Organizational Standards for AI Adoption and Use

ASAE encourages the use of AI to improve how we work, serve members, and lead the association community. This policy exists to enable adoption with clear guardrails.

Ten Key Concepts Guide All AI Use at ASAE

1. Know What is Prohibited – Some uses are off limits regardless of intent: entering member, employee, financial, or legally privileged information into an unapproved tool; using personal AI accounts or unapproved tools for ASAE work; relying on AI to make final decisions about hiring, personnel, or member standing; generating content that impersonates a real person or misstates an ASAE position; and any use that is unlawful, harassing, discriminatory, or that circumvents ASAE’s security, privacy, or licensing controls. Failure to follow any of these policies is treated like any other ASAE policy violation and may result in corrective action up to and including termination of employment. If you encounter any suspected violation of this policy, immediately report it to your supervisor, then to the AI Strategy Group.
2. Encourage Learning & Use – AI is a technology for everyone at ASAE, not a privilege for technical staff – all employees are encouraged to explore how AI can improve their work. ASAE provides AI certification, training, and evolving resources, and staff are expected both to complete this foundational training before using AI in their work, and to keep current as the curriculum expands.
3. Protect Member Data – AI use must avoid personally identifiable information (PII). When any form of PII is required, such as for personalization, the AI usage must be specifically approved by the AI Strategy Group, limited to the bare minimum PII needed, be verified to keep data private, strictly control access to the data, and never allow the data to train AI models.
4. Verify and Own the Output – People make decisions at ASAE, not AI. AI-generated content, analysis, and recommendations must be reviewed by a human before being published, sent, or acted upon, and every AI-assisted process must have a person answerable for its accuracy, its outcomes, and the authenticity of what it produces. Technology enables our work; it does not excuse our judgment nor our accountability.
5. Be Transparent – Transparency builds trust. When AI plays a meaningful role in producing member-facing content, communications, or recommendations, acknowledge it. While disclosure is recommended for internal usage, it is required for member-facing work and staff must never misrepresent how content was created.
6. Respect Intellectual Property – Do not input copyrighted material into AI tools without authorization. Do not present AI-generated content as original work when it substantially reproduces existing material. When AI assists in content creation, ensure the output is original and does not infringe on others’ rights.
7. Choose Approved Tools – Use AI tools that have been reviewed and approved for ASAE use. Approved tools are maintained on a separate list and updated regularly. If you find a tool that could benefit your work, recommend it for review and approval by the AI Strategy Group before use.
8. Watch for Bias – AI models can reflect biases present in their training data. Review AI outputs for language, assumptions, or recommendations that may inadvertently exclude, stereotype, or disadvantage any group. This is especially critical in member-facing content and data-driven decisions.
9. Value Quality Over Volume – Volume does not equal quality. AI makes it easy to produce more, but it does not make more worth reading. Be considerate of the time needed for others to consume what you produce and publish or send only what earns the attention it asks for.
10. Measure the Impact – Track what AI saves and what it produces, and only use AI when traditional workflows do not suffice. Before launching an AI-assisted workflow, capture a baseline. Report results so the organization can learn what works, scale what succeeds, and stop what doesn’t. Use AI with respect for the resource impact it has, choosing lesser models when appropriate to the task, or no AI at all if it’s not needed.

A Note on Governance and Revision – This policy is overseen by ASAE’s AI Strategy Group, led by Keith Soares, VP of Digital & AI Strategy, which reviews tool requests and exceptions and answers questions about applying this policy. AI is changing faster than any policy can anticipate, and this policy is intended to enable, not obstruct. It will therefore be reviewed and updated at minimum twice per year, shaped by staff feedback, new capabilities, and lessons learned. Send questions, suggestions, and tool recommendations to the AI Strategy Group.

Version 1.3. September 2026