Artificial Intelligence (AI) offers associations significant opportunities, from improving member engagement to streamlining operations and delivering data-driven insights. But unlocking the full potential of AI isn’t without its obstacles.
Based on our experience working with associations through our Upbeat Membership solution, we understand that successful AI implementation requires acknowledging and addressing common barriers. Here, we outline the key challenges associations may face when adopting AI, and how to navigate them effectively.
Technical expertise: Building internal capabilities:
Many associations lack staff with experience in AI development, data science, or system integration. This knowledge gap makes it difficult to implement AI tools effectively, particularly when working with legacy systems or meeting new cybersecurity requirements.
Beyond deployment, AI solutions require ongoing maintenance, optimisation, and support, necessitating either upskilling staff or trusted technology partners.
Staff skills: Bridging the knowledge gap:
Beyond technical know-how, staff need a broader understanding of how to manage AI responsibly. This includes interpreting AI-generated insights, making strategic decisions about tool selection, and aligning AI use with organisational goals. Without these skills, associations may struggle to govern AI effectively or realise its full potential.
Therefore, utilise the ability of a trusted technology partner, and take time to upskill your staff.
Resource requirements: Overcoming financial and human constraints:
AI implementation often involves upfront investment in technology, training, or new roles. Smaller associations may find it difficult to justify this spend, while larger ones face competition for AI talent from the private sector. Human resource limitations can also delay rollout or reduce the scope of adoption.
Start allocating AI within your budgeting, including AI considerations as part of your annual budget.
Data quality and access: Ensuring AI effectiveness:
AI depends on accurate, well-structured data. Yet associations often face challenges such as fragmented systems, inconsistent data collection, or legacy databases that hinder the effectiveness of AI tools.
Before scaling AI solutions, it's essential to ensure your data is clean, relevant, and governed effectively. Strengthening data governance, improving integration, and verifying that all reference materials and legislative content are up to date will provide a solid foundation.
Privacy issues: Navigating regulatory compliance:
Using member data in AI systems introduces privacy risks and compliance obligations. Regulations like GDPR and CCPA, along with sector-specific privacy standards, demand secure data practices.
Associations must strike a balance between personalisation and protection, often requiring investment in privacy infrastructure and regular audits. Conduct relevant and regular audits, including making sure that private data is not publicly available.
Change management: Overcoming implementation resistance:
Introducing AI may alter long-standing processes, which can trigger resistance among staff or stakeholders. Concerns about job security, technology complexity, or loss of control can hinder progress.
A structured change management approach—including communication, training, and reassurance—is essential for success.
Values alignment: Maintaining ethical standards:
Associations have a duty to reflect their members’ values, which can be challenged by ethical concerns around AI, such as bias, fairness, and accountability.
Developing ethical frameworks, testing algorithms for bias, and monitoring AI use ensures technology aligns with organisational principles.
Transparency: Ensuring algorithmic accountability:
AI is often criticised for being a “black box”: producing results without clear rationale. Associations must ensure transparency in how AI systems make decisions, particularly when those decisions impact members.
This may involve choosing tools with explainable AI features or providing accessible documentation on AI logic.
Measuring ROI: Demonstrating value and impact:
Demonstrating the return on AI investments is not always straightforward. Some benefits—such as improved member satisfaction or operational efficiency—are hard to quantify. Associations need to develop measurement frameworks that combine financial outcomes with member value and engagement metrics.
These challenges are not insurmountable and acknowledging them is the first step to overcoming them. With a clear strategy, the right partnerships, and an informed approach, associations can confidently embrace AI and unlock substantial value for their members and operations.
If your organisation is already facing some of these challenges, our team can help guide your AI journey.
In the meantime, discover Upbeat Membership from Professional Advantage. This solution, designed specifically for membership-based organisations, uniquely harnesses the leading technology of Microsoft Dynamics 365 CRM to streamline the performance of all major functions in your organisation.
