Here's a frustrating reality: Your team members are quietly achieving 2-3x productivity gains with AI, cutting tasks that used to take hours down to minutes. But when you zoom out to the organizational level? Your association might be seeing 10-20% improvement at best.
What gives?
This disconnect isn't a technology problem. It's an organizational innovation problem. And it's one that AI researcher Ethan Mollick has been studying extensively. In a recent article, Mollick introduced a powerful framework for organizational AI adoption: Leadership, Lab, and Crowd.
What follows is our exploration of how Mollick's model applies specifically to the association world—where traditional corporate innovation approaches often fall flat, and where the opportunities for transformation are uniquely compelling.
Why Traditional AI Adoption Fails in Associations
For decades, many associations have followed a familiar pattern when facing technological change: hire consultants, implement their best practices, and hope for transformation. This worked reasonably well for websites, databases, and even early digital marketing.
But AI is different. Even OpenAI and Anthropic—the companies building your favorite models—release them without knowing exactly how they'll be used in your specific context. No consultant has a magic playbook for how AI should transform member services at your association.
This uncertainty collides with what we'll refer to as the hamster wheel problem. Most associations are running at full capacity, replacing one system with another, implementing incremental improvements, planning the next annual conference. When every hour is spoken for with "necessary" work, where's the space for transformation?
The answer isn't to work harder. It's to work differently. And that's where Mollick's Leadership-Lab-Crowd framework becomes essential for associations.
Leadership: Beyond "We Should Use AI"
In Mollick's framework, leadership is the critical starting point—but not in the way you might think. The problem isn't that association executives don't recognize AI's importance. The problem is that recognizing importance doesn't create change.
Think about the last all-staff meeting where AI was discussed. Did leadership paint a vivid picture of the future, or did they use phrases like "enhance member value" and "improve operational efficiency"? Your team doesn't get out of bed excited about operational efficiency. They get excited about transformation.
Here's the difference:
Vague Leadership Vision: "We should use AI more. It will better serve our members and streamline operations."
Vivid Leadership Vision: "Imagine a new member joining our association and immediately receiving a personalized onboarding journey based on their career stage, geographic location, and learning style. Their AI assistant knows their certification deadlines, suggests relevant networking connections at our events, and creates custom learning paths that adapt in real-time. When they have questions at 2 AM, they get expert-level answers instantly, not a 'we'll get back to you in 2-3 business days' auto-reply."
See the difference? One is what you say. The other is what you see.
But painting the future is only part of leadership's role. Equally important is leading by example. When a leader shares the specific YouTube video about prompt engineering they watched last night, when they demonstrate their own ChatGPT experiments in a staff meeting, when they openly discuss what worked and what failed—that's when culture starts to shift.
The power of sharing learning resources cannot be overstated. It's not enough to say "I've been learning about AI." Share the specific podcast episode. Send the exact YouTube link. Create a Slack channel where team members post their AI discoveries. This transforms AI from an abstract directive to a shared journey.
Leadership also means making hard choices about priorities. If you're still treating AI as a side project while pouring resources into another incremental AMS upgrade, you're sending a clear message about what really matters. Sometimes leadership requires standing up and saying, "This is what we're doing. Not because it's comfortable, but because our mission demands it."
The Crowd: Your Hidden Innovation Engine
This is where Mollick's research reveals something fascinating—and deeply relevant to why associations aren't seeing organizational gains despite individual productivity wins. He found that while only 20% of workers use official company AI tools, over 40% admit to using AI privately. He calls these hidden users "secret cyborgs."
Think about what this means: Nearly half your workforce has already figured out how to dramatically improve their productivity with AI. They're achieving those 2-3x gains we mentioned at the beginning. But instead of this innovation spreading throughout your organization, it's hiding in the shadows. This is precisely why individual gains aren't translating to organizational transformation.
Why the secrecy? Mollick identifies three main fears:
Fear of job elimination: "If I show them AI can do my job in 3 hours instead of 40, will I have a job?" This fear is especially acute in associations where roles have been stable for years. Your membership coordinator who's figured out how to automate renewal campaigns with Claude isn't eager to advertise that fact if they think it means working themselves out of a job.
Fear of increased workload: "If I reveal my productivity gains, they'll just give me 3x more work." Without proper incentives, efficiency gains become punishment. Why would someone share an innovation that just means more work for the same pay?
Lack of rewards: "Why share my innovations if there's no upside for me?" When organizations treat AI adoption as an expectation rather than an achievement worth celebrating, innovation goes underground.
These fears create a vicious cycle. The very innovations that could transform your association remain hidden because the organizational culture inadvertently encourages secrecy over sharing. Breaking this cycle requires leadership to directly address these concerns—not with vague reassurances, but with concrete policies and actions.
But here's what makes associations uniquely positioned: You actually have two crowds whose innovations you're not capturing.
The Internal Crowd consists of your staff members who are already AI power users. They're not waiting for permission or training—they're figuring it out themselves. The education director using ChatGPT to create course outlines. The finance manager using AI to analyze member trends. The communications coordinator using AI to draft newsletters. Each has developed workflows that could benefit the entire organization, but those innovations remain siloed.
The External Crowd—your members—represents an even larger missed opportunity. Your architect members are using AI for design work. Your healthcare members are transforming patient communication with AI. Your manufacturing members are revolutionizing quality control. This distributed innovation across your membership base contains insights that could transform how you serve them.
The solution here is creating what Mollick calls "permission structures"—clear, defined spaces where experimentation is not just allowed but actively encouraged and rewarded. This might look like dedicating time for AI experimentation, creating forums for sharing discoveries, or establishing recognition programs for innovative AI applications. The key is moving from "don't use AI incorrectly" to "here's how and where we want you to experiment."
