Ethical AI process improvement with human judgement built in.
Leanable applies ethical AI process improvement principles to every engagement. This plain-English policy explains how AI supports stakeholder interviews, analysis and report drafting, where human judgement remains essential, and how our approach aligns with responsible AI expectations in New Zealand and Australia.
Ethical AI process improvement keeps professional judgement in control.
Leanable uses AI to support interviews, analysis and report drafting. The AI does not replace the expertise. It operationalises it. Four human approval gates and senior business analyst review help ensure completed outputs are grounded in the engagement evidence before delivery.
Ethical AI process improvement policy
Plain English. Written for Leanable clients, stakeholders and procurement reviewers in New Zealand and Australia.
1. Purpose of our ethical AI process improvement policy
This policy explains how Leanable uses artificial intelligence in a responsible, safe and transparent way during process improvement engagements. It helps clients and stakeholders understand where AI is used, where human judgement remains essential and what controls reduce the risk of inaccurate, unfair or unsupported analysis.
Leanable’s approach is informed by New Zealand responsible AI guidance for the public service and Australia’s AI Ethics Principles, including safe, transparent and accountable AI use, privacy protection, fairness, human oversight, security, reliability, contestability and accountability. Leanable is a Changeable product, with more background available on the About Leanable page.
2. How Leanable uses AI
Leanable uses ethical AI process improvement controls throughout its eight-phase methodology. AI may assist with structured stakeholder interviews, transcript analysis, theme identification, current-state analysis, opportunity identification, future-state design, automation assessment, report drafting and plain-English summarisation.
- AI helps process and organise information collected during an engagement.
- AI helps identify patterns, risks, pain points and improvement opportunities.
- AI helps generate draft analysis for human review.
- AI does not make final decisions for clients.
- AI does not replace professional judgement, business analysis review or client accountability.
3. Human oversight, approval gates and accountability
Leanable includes four human approval gates during Current State Analysis, Opportunity Identification and Research, Future State Design, and AI and Automation Assessment. Completed reports are also reviewed by a senior business analyst before delivery. This checks whether the analysis is reasonable, relevant to the engagement context, grounded in the information provided and presented in a way clients can understand and challenge.
- A human reviewer remains accountable for the final delivered report.
- AI output is treated as draft support, not as final professional advice.
- Client decisions remain the responsibility of the client organisation.
- Recommendations should be assessed against operational reality, legal obligations, employment obligations, privacy obligations and organisational context before implementation.
Leanable outputs are business analysis and process improvement support. They are not legal, financial, employment, privacy, cybersecurity, medical or professional advice.
4. Privacy and personal information
Leanable is designed to collect only the information needed to deliver the engagement, as explained in our Data Handling and Privacy Policy pages. Where personal information is involved, we aim to handle it consistently with New Zealand Privacy Act 2020 principles and Australian privacy expectations, including transparency, reasonable collection, secure handling, limited access and deletion on request where appropriate.
- We avoid collecting unnecessary personal information.
- We ask clients not to upload sensitive information unless it is genuinely required for the engagement.
- We use engagement data to deliver the service, not for advertising.
- We do not sell client or stakeholder data.
- We explain AI processing separately in our Data Handling page.
5. Transparency in AI-assisted process improvement
Clients and stakeholders should know when AI is part of the service. Leanable clearly explains that AI supports stakeholder interviews, transcript analysis, structured recommendations and report generation while human reviewers retain responsibility for approval and delivery.
- We disclose that AI is used in the Leanable process.
- We explain the role AI plays in analysis and report drafting.
- We identify the AI provider used for processing in our Data Handling page.
- We make clear that final outputs are reviewed before delivery.
6. Fairness, evidence quality and bias awareness
AI systems can reflect bias, incomplete information, minority viewpoints that are easy to overlook, unclear assumptions or overconfident patterns. Leanable treats AI-generated analysis as evidence to be tested and reviewed, not as a conclusion that should be accepted automatically.
