The Rise of AI in the Workplace: Strategic Considerations for Associations
7/22/2025
ByGwen Garrison
The adoption and use of AI tools continue to accelerate across nearly every business sector. According to McKinsey’s 2024 Global Survey on AI[1], 72% of organizations now use AI tools in at least one business function. Leading areas of adoption include Marketing and Sales (for content creation and personalized marketing), Product and Service Development (to summarize research and accelerate testing), and IT (through chatbots and data management systems).
As associations consider how to integrate AI into their operations, two strategic priorities stand out
1. Internal Policies and Ethical Use Guidelines General-purpose AI tools like Google Gemini and Microsoft Co-Pilot are now embedded in search engines and browsers, enabling users to submit prompts in natural language. The responses are typically summaries, informed by a vast pool of previous user inputs. Both Google and Microsoft capture this activity to further train their AI models. The challenge: most employees may be unaware that proprietary or sensitive data submitted to these tools could become part of a broader digital training set. To address this, associations urgently need to:
- Develop organizational AI use policies - Implement association-specific AI tools (e.g., private instances of ChatGPT that don’t feed public training data) - Offer employee training, both in-person and on-demand, to build awareness, encourage appropriate use, and foster a responsible AI culture.
2. Data Quality and Employee Readiness As AI use becomes more common, employees are increasingly experimenting with its capabilities. Many manage important data (e.g., event registrations, member sales, marketing lists) in decentralized spreadsheets, often outside of core association management systems (AMS).
AI tools can analyze these spreadsheets, but outputs are only as good as the data provided. If staff are unaware of data quality issues or best practices for preparation, AI may return biased or misleading insights—reinforcing what users expect rather than what is accurate. This can weaken decision-making and even lead to public-facing errors. Training staff on data hygiene and spreadsheet readiness is now a prerequisite for effective AI use.
In Conclusion The AI revolution is no longer on the horizon—it’s here. As association leaders, we must proactively guide our teams in both formal and informal AI use. This means crafting thoughtful policies, investing in training, and equipping our organizations with the tools to use AI responsibly and effectively.
[1] Singla, A. Sukharevsky, Yee, L, and Chui, M. (2024) The state of AI in early 2024: Gen AI adoption spikes and starts to generate value from QuantumBlack AI, McKinsey and McKinsey Digital. McKinsey & Company https://www.mckinsey.com/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/the-state-of-ai-in-early-2024-final.pdf
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