For leaders, addressing the secret cyborg phenomenon requires both honesty and action. If staff members have figured out how to automate 80% of their routine work, that's not a threat—it's an opportunity to redeploy human talent toward higher-value activities. But this only works if you back up words with actions. When someone shows you an AI innovation, the response can't be "great, now you can do three times as much." It needs to be "fantastic, let's figure out how you can use this freed-up time to tackle that strategic project we've been putting off."
The Lab: Not Your Traditional R&D
Labs are for companies with R&D budgets, right? For organizations with teams of data scientists?
Not exactly.
The Lab in Mollick's framework isn't a place or a department. It's a function—and it's the critical bridge between individual experiments (your Crowd) and organizational transformation. Without the Lab function, all those individual productivity gains remain just that—individual. The Lab is where you systematically turn isolated innovations into scalable solutions.
For associations, the Lab concept needs adaptation. Here's how we see it working:
1. It's Ambidextrous
The Lab isn't just dreaming about the future. It's building for today while exploring tomorrow. This dual focus is essential for moving from individual to organizational gains. You might create an AI tool that handles routine member inquiries this month (capturing immediate productivity gains) while simultaneously prototyping what fully automated certification pathways could look like next year (transforming your entire education model).
2. It's About Building, Not Analyzing
Traditional association task forces might produce reports. The Lab produces prototypes. This shift from analysis to building is crucial for organizational transformation. When your team can see and interact with a working prototype—even a rough one—it moves AI from abstract concept to concrete possibility. With today's AI tools, non-technical staff can build functional prototypes in hours, not months.
3. It Creates Custom Benchmarks
Mollick makes a brilliant point: Most AI benchmarks test things like math problems or coding challenges. But what good does that do when you need to know which AI writes the best member engagement emails for YOUR association? The Lab develops organization-specific benchmarks. Which AI understands your certification requirements best? Which one can accurately answer questions about your specific bylaws? These custom benchmarks help you move beyond random individual experiments to systematic organizational improvements.
For resource-constrained associations, the Lab doesn't require a dedicated R&D department. It can start as a three-day hackathon or idea-thon where you gather five people—including some who've never coded—and give them a provocative challenge.
Here's one that directly addresses the individual-to-organizational gap: Build a competing association that could put your organization out of business. Using AI tools, a small team can prototype what a fully automated professional development platform might look like—one that delivers your value proposition at a fraction of the current cost. This exercise forces you to think beyond incremental improvements to true transformation.
The Lab is where scattered individual innovations become coherent organizational capabilities. Without it, you're just hoping that individual gains somehow add up to organizational transformation. They won't. You need the Lab to make that leap.
Making It Work in Your Association
Here's where the rubber meets the road. You understand why individual productivity gains aren't translating to organizational transformation. You see how Leadership-Lab-Crowd can bridge that gap. But you're staring at a calendar full of "urgent" projects and a board that expects progress on the strategic plan they approved last year.
The key insight? You can't layer this framework on top of everything else you're doing. Something has to give. And that something should probably be the incremental improvements that are keeping you on the hamster wheel.
Start With Honest Priority Assessment
That AMS upgrade scheduled for next year? The one that will cost a fortune and take forever to implement for marginal productivity gains? Put it on hold. Take a fraction of that budget and time to invest in AI transformation. The ROI comparison isn't even close. One focuses on incremental improvements to existing processes; the other could fundamentally transform how you deliver value.
Pick Your Entry Point Based on Your Gaps
Look at where the individual-to-organizational disconnect is strongest in your association:
- Leadership-first: If your team is experimenting but lacks direction, start with vivid vision casting and personal example setting
- Lab-first: If you have scattered innovations but no systematic approach to scaling them, run a three-day prototype hackathon or idea-thon
- Crowd-first: If innovation is happening in secret, focus on creating permission structures and surfacing your secret cyborgs
Address the Fear Factor Head-On
The biggest barrier to organizational transformation isn't technology—it's fear. Be explicit about intentions: "We want to automate routine tasks SO THAT humans can do higher-value work, not so we can eliminate positions." Then back it up with actions. When someone shows you how AI can automate a 20-hour task, celebrate publicly and give them a new creative challenge that uses their freed-up time.
Measure Transformation, Not Just Efficiency
Traditional metrics won't capture the shift from individual to organizational gains. Instead of just tracking time saved, measure:
- Number of AI innovations moved from individual use to team-wide adoption
- Prototypes built and tested
- Member-facing innovations launched
- Strategic initiatives enabled by automation
- Cross-functional AI applications developed
Create Feedback Loops Between Elements
The real power comes when Leadership, Lab, and Crowd reinforce each other. Leadership sets vision and removes barriers. The Crowd surfaces innovations. The Lab systematizes and scales them. Leadership celebrates and promotes the wins. It's a virtuous cycle that turns individual experiments into organizational capabilities.
The Path Forward: From Individual Wins to Organizational Transformation
The Leadership-Lab-Crowd framework offers associations a model for solving the puzzle we started with: Why are your individual team members achieving 2-3x productivity gains while your organization sees only incremental improvement?
The answer is now clear. Individual gains don't automatically scale. They need:
- Leadership that paints vivid futures and creates the cultural conditions for innovation
- Systems (the Lab) that turn scattered experiments into scalable solutions
- Mechanisms for surfacing and spreading innovation from your Crowd
Without this complete system, individual gains remain isolated. With it, you can finally bridge the gap between what your people can do and what your organization is achieving.
Start with whichever element offers the clearest path forward for your association. If your team lacks direction, begin with leadership vision. If you have scattered innovations, build your Lab function. If productivity gains are hiding in the shadows, activate your Crowd.
The difference between associations that thrive with AI and those that merely survive will be their ability to transform individual capabilities into organizational ones. This framework shows you how.
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