- We review outputs for unsupported claims, unfair framing and overstatement.
- We avoid using AI to rank, discipline, profile or make employment decisions about individual workers.
- We focus on process-level analysis rather than blaming individuals.
- We encourage clients to test findings with operational context before acting on recommendations.
7. Safety, reliability and quality control
Leanable uses AI in a controlled way to support bounded process improvement tasks, consistent with practical responsible AI practices such as risk management, human oversight and clear governance. We do not use AI as an unrestricted decision engine or autonomous management system.
- We use structured prompts and defined engagement workflows.
- We review outputs before they are delivered to clients.
- We avoid presenting AI-generated content as certain where the evidence is incomplete.
- We distinguish between stakeholder input, analysis, assumptions and recommendations where practical.
- We may ask for clarification where the process scope or evidence is unclear.
8. Contestability and correction
Clients should be able to question, correct or challenge Leanable outputs. If a report includes an inaccurate process detail, misunderstood context or unsupported conclusion, clients can contact us for review.
- Clients can request clarification about findings or recommendations.
- Clients can identify factual errors or missing context.
- Where appropriate, we may revise a report to correct material inaccuracies.
- Stakeholder feedback should be considered before major operational changes are implemented.
9. Acceptable AI use
Leanable should be used for constructive process improvement, not surveillance, punishment or covert monitoring. Clients must not use Leanable to process information they do not have the right to provide.
- Do not upload confidential, personal or sensitive information unless you have authority to do so.
- Do not use Leanable to covertly monitor staff or stakeholders.
- Do not use Leanable outputs as the sole basis for employment, disciplinary, legal or financial decisions.
- Do not submit false, misleading or deliberately incomplete information.
10. New Zealand and Australia context
Leanable is built for organisations operating in New Zealand and Australia. Responsible AI use in these markets requires more than technical performance. It requires privacy awareness, transparency, human oversight, fairness, contestability, security, cultural awareness, and practical accountability.
For New Zealand clients, responsible use should consider local privacy expectations, employment context, Māori data considerations where relevant, public trust, and the need for clear human accountability. For Australian clients, responsible use should consider privacy obligations, Australia’s AI Ethics Principles, emerging government assurance practices, and sector-specific obligations where relevant.
11. Security and supplier control
AI use creates supplier and data-flow risks. Leanable limits AI processing to the AI provider described in our Data Handling page and uses supporting service providers only where required to deliver the service.
- We aim to limit data access to what is required for the engagement.
- We do not use client data for advertising.
- We do not intentionally train our own AI models on identifiable client engagement data.
- We explain storage, AI processing and deletion in our Data Handling page.
12. Review and improvement
Responsible AI practice will continue to evolve. Leanable may update this policy as laws, standards, government guidance, AI tools, privacy expectations and client requirements change.
Where material changes affect how client data is processed or how AI is used in the service, we will update the relevant privacy, data handling or terms policy pages and, where appropriate, notify affected clients.
13. Questions about responsible AI use
For questions about Leanable’s AI use, human review process, data handling, privacy, procurement review or responsible AI controls, use the Leanable contact page or email hello@leanable.co.nz.
The practical rules behind ethical AI process improvement.
These working principles guide how Leanable uses AI to support process improvement engagements while preserving transparency, privacy, contestability and accountable human review.
Human accountable
AI supports the work, but a human reviewer remains responsible for the final report delivered to the client.
Transparent use
Clients and stakeholders are told that AI supports interviews, analysis and report generation.
Privacy aware
We collect only what is needed, restrict access, and explain where data is stored and processed through the Data Handling page.
Challengeable
Clients can question findings, provide missing context and request correction of material inaccuracies.
Need our ethical AI process improvement approach reviewed?
For questions about responsible AI use, AI processing, data location, supplier access, privacy obligations, human approval gates or internal procurement requirements, contact Leanable before starting an engagement. We can provide the policy and data-handling information needed for procurement or internal review.