Many association executives view artificial intelligence as a technical challenge to be solved by the IT department or a specialized task force. They see it as a line item in the budget or a new software suite to be vetted. However, you don't need to be a tech expert to lead through AI; this perspective overlooks the most critical element of the technology: its impact on the people who make the organization run. When we treat AI as a mere technical experiment rather than a core leadership duty, we miss the opportunity to prepare our teams for a future that is already arriving. The reality is that AI adoption is not about the tools themselves; it is about the stewardship of the professionals within our organizations. Leading an association through this transition requires a shift in how we define our responsibilities to our staff and how we manage the inherent risks of innovation.
The ethical case against leadership malpractice
There is a strong argument to be made that failing to push AI as a critical component of professional development is a form of leadership malpractice. As leaders, our primary responsibility is to our people. We are tasked with preparing them to be successful not only within our current organization but in the future of their careers, wherever that may lead. In a professional environment where AI is becoming a standard expectation for almost every role, a leader who ignores this reality is leaving their staff vulnerable. If a staff member leaves your association in three or five years and does not have the skills to navigate an AI-driven workplace, you have failed in your duty of care as a mentor and executive.
This perspective is deeply rooted in the culture at the American Society of Landscape Architects (ASLA). Torey Carter-Conneen, the CEO of ASLA, views the organization’s internal AI training not just as a way to improve efficiency, but as a way to empower his team. He recognizes that for most employees, their current role will not be their last. By providing them with tiered training—ranging from basic 100-level introductory courses to advanced 300-level applications—he is ensuring they can distinguish themselves in the job market. This is a selfless approach to leadership. It acknowledges that while we want our best talent to stay, we also want them to be prepared for what comes next. When you invest in your people’s future, they are more likely to give their best to the organization in the present.
Professional development in AI should not be optional. When training is merely encouraged, it often reaches only the early adopters—those who are already curious and tech-savvy. The people who most need the skills, perhaps because their roles are more routine or susceptible to automation, are often the ones who hesitate. By making AI training a standard part of the professional journey, leaders remove the intimidation factor. It signals that the organization is moving forward together and that no one will be left behind. This builds a culture of trust rather than one of fear. Staff members begin to see AI not as a threat to their job security, but as a tool that makes them more effective and more marketable professionals.
Applying standard risk management to new technology
One of the most common reasons association leaders hesitate to adopt AI is a perceived sense of risk. There are concerns about data privacy, the accuracy of outputs, and the ethical implications of automated decision-making. These are valid concerns, but they are often treated differently than other business risks. When an association considers signing a high-stakes advocacy letter or moving its annual conference to a new city, the leadership goes through a standard risk assessment. They weigh the potential benefits against the possible downsides, consult stakeholders, and make a calculated decision. However, when it comes to AI, many leaders freeze. They wait for a level of perfection and certainty that they do not demand from any other part of their operations.
This double standard is a barrier to progress. To move forward, leaders must apply the same logic model to AI that they use for every other strategic decision. For instance, if you are considering using an AI agent to respond to member inquiries, you must ask: What is the risk of a wrong answer from the AI versus the risk of a human error or a delayed response? In many cases, the risk of inaction—the "absence of motion"—is greater than the risk of a controlled experiment. At ASLA, this meant allowing AI to handle specific member inquiries and generate chapter reports. The team did not wait for the technology to be flawless; they built a system where the AI produces the report, and the staff performs a quick review before it is released. This is a measured, managed risk that results in hours of saved time every month.
Transparency is the key to managing this risk effectively. Leaders should be open with their boards and their staff about what they are testing and why. Instead of hiding behind technical jargon, explain the logic. If the organization is using AI to personalize renewal communications based on a member’s specific history—such as their participation in an advocacy day or their committee work—explain the benefit of that deeper connection. When you frame AI as a way to deliver better service and free up staff for high-value work, the risk becomes easier to justify. You are not taking risks for the sake of novelty; you are taking them to fulfill the organization’s mission more effectively.
Cultivating a culture of curiosity and candor
Successful AI adoption requires more than just a training program; it requires a specific type of organizational culture. This culture is built on two primary traits: curiosity and candor. Leaders must create an environment where staff feel safe to experiment, fail, and share their findings. Carter-Conneen describes this as opening the "drawer of ideas." Most organizations have a drawer full of projects that were once deemed too difficult, too expensive, or too time-consuming. AI often makes those ideas possible, particularly through the use of AI agents. By encouraging staff to revisit those old concepts through the lens of new technology, leaders can spark a sense of entrepreneurial spirit within the association.
Hiring for these traits is just as important as cultivating them in existing staff. When interviewing new candidates, the focus should shift from purely technical skills to a candidate’s willingness to learn and their honesty about what they do not know. A candidate who can admit they don't have an answer but explains how they would go about finding it is often more valuable in an AI-driven world than one with a static set of skills. At ASLA, the final interview for every new hire is with the CEO, specifically to ensure that the candidate fits this culture of collaboration and innovation. It is a way to protect the organization’s most valuable asset: its mindset.
This culture is reinforced through regular, internal storytelling. Instead of bringing in external consultants who might use intimidating language, look to the early adopters within your own team. When a colleague demonstrates how they used AI to turn a five-hour task into a thirty-minute one, it carries more weight than any keynote speech. It makes the technology feel accessible and practical. At ASLA, staff members volunteer each month to present case studies on how they are using AI in their daily work. This peer-to-peer learning builds momentum and shifts the focus from the technology to the value it creates for the members and the staff alike.
The long-term ROI of prepared leadership
Ultimately, the return on investment for AI is not just found in saved hours or reduced costs. The true ROI is the increased capacity of the organization to serve its members. When staff are no longer bogged down by repetitive data entry or manual reporting, they have the mental bandwidth to understand what members actually need. They can spend more time on the phone with chapter leaders, more time developing high-quality educational content, and more time advocating for the profession. This is how an association moves from being an episodic partner in a member’s life to being an essential, daily resource.
Leadership in the age of AI is about stewardship. It is about recognizing that the world is changing and ensuring that your organization and your people are prepared to thrive in that new reality. It requires the courage to take calculated risks, the humility to learn alongside your team, and the vision to see AI as a tool for human empowerment. By treating AI professional development as a core responsibility, you are not just implementing a new technology; you are building a more resilient, more capable, and more valuable organization for the decades to come. The associations that succeed will be those led by executives who refused to freeze in the face of change and instead chose to lead their people toward the future.