under controlled conditions before deciding how to regulate them at scale. Regulatory sandboxes, innovation hubs, pilot regimes and testbeds trade defined flexibility or guidance for close supervision and shared learning. This page sets out how such experiments are designed, where they go wrong and how their evidence is evaluated. It makes no regulatory claims: only competent authorities run sandboxes and decide what follows from them.
Experimental governance in seven parts.
- 01The questionExperimental governance: how the risk develops
- 02IndicatorsWhat is measured, and how well
- 03SourcesWhere the evidence comes from
- 04DecisionsWho decides, and what the evidence serves
- 05Core questionsWhat experts ask
- 06MechanismsMechanisms and drivers
- 07Methods and dataHow it is studied, and where the methods stop
Experimental governance: how the risk develops.
Sandboxes and evaluation without regulatory claims. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Learning under supervision
A sandbox admits a limited number of participants under agreed safeguards, so the regulator observes real behaviour before writing rules. The value lies in what is learned and published, not in the admission.
Selection shapes results
Participants who apply are often better resourced and more compliant than the market as a whole. Results from a sandbox cohort may not hold when rules apply to everyone.
Advantage and capture
Admission can signal approval to investors and customers, and close contact can tilt a regulator toward participants. Transparent criteria, equal access and exit rules keep the experiment fair to competitors.
Pilots that never end
Temporary regimes can persist without evaluation, leaving firms and consumers in long uncertainty. An experiment needs an end date, a decision point and a published evaluation to become governance.
Regulatory sandbox board.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Regulatory sandbox board
Experimental governance · Regulatory sandbox · Cohort 3
Cohort
| Parametric micro-cover | Insurance | Agreed | 7 of 12 | Testing |
| Flood sensor data market | Data | Partial | 4 of 12 | Conditions |
| AI permit triage | Public service | Agreed | 6 of 12 | Testing |
| Drone deliveries, medical | Logistics | Agreed | 11 of 12 | Exit test |
Exit criteria
- Consumer harm
- none recorded
- Evidence
- independent evaluation
- Rule change
- regulator decides
- Wind-down
- plan on file
Sandbox cycle
- Applyeligibility
- Admitsafeguards
- Testbounded
- Evaluateindependent
- Exitor rule change
- Publishlessons
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Active regulatory sandboxes by sector | count of programmes | annual | Regulator registers and announcements | Published statistics |
| Sandbox applications and admissions | count per cohort | per cohort | Regulator cohort reports | Published statistics |
| Sandboxes with published entry, exit and evaluation criteria | percent of programmes | annual | Regulator programme documents | Published statistics |
| Time from sandbox exit to regulatory decision | months | per experiment | Regulator dockets | Published statistics |
| Published sandbox evaluations | count of evaluations | annual | Regulator and audit reports | Published statistics |
| Consumer complaints and incidents during testing | count per experiment | per experiment | Regulator supervision records | REPORTED |
| Cross-border and multi-regulator testing arrangements | count of arrangements | annual | Regulator network and memorandum records | Published statistics |
Compare instruments: rules, incentives and information.
Three families of instruments side by side against the baseline, each with its own lag and adoption speed, under the coverage and compliance you set; effect sizes are teaching values to replace with evidence. Scenario: named assumptions about the future, not a forecast.
