Menu

AI Governance Lifecycle Starter

Find where to start with your AI governance.

Answer 20 practical questions across the AI lifecycle. Your responses will be organised into areas to address, strengthen, assess or confirm, with suggested next steps and evidence to consider.

20 control questions5 response states6 action themesClient-side · no account or email

This is a structured starting point, not a compliance assessment, maturity score or risk classification.

20-question Lifecycle Starter

Answer based on what you know today.

You do not need to be an AI governance specialist to use this Starter. Answer based on what you know today. Where you are unsure, select Not assessed.

Established

Maintain and confirm that relevant evidence remains current and reviewable.

Partially established

Strengthen incomplete elements.

Not established

Address the relevant governance or control area.

Not assessed

Assess the area before relying on it.

Potentially not applicable

Confirm applicability and document the rationale.

T1

Q01–Q03

Purpose, Governance & Applicability

Q01Is it clear what the AI system is meant to do?

What this means: Define its intended purpose, who will use it, where it will operate and what decision or activity it will support.

Q02Do you know which rules and standards may apply?

What this means: Consider where the AI will be used, your organisation's role, the sector and relevant laws, regulations, regulatory guidance and standards.

Q03Have the main risks, impacts and responsibilities been considered?

What this means: Consider who could be affected, what could go wrong, who is accountable and where human oversight may be needed.

T2

Q04–Q05

Data

Q04Do you know where the data comes from and whether you are permitted to use it?

What this means: Consider data sources, provenance, permitted use, ownership or stewardship and relevant restrictions.

Q05Is the data suitable for what the AI system is expected to do?

What this means: Consider data quality, relevance, representativeness, known limitations, potential bias and applicable privacy requirements.

T3

Q06–Q07

Third Parties

Q06Have external AI models, systems, data or services been appropriately assessed before use?

What this means: The depth of review should reflect what is being acquired, how it will be used and the associated risk and applicable requirements.

Q07Are responsibilities with external providers clear?

What this means: Consider responsibilities, information needs, changes, security, support, service expectations and exit or transition.

T4

Q08–Q12

Design, Controls & Evaluation

Q08Does the design reflect what the AI must do and the controls it needs?

What this means: Translate intended purpose, applicable requirements and identified risks into appropriate design and operating controls.

Q09Have important safeguards been designed into the system?

What this means: Where relevant, consider human oversight, decision boundaries, transparency or explainability, logging, security and fallback arrangements.

Q10Are important development and configuration changes controlled and traceable?

What this means: Keep important changes to models, software, configuration and versions linked to requirements, decisions and approvals.

Q11Has the AI system been adequately tested before use?

What this means: Evaluate it using criteria appropriate to its intended purpose, risk and applicable requirements. Depending on context, this may involve verification, validation or other evaluation.

Q12Have known limitations and remaining risks been reviewed and accepted?

What this means: Record significant issues, limitations and residual risks, together with the decision to proceed and who approved it.

T5

Q13–Q16

Deployment & Operations

Q13Is the system ready to be deployed in a controlled way?

What this means: Consider readiness criteria, approval, configuration, access, user preparation and fallback or rollback arrangements.

Q14Have any obligations that apply before deployment been checked?

What this means: Depending on context, this may include required information, notices, documentation, registration or other applicable requirements.

Q15Is responsibility for operating and supporting the AI system clear?

What this means: Define ownership and processes for access, configuration, maintenance, service requests, incidents, problems and changes.

Q16Do significant changes trigger a fresh review?

What this means: Changes in purpose, users, data, model, supplier, configuration, jurisdiction or operating context may require reassessment and approval.

T6

Q17–Q20

Monitoring & Retirement

Q17Are you monitoring whether the AI system continues to work as intended?

What this means: Monitor relevant performance, drift, incidents, emerging risks or impacts, security and control indicators using defined criteria or triggers.

Q18Are monitoring results and important external changes reviewed periodically?

What this means: Consider whether performance information, incidents, regulatory changes, new standards or other significant events require changes to controls, risk assessments or approvals.

Q19Is there a controlled plan for retiring or replacing the AI system?

What this means: Consider continuity, communication, access removal, replacement arrangements and supplier or service exit.

Q20Do you know what must happen to the data, models and records when the system is retired?

What this means: Determine what needs to be retained, archived, transferred or disposed of according to applicable requirements and documented decisions.

Generate your on-screen summary

Review every response before continuing.

20 questions still need a response.

RegulatedAI.in organising structure

Continue into the nine-stage lifecycle control map.

The Starter themes organise questions for an initial review. The full RegulatedAI.in lifecycle structure provides the deeper control and evidence map.

01

Concept and Requirements

Define intended purpose, context, stakeholders, requirements, constraints and initial governance boundaries before solution commitment.

02

Data Acquisition and Preparation

Establish that data used to develop, configure, evaluate or operate the AI system is suitable for its intended purpose and governed throughout use.

03

Acquisition and Third-Party Management

Control externally acquired AI systems, models, services, components, data and supporting services.

04

System and Model Design

Translate requirements, governance decisions and risk treatments into an AI system and operating design.

05

Development, Verification and Validation

Build or configure the system and obtain evidence that specified requirements and intended-use expectations are met before deployment.

06

Transition and Deployment

Move the approved AI system into its intended operating environment under controlled conditions.

07

Operation and Maintenance

Operate and support the AI system within approved boundaries while controlling service, configuration and maintenance changes.

08

Monitoring and Continual Evaluation

Monitor performance, risk, impacts and control effectiveness and determine when intervention, reassessment or change is required.

09

Retirement and Disposal

End use of the AI system or component in a controlled manner while preserving required records, continuity and obligations.

The complete method disclosure appears on Lifecycle Controls and What RegulatedAI.in Is. RegulatedAI.in does not attribute this organising structure to a regulator, standards body or other authority.

Response and result boundaries

No score, percentage, benchmark or compliance conclusion.

The Action Summary is produced deterministically from the responses in the current browser session. RegulatedAI.in does not independently verify the answers, classify risk or determine compliance.

Return to the full lifecycle control map

Continue exploring