How to Use ISMS Copilot Responsibly

Overview

Responsible use of AI tools requires understanding their capabilities, limitations, and appropriate applications. This guide provides practical best practices for using ISMS Copilot effectively and ethically in your compliance work.

Who This Is For

This article is for:

• Compliance professionals using AI for the first time

• Teams establishing AI governance policies

• Consultants managing multiple client projects

• Anyone who wants to maximize AI value while minimizing risks

Core Principles of Responsible AI Use

1. AI as Assistant, Not Replacement

The Right Mindset:

• Think of ISMS Copilot as a knowledgeable junior consultant

• It provides drafts and suggestions, not final deliverables

• Human expertise, judgment, and review remain essential

• AI accelerates work but doesn't replace professional responsibility

2. Verify Before You Trust

Always validate:

• Control numbers and framework citations

• Regulatory requirements and compliance mandates

• Technical specifications and implementation details

• Statistics, timelines, and quantitative claims

Verification sources:

• Official standards (ISO 27001:2022, SOC 2 criteria, etc.)

• Regulatory guidance documents

• Industry frameworks and best practice guides

• Legal and compliance experts

3. Context Is Everything

AI needs your organizational context:

• Industry and regulatory environment

• Organization size and complexity

• Current ISMS maturity level

• Risk tolerance and business objectives

• Available resources and timeline

4. Transparency in AI Use

Be open about using AI:

• Disclose AI-assisted work to clients when appropriate

• Document AI use in your compliance processes

• Include AI tools in your data processing agreements

• Train your team on proper AI use and limitations

Best Practices for Asking Questions

Be Specific and Detailed

Instead of vague questions:

• ❌ "Tell me about ISO 27001"

• ❌ "How do I do access control?"

• ❌ "What's SOC 2?"

Ask specific, contextualized questions:

• ✓ "How do I implement ISO 27001:2022 control 5.15 (Access Control) for a 50-person SaaS company?"

• ✓ "What evidence do I need for SOC 2 CC6.1 (Logical and Physical Access Controls) for our AWS-hosted application?"

• ✓ "What are the key steps to create a GDPR-compliant data retention policy for customer support records?"

Provide Relevant Context

Useful context to include:

• Organization profile: "We're a 200-employee healthcare SaaS company..."

• Current state: "We're implementing ISO 27001 for the first time..."

• Specific goal: "We need to prepare for our Stage 2 audit in 3 months..."

• Constraints: "We have limited IT security staff and a small budget..."

• Framework version: "We're working with ISO 27001:2022, not the 2013 version..."

Break Down Complex Questions

Instead of one massive question:

❌ "How do I implement ISO 27001 from scratch including risk assessment, controls, policies, procedures, and prepare for certification?"

Break into focused questions:

1. "What are the key phases of ISO 27001 implementation for a first-time organization?"

2. "How do I conduct an ISO 27001 risk assessment for a cloud-based SaaS platform?"

3. "What policies are required for ISO 27001:2022 certification?"

4. "What evidence should I prepare for an ISO 27001 Stage 2 audit?"

Ask for Explanations, Not Just Answers

Questions that promote understanding:

• "Explain the difference between ISO 27001 controls 5.15 and 8.2"

• "Why is segregation of duties important for SOC 2 compliance?"

• "What's the rationale behind GDPR's data minimization principle?"

• "Walk me through the logic of risk treatment decision-making in ISO 27001"

Benefits:

• Deepens your understanding of compliance concepts

• Helps you explain requirements to stakeholders

• Enables better customization to your organization

• Makes you a more effective compliance professional

Best Practices for Document Generation

Use AI for First Drafts

Good use cases for AI drafting:

• Policy and procedure templates

• Risk assessment frameworks

• Control implementation guides

• Gap analysis documentation

• Audit preparation checklists

Workflow:

1. Generate: Ask ISMS Copilot to create a policy draft

2. Review: Check for accuracy, completeness, and relevance

3. Customize: Adapt to your organization's specific context

4. Enhance: Add organization-specific details and examples

5. Validate: Have compliance expert or auditor review

6. Approve: Final sign-off by appropriate authority

Customize to Your Organization

Areas requiring customization:

• Roles and responsibilities: Actual job titles and names

• Technical environment: Specific systems, tools, and platforms

• Business processes: How your organization actually operates

• Risk profile: Your specific threats, vulnerabilities, and risk appetite

• Regulatory requirements: Industry-specific or jurisdiction-specific rules

Example customization:

AI-generated (generic):

"The Information Security Manager is responsible for overseeing access control processes."

