Do you remember when a computer beat two Jeopardy! champions in a head-to-head match? It was entertaining television at the time, but years later, as artificial intelligence (AI) has moved into everyday work, what followed that moment offers a cautionary lesson about the hidden costs of poorly integrated AI. A lesson that’s especially relevant to association leaders.
Here’s what happened. It was 2011 and two show champions took on IBM’s supercomputer Watson in a two-day Jeopardy! match, and the computer won. The challenge highlighted Watson’s capabilities and proved to be great publicity for IBM’s aspirations for the technology.
IBM planned to use Watson to help oncologists diagnose cancer, care for cancer patients, provide insight to pharmaceutical companies for drug development and match patients with clinical trials. The company spent billions of dollars during the next several years to make the promise a reality, but Watson never quite delivered. By 2020, IBM had essentially dismantled Watson and sold it for parts.
As reported in Slate, IBM’s senior leadership believed that Watson’s success on Jeopardy! could translate quickly into enterprise-scale healthcare AI. However, they underestimated several critical issues. Clinical data was fragmented, unstructured and inconsistent across hospitals, and medical decisions required a deeper clinical context than AI could “learn” quickly from papers and guidelines. In addition, physicians wanted AI recommendations that fit seamlessly into existing clinical processes. Oncologists deal with life and death, and adoption requires trust, training and cultural buy-in, not just new technology.
Association leaders face similar challenges as they plan AI adoption in their own organizations. Although the financial stakes may be lower than in large corporations, the costs are very real when implementation doesn’t go well and results in:
- Lost revenue
- Reputational damage
- Wasted staff time
- Eroded trust in reporting
[Related: AI Without Leadership Is Just Hype – Why Vision Matters More Than Tech]
5 Hidden Costs Leaders Commonly Underestimate in AI Planning
Let’s take a look at five AI planning costs that may take you by surprise.
1. It Takes Time to Align People (Even With Great Technology)
Leaders might assume that once they pick a tool, adoption will follow easily and quickly.
For example, they might roll out ChatGPT licenses for everyone, thinking the tool is self-explanatory. But many staff members may continue to use their personal accounts, while others might avoid AI altogether due to fear of “doing it wrong.”
The result is that staff members are unsure when to use AI. Or, departments use their own tools independently and encourage their teams to use the department’s tech instead of the tools chosen for the entire organization.
What leaders see is inconsistent outputs and mixed results. AI initiatives stall when people don’t understand why, when or how to use them. Alignment often takes longer than tool selection.
[Related: Launch Smart – A Practical Guide to Starting AI Projects in Associations]
2. Governance Work Is Necessary Before AI Use Scales
AI tools are designed to be intuitive, and the risks aren’t always immediately apparent.
For example, staff members may not initially understand that uploading member data into a free AI tool exposes personal details to the entire AI ecosphere, but it’s a real threat. Developing appropriate governance early is the best remedy to protect members.
Instead, leaders often want to observe how teams use the new technology before they create policies. Unfortunately, AI is often used informally, before it’s sanctioned by the association, resulting in inconsistent data sharing. By the time leadership responds, usage can be widespread, leaving the organization exposed without clear guardrails in place.
AI governance isn’t optional once usage begins — it’s foundational. Delaying it increases compliance, security and reputational risks.
[Related: 5 AI Pitfalls Associations Should Avoid (And How to Get It Right)]
3. Change Management Efforts Are Required (Even for ‘Simple’ Tools)
Two things are true: change must be managed, regardless of its complexity, and people resist change unless they see a benefit to themselves.
Without proactive change management, staff members often quietly revert to old workflows such as spreadsheets and private databases. With AI tools, drafts can feel unfinished or unfamiliar, which slows adoption.
It’s easy to believe that because AI tools are intuitive, training won’t be a big lift. Instead, staff members can feel overwhelmed by new expectations, productivity can dip before it improves, and resistance can show up as avoidance, rather than as complaints.
AI changes how work gets done, not just what tools are used. That requires intentional communication, reassurance and training.
[Related: Preparing for a Technology Transition: A Change Management Playbook for Associations]
4. Data Readiness and Quality
It’s tempting to expect miracles from AI when it comes to analyzing an association’s data. One of the promises of AI analysis, for example, is the ability to understand topics like member engagement.
Before applying analytics, however, the data must be current and complete and have consistent tagging, among other things.
Instead, AI data tools often reflect existing data gaps and inconsistencies. AI amplifies what already exists, good or bad. Poor data quality leads to poor outcomes, no matter how advanced the tool. Flaws can produce unreliable or misleading outputs and ultimately erode confidence in the AI tool.
[Related: How AI Marketing Tools Could Benefit Your Association’s Strategies]
5. The Ongoing Nature of AI Readiness
Don’t fall into the “one and done” trap. The job continues after the initial introduction of AI tools. AI readiness is not a one-time project — it’s an ongoing capability.
The reason? Tools evolve rapidly, and policies need regular updating to keep pace. Changes require management, and as staff skills grow, they bring new benefits and challenges to the entire organization.
[Related: Why AI Readiness Should Be Your First 2026 Priority]
The Hidden Costs Your Association May Encounter in Year 1
Here are the top costs you may encounter in your first year:
- Lost staff time from trial-and-error experimentation without clear guidance or standards
- Duplicate tool spend when departments independently test overlapping AI solutions
- Productivity temporarily declines as teams adjust workflows and rebuild trust in AI-assisted outputs
- Rework and inconsistency caused by unclear prompts, data quality issues or lack of shared best practices
- Unplanned training needs once skill gaps and confidence issues surface
- Compliance and risk exposure from informal AI use before policies and governance are in place
- Change fatigue when AI is introduced without clear purpose or prioritization
- Delayed ROI because success metrics were never clearly defined upfront
[Related: Turn Your 2026 Technology Planning Into a To-Do List]
How to Eliminate Hidden Costs In AI Adoption
Our best advice about managing the hidden costs of implementing AI in your association is to approach it as you would any major change, while addressing its specific challenges. Dennison & Associates offers a number of resources and blogs on our website to help you plan the change you want to see. Try these:
- Will Your Next Tech Implementation Be a Success or a Struggle?
- The Hidden Costs of Poor Technology Integrations
- Aligning Technology With Organizational Goals Beyond the IT Department
Get Professional Help
Dennison & Associates is here to help you navigate your AI use in all capacities. Our AI Ready Program covers everything from training and policy development to implementation and future planning. Contact us today to learn more.