The past few years have shown that AI goes beyond a short-lived novelty and is sticking around. However, as recently discussed on the Sidecar Sync podcast, many associations face significant hurdles when it comes to adopting AI. The following guide comprehensively addresses six common obstacles and provides practical strategies for association leaders to overcome them, thus paving the way for successful AI integration.
Obstacle 1: Time Constraints
One of the most common objections to AI adoption is a lack of time. Many association professionals feel overwhelmed by their current workload and view AI as another task on their already full plate. However, this perspective overlooks AI's potential to save time in the long run.
Strategies to overcome time constraints:
- Recognize the urgency: Understand that AI adoption is not optional—it's essential for future success. The time invested now will pay dividends in increased efficiency and innovation later.
Action step: Schedule a leadership meeting to discuss the potential impact of AI on your association's future. Use this to build consensus on the urgency of adoption.
- Prioritize AI learning: Dedicate specific time slots for AI education and experimentation.
Action step: Implement a "Learning Friday" where team members spend the last hour of the workday exploring AI tools or taking online courses.
- Create a "stop doing" list: Identify tasks that can be eliminated or automated to free up time for AI initiatives.
Action step: Conduct a team-wide audit of current tasks. For each task, ask: "Is this essential? Can it be automated? Can it be delegated?" Create a plan to phase out or automate non-essential tasks.
- Start small: Begin with manageable AI projects that can demonstrate quick wins and time savings.
Action step: Identify one repetitive task in each department that could be automated with AI. Implement these automations and track the time saved.
- Leverage existing resources: Many associations already have AI capabilities built into their current software. Take advantage of these before investing in new tools.
Action step: Review your current tech stack for AI features. Many AMS, CRM, and marketing automation platforms now include AI capabilities.
Remember, the time invested in AI now will yield significant returns in efficiency and innovation later.
Obstacle 2: Lack of AI Policies and Guidelines
Many associations hesitate to adopt AI due to the absence of clear policies and guidelines. While it's important to have governance in place, waiting for perfect policies before getting started can significantly delay progress.
Addressing the policy gap:
- Develop initial, flexible guidelines: Start with basic rules that can evolve as your AI usage matures.
Action step: Draft a one-page AI usage guideline covering basic principles like data privacy, ethical use, and transparency. Make it clear that this is version 1.0 and will be updated regularly.
- Focus on key concerns: Address data privacy, ethical use, and security in your initial policies.
Action step: Consult with your legal team or an external expert to ensure your initial guidelines cover critical legal and ethical considerations.
- Plan for regular reviews: Set a schedule to revisit and update your AI policies as you gain more experience.
Action step: Schedule quarterly policy review meetings. Involve team members who are actively using AI to get their input on necessary updates.
- Create a sandbox environment: Designate a 'safe space' for AI experimentation that doesn't involve sensitive data or high-stakes decisions.
Action step: Set up a separate AI testing environment with non-sensitive data. Encourage team members to experiment freely in this space.
- Communicate clearly: Ensure all team members understand the current guidelines and the process for suggesting changes.
Action step: Hold a town hall meeting to introduce the AI guidelines. Create an easily accessible document (e.g., a wiki page) where team members can review guidelines and suggest changes.
Obstacle 3: Resistance to AI Training Without Policies
Some team members may resist AI training, arguing that policies should be in place first. This creates a catch-22 situation where experience is needed to create effective policies, but policies are seen as a prerequisite for gaining experience.
Breaking the deadlock:
- Implement a phased approach: Begin with basic training and simple use cases, developing policies in parallel.
Action step: Start with a 'Lunch and Learn' series on AI basics. As team members become more comfortable, gradually introduce more advanced training.
- Set clear expectations: Communicate that policies will evolve based on practical experience and learning.
Action step: Create a roadmap that shows the parallel tracks of AI adoption and policy development. Share this with the team to illustrate how both will progress together.
- Start with low-risk applications: Choose AI projects with minimal sensitive data to build confidence and experience.
Action step: Identify three low-risk AI projects (e.g., using AI for content ideation or basic data analysis). Implement these as pilot projects.
- Encourage feedback: Create channels for team members to share their experiences and concerns as they start using AI.
Action step: Set up a dedicated Slack channel or regular check-in meetings for AI users to share insights and raise concerns.