Controls
- Baseline trend of the outcome
- 2.0% a year
- Coverage of the instrument
- 70%
- Compliance
- 75%
- Effect size, against the teaching value
- 100%
- Years ahead
- 20 years
Readouts
- Largest reduction at the horizon
- Regulation
- Its reduction against the baseline
- 21%
Numbers, methods and sources
| Year | Baseline | Regulation | Economic incentive | Information and capacity |
|---|---|---|---|---|
| 0 | 100.0 | 99.5 | 98.8 | 99.1 |
| 1 | 102.0 | 101.2 | 100.1 | 99.8 |
| 2 | 104.0 | 102.5 | 101.1 | 99.9 |
| 3 | 106.1 | 103.5 | 101.6 | 100.0 |
| 4 | 108.2 | 103.7 | 101.8 | 100.7 |
| 5 | 110.4 | 103.2 | 101.7 | 102.1 |
| 6 | 112.6 | 102.0 | 101.6 | 103.9 |
| 7 | 114.9 | 100.4 | 101.6 | 105.9 |
| 8 | 117.2 | 99.2 | 102.1 | 108.0 |
| 9 | 119.5 | 98.6 | 102.9 | 110.1 |
| 10 | 121.9 | 98.9 | 104.2 | 112.3 |
| 11 | 124.3 | 99.7 | 105.7 | 114.5 |
| 12 | 126.8 | 101.1 | 107.4 | 116.8 |
| 13 | 129.4 | 102.7 | 109.4 | 119.2 |
| 14 | 131.9 | 104.5 | 111.4 | 121.6 |
| 15 | 134.6 | 106.5 | 113.5 | 124.0 |
| 16 | 137.3 | 108.5 | 115.7 | 126.5 |
| 17 | 140.0 | 110.7 | 118.0 | 129.0 |
| 18 | 142.8 | 112.9 | 120.4 | 131.6 |
| 19 | 145.7 | 115.1 | 122.8 | 134.2 |
| 20 | 148.6 | 117.4 | 125.2 | 136.9 |
Methods
- Tools of government Hood (1983), The Tools of Government, Macmillan
- Carrots, sticks and sermons Bemelmans-Videc, Rist and Vedung (1998), Transaction
- Diffusion of innovations Rogers (2003), Diffusion of Innovations, Free Press
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page's map can draw:
- Borders Natural Earth
- Cities Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Innovation Nexus in Foundry
- Tested at Innovation Nexus in Universe
- Codified in Open Infrastructure and Developers in Standards
- Published in Innovation Nexus in Reports
- Taught in Faculty of Technology and Digital Systems in Academy
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| UK Financial Conduct Authority regulatory sandbox records | Cohort lists, eligibility criteria and lessons-learned reports | Open, attribution (FCA terms) |
| World Bank and CGAP regulatory sandbox research | Inventory and design features of fintech sandboxes worldwide | Free, attribution (CC BY IGO) |
| Global Financial Innovation Network | Cross-border testing arrangements among financial regulators | Public records, terms per member |
| EUR-Lex: EU AI Act provisions on sandboxes | Legal basis and conditions for AI regulatory sandboxes and testing in real-world conditions | Free reuse, attribution (Commission reuse decision) |
| OECD Indicators of Regulatory Policy and Governance (iREG) | Practice of impact assessment, consultation and ex post evaluation by country | Open, attribution (OECD terms) |
| National regulators' registers and annual reports | Sandbox programmes in energy, health, transport, data and telecommunications | Public records, terms per regulator |
From mandate to evaluation, by pillar.
The steps an instrument takes from mandate to evaluation, each with the pillar that runs it, and the decisions that stay with the authority. Teaching model with stated illustrative values, not a prediction.
- Mandate and problem framing Competent authority (outside the programme)
A competent authority frames the problem and the mandate under its own rules. Howlett, Ramesh and Perl (2009) - Evidence and system model Foundry
The system is modelled with its feedbacks, data and stated limits. OECD (2014), principle 2 - Options appraised with scenarios Foundry
Instruments are compared under scenarios, with uncertainty shown. Hood (1983) - Exercise with stakeholders Universe
The options are tested in an exercise with those who would implement and bear them. OECD (2014), principle 3 - Standard or guidance drafted Nexus Standards
What works is codified as a standard or guidance, open to comment. Nexus Standards process - Decision by the authority Competent authority (outside the programme)
The authority decides, outside the programme, with the evidence on record. Howlett, Ramesh and Perl (2009) - Capacity and training Risk Academy
Those who implement are trained on the decided instrument and its data. Sendai Framework (2015), priority 2 - Monitoring and public report Reports
Indicators are published with sources, limits and corrections. OECD (2014), principle 5 - Evaluation and revision Nexus Standards
Results return to the standard and the model: the cycle closes. Howlett, Ramesh and Perl (2009)
Methods
- Policy cycle Howlett, Ramesh and Perl (2009), Studying Public Policy, Oxford University Press
- Governance of critical risks OECD (2014), Recommendation of the Council on the Governance of Critical Risks
- Layered drawing of directed graphs Sugiyama, Tagawa and Toda (1981), IEEE SMC 11
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Innovation Nexus in Foundry
- Tested at Innovation Nexus in Universe
- Codified in Open Infrastructure and Developers in Standards
- Published in Innovation Nexus in Reports
- Taught in Faculty of Technology and Digital Systems in Academy
Who decides, and what the evidence serves.
