Artificial intelligence has quickly shifted from a novelty to an operational necessity for associations. According to Momentive's 2025 Associations Trends study, the AI adoption rate among association professionals doubled year over year, to 39%During the same time period, the share of organizations that report having an AI policy in place rose from 23% to 40% Board conversations are ramping up, staff are experimenting, and members increasingly expect the kind of personalized, data-driven engagement that AI makes possible.
But while enthusiasm has surged, readiness and strategy remain uneven. Many organizations still feel caught between curiosity and concern, eager to leverage AI's benefits but unsure how to do so safely or sustainably. Drawing from our professional experiences as a technology provider and an association professional in AI and data roles, we've seen that AI presents enormous opportunities, but only if associations approach it thoughtfully, with governance, and with a focus on people as much as technology.
Understanding the Current AI Landscape
AI adoption is accelerating in associations, but not every tool or approach is equal. While some organizations are still experimenting with free versions, many are investing in paid AI solutions to maintain control over sensitive data and ensure reliability. Organizations that pay for AI solutions typically benefit from greater privacy protections and tailored capabilities, while free tools, although accessible, may present risks if used with proprietary or personally identifiable information (PII).
Beyond tools, governance is critical. AI policies serve as guardrails, helping staff use AI responsibly while preventing data compromise or misuse. In our experience working with associations, overly rigid policies often backfire; staff may circumvent restrictions, using personal accounts or unauthorized tools, which creates more risk than it prevents. The most effective policies are flexible, iterative, and tied to organizational objectives.
Designing a Strategic AI Policy
A strong AI policy starts with clarity around data usage. Associations must identify what information can safely enter AI tools and establish clear guidelines on what is restricted. Policies should differentiate between personal data, organizational data, and publicly available information, and outline specific processes for reviewing new AI use cases.
From a practical standpoint, we recommend that associations focus on five core elements when implementing AI policies: purpose, people, projects, platforms, and performance.
Regular review and iteration are key. AI tools and capabilities evolve quickly, so policies must be revisited frequently to ensure they remain relevant and effective. For smaller organizations, this may mean annual reviews; for larger associations, quarterly evaluations can help keep pace with technological change.
AI as a Workforce Multiplier
A critical dimension of AI adoption is its impact on association staff, particularly entry-level roles. Routine tasks such as drafting content, managing spreadsheets, or compiling basic reports are increasingly being automated, which can shift the focus of early career staff toward work that is higher in critical thinking, strategic analysis, and creative problem-solving.
But automation shouldn't come at the expense of learning foundational skills. Staff still need to develop operational and analytical capabilities alongside AI tools. Associations that provide training, certifications, and peer learning programs equip staff to thrive in a human-plus-AI environment. The goal is augmentation, not replacement: AI can enhance productivity and insight, but staff must remain capable of judgment and strategic thinking.
AI adoption also prompts bigger questions about career pathways. As routine tasks shift, associations must ensure early-career staff still gain transferable, robust experiences. Leaders need to anticipate both emerging skill requirements and potential gaps that AI might create if foundational experiences are overlooked.
Navigating Risk and Governance
AI introduces a range of risk and governance considerations. Associations must maintain visibility over who is using AI tools, what data is shared, and how decisions derived from AI outputs align with organizational standards. Human oversight is essential because AI lacks context, conscience, and the ability to judge nuanced, association-specific standards.
Policies must clearly define what constitutes acceptable AI use, establish approval workflows, and provide audit trails to track methods and data sharing and usage. Security and compliance teams play a pivotal role, but collaboration with programmatic, membership, and operational staff ensures policies are both practical and attainable.
Enforcement is another critical component. Simply having a policy is insufficient; staff must be trained, accountable, and informed about the consequences of misuse—whether intentional or accidental. Many associations integrate AI usage into existing confidentiality agreements or require completion of training modules to ensure awareness.
Practical Approaches to AI Adoption
Associations, particularly small-staff organizations, may feel overwhelmed by AI adoption. Starting small is often the most effective approach. Identify a single, high-priority challenge—policy documentation, member communications, or event analytics—and experiment with AI solutions in a controlled, measured way. This allows staff to gain familiarity, assess outcomes, and refine processes before scaling adoption across the organization.
Many platforms used daily by associations already incorporate AI capabilities, often unrecognized by staff. Understanding what is available, exploring vendor roadmaps, and connecting with peer organizations through networks, such as ASAE, can provide valuable guidance, reduce learning curves, and accelerate responsible adoption. Academic partnerships, such as collaborations between associations and university research centers, may offer access to emerging AI innovations and pilot programs at a reduced cost.
Charting the Path Forward
As associations weave AI more deeply into daily work, it becomes less about technology and more about how people use it. The organizations seeing the most meaningful impact are the ones that treat AI as a way to elevate human skills like judgment, creativity, and connection. When routine tasks fall away, staff have more room to apply the expertise that truly moves missions forward.
Getting ready for that future starts with understanding your data. Many associations underestimate how scattered their information is across systems and teams. Before AI can help, leaders need clarity on where data lives, who has access, and what risks or opportunities come with using it. With that foundation in place, governance decisions become easier and far more strategic.
From both the technology and association perspective, we've seen AI become a powerful amplifier when it's guided thoughtfully. It can speed up work, illuminate insights, and deepen engagement, but only when paired with good governance and a commitment to preparing staff for what's ahead. Associations that stay curious, flexible, and mission-focused will be best positioned to use AI not as a replacement for human expertise, but as a catalyst for even greater impact.