- Provide context: Help team members understand how other associations and industries are approaching AI adoption.
Action step: Share case studies or invite guest speakers from associations successfully using AI to share their experiences.
Obstacle 4: Mixed Feelings About AI Within Teams
It's common for teams to have diverse opinions about AI, ranging from enthusiasm to skepticism or even fear. This mix of attitudes can create friction and slow down adoption efforts.
Leading teams with diverse opinions:
- Address concerns openly: Create forums for team members to express their thoughts and ask questions about AI.
Action step: Hold a series of "AI Town Halls" where team members can voice concerns and ask questions in a safe environment.
- Provide education: Offer resources to help team members understand AI's potential and limitations.
Action step: Create an "AI Resource Library" with curated articles, videos, and courses. Allocate time for team members to use these resources.
- Lead decisively: While it's important to listen to concerns, be prepared to make firm decisions about moving forward with AI initiatives
Action step: After gathering input, clearly communicate the association's AI strategy and the rationale behind it. Be transparent about the decision-making process.
- Showcase success stories: Highlight how AI is already benefiting the association or similar organizations.
Action step: Create a monthly "AI Win" newsletter highlighting successful AI implementations within your association or peer organizations.
- Address job security concerns: Be clear about how AI will augment rather than replace human roles.
Action step: Develop and communicate a plan for how AI will be integrated into existing roles, emphasizing skill development and new opportunities.
Obstacle 5: Hesitation to Invest in Paid AI Tools
Many associations experiment with free AI tools but hesitate to invest in paid versions. This can limit the benefits and potentially expose the organization to risks.
Making the case for paid AI tools:
- Highlight the limitations of free tools: Discuss data privacy concerns and feature restrictions.
Action step: Create a comparison chart showing the features and limitations of free vs. paid versions of key AI tools.
- Emphasize the benefits of paid versions: Better data protection, advanced features, and organizational control.
Action step: Conduct a pilot project using both free and paid versions of an AI tool. Document the differences in results and user experience.
- Consider team or enterprise subscriptions: These often provide better value and more robust management features.
Action step: Calculate the potential ROI of a team subscription, factoring in time saved and new capabilities gained.
- Address budget concerns: Look for ways to reallocate existing resources to fund AI tools.
Action step: Review current software subscriptions. Identify any that could be replaced or consolidated with AI-powered alternatives.
- Start small and scale: Begin with a limited paid subscription and expand as you demonstrate value.
Action step: Propose a 3-month trial of a paid AI tool for a specific team or project. Set clear KPIs to measure its impact.
Obstacle 6: Uncertainty About Next Steps After Initial Experimentation
After initial AI experiments, many associations struggle to determine their next steps. This uncertainty can stall momentum and prevent deeper integration of AI into operations.
Moving from experimentation to integration:
- Invest in structured learning: Encourage team members to take courses, attend webinars, or read books on AI applications in associations.
Action step: Allocate a specific budget for AI education. Offer incentives for team members who complete AI certifications or courses.
- Set clear goals: Identify specific areas where AI can add value to your association and set measurable objectives.
Action step: Conduct an "AI Opportunity Workshop" where teams brainstorm potential AI applications. Prioritize ideas based on potential impact and feasibility.
- Encourage practical application: Create opportunities for team members to apply AI tools to real-world association challenges.
Action step: Launch an "AI Challenge" program where teams compete to solve a specific association problem using AI tools.
- Develop an AI roadmap: Create a clear plan for AI integration across different departments and functions.
Action step: Work with department heads to create a 12-month AI integration plan for each area of the association.
- Foster a culture of continuous learning and adaptation: Encourage experimentation and learning from both successes and failures.
Action step: Implement a "fail fast" policy for AI projects, emphasizing quick iterations and learning from unsuccessful attempts.
Conclusion
Adopting AI in your association doesn't have to be an insurmountable challenge. By addressing these common obstacles head-on, you can pave the way for successful AI integration. The key is to start now. Take the first step today—whether it's scheduling time for AI learning, drafting initial guidelines, or investing in a paid AI tool. Learn continuously and be willing to adapt as you go. The associations that embrace AI today will be better positioned to serve their members and fulfill their missions in the future.
Looking to take that first step but not wanting to spend any money? Look no further than Ascend 2nd Edition, your guide to all things AI in associations. Available for FREE download here.
.svg)