Customized (specific):

"The Chief Information Security Officer (CISO), Jane Smith, delegates access control oversight to the IT Operations Manager, who uses Okta for identity management and reviews access logs weekly via Splunk."

Add Evidence and Implementation Details

Transform AI policies into audit-ready documentation:

• Add specific tool names (e.g., "using Vanta for compliance automation")

• Include evidence locations (e.g., "access logs stored in S3 bucket: company-audit-logs")

• Reference related procedures (e.g., "See SOP-001: User Onboarding Process")

• Document review cycles (e.g., "Policy reviewed quarterly by Security Committee")

• Link to compliance artifacts (e.g., "Risk register maintained in Jira Security project")

Best Practices for File Uploads

What to Upload

Good documents to analyze:

• Existing policies for gap analysis

• Risk assessments for review and improvement

• Audit reports for remediation planning

• Control matrices for completeness checks

• Vendor security questionnaires for response drafting

File requirements:

• Maximum 10MB per file

• Supported formats: PDF, DOCX, DOC, XLSX, XLS, TXT, CSV, JSON

• One file at a time

Data Sensitivity Considerations

Before uploading sensitive data:

1. Review what personal or confidential information the document contains

2. Consider anonymizing client names, employee details, or proprietary information

3. Remember that uploaded files are retained based on your data retention settings

4. Use workspaces to isolate different clients' data

What NOT to Upload

Avoid uploading:

• Copyrighted ISO standards or proprietary frameworks (AI won't process them)

• Raw credential files or passwords

• Unredacted PII or sensitive personal data

• Client data without appropriate contractual agreements

• Documents containing trade secrets unless necessary

Workspace Management Best Practices

Organize by Project or Client

Recommended workspace structure:

• For consultants: One workspace per client

• For organizations: One workspace per framework or initiative

• For multi-phase projects: Separate workspaces for planning, implementation, and audit prep

Example workspace names:

• "Client A - ISO 27001:2022 Implementation"

• "SOC 2 Type II Audit Prep Q1 2024"

• "GDPR Compliance - HR Department"

• "Risk Assessment - Cloud Infrastructure"

Use Custom Instructions Effectively

Good custom instructions:

• "Focus on ISO 27001:2022 controls. We're a healthcare SaaS company subject to HIPAA."

• "We're preparing for SOC 2 Type II audit. Emphasize evidence collection and documentation."

• "This is a small startup (20 employees) with limited security resources. Prioritize practical, cost-effective controls."

Instructions that won't work:

• ❌ Attempting to override safety constraints

• ❌ Requesting non-compliance content

• ❌ Asking to ignore copyright protections

Clean Up Completed Workspaces

When to delete workspaces:

• Project or engagement is complete

• Data retention period for that client has expired

• Client contract requires data deletion

• Workspace was created for testing or experimentation

Before deleting:

1. Export any important conversations or documentation

2. Archive relevant information in your compliance management system

3. Verify you don't need the workspace for future reference

4. Delete the workspace to maintain data hygiene

Data Retention Best Practices

Setting Appropriate Retention Periods

Consider:

• Legal requirements: Regulatory retention mandates for your industry

• Contract obligations: Client agreements on data retention

• Business needs: How long you need conversation history for reference

• Risk profile: Balance between data utility and exposure minimization

Recommended retention periods:

Export Before Expiration

For important conversations:

1. Copy conversation content before retention period expires

2. Save to your compliance management system or documentation repository

3. Include relevant metadata (date, workspace, context)

4. Follow your organization's records management procedures

Temporary Chat Appropriate Use

When to Use Temporary Chat

Good use cases:

• Quick one-off questions that don't need permanent storage

• Exploratory research before committing to a workspace

• Sensitive discussions you don't want in permanent history

• Testing how to phrase complex questions

Not appropriate for:

• Important project work you'll need to reference later

• Generating documentation for audits

• Building organizational knowledge base

• Work you may need as evidence of compliance activity

Remember the 30-Day Safety Window

Important limitation:

Even temporary chats may be retained for up to 30 days for safety monitoring and abuse prevention.

