AI Standards & Guidelines
Set the standards for your organization
BBTx Consulting
Practical guidance for leading organizations through AI adoption and governance.
Developing Organizational Standards and Guidelines for Artificial Intelligence
A guide for organizations that are not yet using AI, those in the early stages, and those building sophisticated enterprise AI integration plans.
Prepared for
Client and leadership use
Prepared by
BBTx Consulting
Version
v1
Date
March 7, 2026
Purpose: This document provides a practical framework organizations can use to draft their own AI standards, guidelines, and governance rules in a way that matches their current level of AI maturity.
Contents
1. Purpose
2. Core principle
3. What AI standards and guidelines should cover
4. Foundational design principles
5. Guidance for organizations not currently using AI
6. Guidance for organizations in the early stages of AI use
7. Guidance for sophisticated AI integration plans
8. Suggested structure for an organizational AI standards document
9. Practical questions for leadership and planning teams
10. Implementation roadmap
11. Sample policy statements organizations can adapt
12. Common mistakes to avoid
13. Conclusion
Appendix. One-page leader summary
1. Purpose
Artificial intelligence is no longer an issue only for advanced organizations. Even organizations with no formal AI program need a clear set of standards and guidelines because employees, contractors, and vendors are increasingly exposed to AI-enabled tools in everyday work.
The purpose of organizational AI standards is to reduce risk, improve quality and consistency, protect confidential information, support learning and innovation, and align AI practices with the organization’s mission and values.
2. Core principle
Every organization should establish an AI governance framework proportionate to its level of AI maturity. That framework should answer five practical questions:
What is permitted?
What is prohibited?
What requires review or approval?
Who is accountable?
How will the organization learn and improve over time?
3. What AI standards and guidelines should cover
Purpose and scope
The standards should explain why they exist, define who is covered, and provide a practical definition of AI that includes generative AI, predictive systems, machine learning applications, chatbots, transcription and summarization tools, recommendation systems, and other pattern-based tools that influence work.
Ethical and strategic principles
Transparency
Fairness
Privacy
Human accountability
Security
Reliability
Respect for intellectual property
Alignment with mission and values
Acceptable, restricted, and prohibited uses
The standards should distinguish clearly among approved uses, restricted uses that need additional review, and prohibited uses that are not allowed under any circumstances.
Data handling and privacy
This section should identify what data may or may not be entered into AI systems, especially confidential business information, client data, employee records, health information, financial information, legal materials, and unpublished intellectual property.
Human review and accountability
The standards should make clear that AI does not remove human responsibility. Final accountability for decisions, analyses, and official communications remains with human personnel.
Quality, accuracy, and compliance
Users should be required to verify important facts, evaluate outputs for bias or distortion, review for audience appropriateness, and comply with applicable law, regulation, contract terms, and records requirements.
4. Foundational design principles
Human responsibility remains central
AI may assist with drafting, research, analysis, and recommendations, but it should not replace human judgment in areas involving ethics, legal responsibility, people decisions, safety, or material business consequences.
Please note: As organizational leaders, we suggest your legal counsel review your final document if you use these outlines.