Innovation Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Sector regulators (financial, energy, health, telecommunications, data protection) | Whether to open a sandbox, on what eligibility and safeguards, and how to end it | Sandbox design guides; comparative registers of other regulators' criteria and outcomes |
| National competent authorities under the EU AI Act | How to run AI regulatory sandboxes and supervise testing in real-world conditions | Legal provisions, implementing acts and comparative experience from other sectors |
| Legislatures and regulatory oversight bodies | Whether a regulator holds the mandate to experiment and how experiments are reviewed | Comparative legal bases for sandboxes; ex post evaluation practice |
| Competition authorities | Whether admission to a sandbox gives participants an unfair advantage | Admission criteria, cohort composition and access records |
Outputs this topic produces
- Sandbox design guides covering eligibility, safeguards, exit and evaluation
- Comparative registers of experimental regimes with their criteria and published outcomes
- Evaluation frameworks that separate learning for rule-making from participant success
- Dialogue formats that bring regulators across sectors and borders together on shared experiments
How experimental governance is governed: instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Policy instrument matrix
The kinds of instrument available on experimental governance, by level of government and cooperation.
| Instrument type | Local | National | Regional | Global |
|---|---|---|---|---|
| Regulatory | Zoning, building codes | Laws, standards, licensing | Harmonised rules | Conventions and treaties |
| Economic | Local levies, grants | Budget lines, taxes, insurance schemes | Risk pools, regional funds | Financing mechanisms |
| Information | Local warnings | Disclosure, early warning, statistics | Data sharing arrangements | Global monitoring and reporting |
| Institutional | Local committees | Lead agencies, coordination councils | Regional bodies and secretariats | Multilateral mandates |
| Cooperative | Community agreements | Partnership compacts | Memoranda and joint programmes | Agreements and joint commitments |
What experts ask.
The questions concern what is tested, under whose authority, and what is learned.
- What exactly is being tested: a technology, a business model, a rule or an institutional process?
- Which authority has the power to permit the test, and under what conditions?
- How are participants and the public protected during the test?
- How will results be evaluated, and will they be published?
- What happens at the end: permanent rules, extension or withdrawal?
Mechanisms and drivers.
A regulatory sandbox is a framework set up by a regulator that allows firms to test innovations under supervision, sometimes with tailored requirements, for a limited time. Only a regulator with the relevant legal powers can create one, and it applies only within that regulator's remit. Pilots and test beds are broader tools that public bodies and others use to try new approaches at small scale.
Experiments produce learning only if they are designed to: with clear questions, comparison groups where possible, and honest publication of results, including failures. Common weaknesses include selection of participants who would have succeeded anyway, short duration, and pressure to declare success.
Why now: regulatory sandboxes and testing regimes are spreading, including the AI regulatory sandboxes foreseen under the European Union AI Act (2024). Innovation Nexus compares their rules on scope, safeguards and exit, and a governed trial can be exercised in Universe before it touches the public.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Evaluation design, including comparison groups | Whether an intervention made a difference | Randomisation is often impractical |
| Process evaluation | How the test was implemented | Does not establish effect |
| Comparative analysis of sandboxes | How frameworks differ across jurisdictions | Outcomes are rarely published in comparable form |
| Systems engineering test protocols | Structured testing of complex systems | Controlled tests may not reflect real use |
How it is studied, and what the methods cannot say.
- 01Policy, institutional and decision scienceMandate and gap mapping · Programme evaluation design · Comparative regulatory analysisApplied here
- 02Systems engineeringRequirements traceability for AI governance · Readiness gates for transfer programmesApplied here
- 03Artificial intelligence and machine learningCoding policy and legal texts · Mapping patents and papers to technologiesApplied here
Questions and answers.
Does a sandbox exempt firms from the law?
What is the difference between a sandbox and an innovation hub?
How should a sandbox be evaluated?
Does Innovation Nexus run sandboxes or test products?
Does Innovation Nexus run a regulatory sandbox?
Is testing in Universe a regulatory approval?
Why publish failed experiments?
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