What this means:

• Temporary chat isn't completely ephemeral

• Data may be reviewed if safety concerns arise

• Still subject to data processing agreements

• Use regular workspaces if you need complete control over retention

Ethical Considerations

Client Confidentiality

Protect client information:

• Use separate workspaces for different clients

• Anonymize client names in documents when possible

• Include AI use in your client contracts and NDAs

• Set retention periods that comply with client agreements

• Inform clients if using AI tools for their work

• Enable Advanced Data Protection Mode when client contracts require EU-only data processing or zero AI provider retention

Attribution and Disclosure

When delivering work to clients:

• Be transparent about AI assistance in creating deliverables

• Emphasize your expert review and customization

• Don't claim AI-generated content as purely original work

• Explain how AI enhanced efficiency without compromising quality

Avoiding Over-Reliance

Warning signs of over-reliance:

• Accepting AI responses without verification

• Skipping expert review of AI-generated documents

• Using AI as a substitute for learning compliance frameworks

• Delivering AI content without customization

• Making critical decisions based solely on AI advice

Maintain professional competence:

• Continue learning about frameworks and standards

• Engage with compliance community and thought leaders

• Attend training and certification programs

• Read official standards and regulatory guidance

• Develop expertise beyond AI-assisted work

Team Training and Governance

Establishing AI Use Policies

Key policy elements:

1. Approved use cases: What AI can and cannot be used for

2. Review requirements: Who must review AI-generated content

3. Verification standards: How to validate AI output

4. Data handling: What data can be uploaded and how

5. Client disclosure: When and how to inform clients of AI use

6. Documentation: How to record AI assistance in work products

Training Your Team

Essential training topics:

• How ISMS Copilot works and its limitations

• Recognizing and reporting hallucinations

• Effective prompting techniques

• Verification and customization requirements

• Data sensitivity and privacy considerations

• Workspace and retention management

• Ethical AI use principles

Quality Assurance Processes

Implement review checkpoints:

1. AI Draft: Initial AI-generated content

2. First Review: Subject matter expert verifies accuracy

3. Customization: Adapt to organizational context

4. Second Review: Compliance lead checks completeness

5. Final Approval: Authorized reviewer signs off

6. Audit Trail: Document review and approval

Measuring Effectiveness

Track AI Value

Metrics to consider:

• Time saved on policy drafting

• Reduction in compliance preparation cycles

• Number of audit findings (to ensure quality isn't compromised)

• Team satisfaction with AI assistance

• Client feedback on deliverable quality

Continuous Improvement

Refine your approach:

• Document effective prompts and questions

• Share best practices across your team

• Track and report hallucinations to improve the system

• Update AI use policies based on experience

• Adjust retention and workspace strategies as needed

Responsible AI Checklist

Before Using AI

• ✓ Understand your organization's AI use policy

• ✓ Check client contracts for AI tool restrictions

• ✓ Plan for verification and review processes

• ✓ Set appropriate data retention periods

• ✓ Create workspaces for different projects/clients

During AI Use

• ✓ Provide specific, contextualized questions

• ✓ Review responses for accuracy and relevance

• ✓ Customize AI output to your organization

• ✓ Cross-reference with official standards

• ✓ Maintain professional judgment

After AI Use

• ✓ Have expert review AI-generated content

• ✓ Document AI assistance in work products

• ✓ Report hallucinations or safety concerns

• ✓ Archive important conversations before expiration

• ✓ Delete completed workspaces appropriately

What's Next

• Learn about AI safety guardrails and constraints

• Understand how to identify and prevent hallucinations

• Start your first conversation with best practices

• Set up workspaces to organize your work

Getting Help

For questions about responsible AI use:

• Review the Trust Center for AI governance guidance

• Contact support through the Help Center menu

• Report safety concerns or inappropriate AI behavior

• Share feedback on AI effectiveness and usability