Navigating 5 Common Anxieties Around AI

2. Cost overruns and unclear ROI

AI use and pilot projects can spiral in cost, especially when organizations underestimate infrastructure, training, or integration needs. And we’re seeing AI companies scramble to raise prices to recoup startup costs. This makes it difficult for executives to predict budgets or returns, leading to stalled AI initiatives.

Start small and start free (or free-ish). Try to maximize any AI capabilities built into platforms you already pay for, such as Microsoft Copilot or Google Gemini. These platforms have plenty of free, high-quality training videos. Maximizing your built-in tools builds proficiency and gives you a clearer idea of how to translate internal efficiencies into audience value.

3. Job displacement and workforce anxiety

A common concern is that AI might make roles obsolete or diminish upward mobility. This goes for folks up and down the organizational chart. Junior-level employees worry that their production will be replaced by senior-level employees entering prompts into a tool. Middle management is worried their oversight will be replaced by some sort of AI dashboard. Senior leaders worry that a failure to adopt AI across the organization is a failure to compete.

But if you take away all the industry hype and headlines—bombastic tweets, the cottage industry of AI courses with ambitious promises, mass layoffs of programmers—the reality is much more grounded. The best use cases require thoughtful human intervention. AI tools on their own can’t solve problems, let alone define problems. And those mass tech layoffs being attributed to AI? Evidence suggests it’s a smokescreen for run-of-the-mill business pressures like stakeholder value and a tenuous economy.

Encourage your teams to view AI as an assistant.

4. Reputation and customer risk

Nobody wants their brand to be the next viral AI-fail. Between tone-deaf chatbots, biased algorithms, and lifeless content, a single AI snafu can erode years of customer trust in the blink of an eye.

All of these scenarios hinge on the quality of your organization’s review process. If your teams use AI to generate content, reports, or data, then strong AI governance guidelines can mitigate these risks. Make sure your guidelines include thorough human review for accuracy, bias, and brand alignment. Most importantly, get a clear, honest assessment of where and how AI is currently being used in your organization. You don’t want to find out down the road that an overly ambitious team member is taking big, risky swings on use cases that can lead to disaster.

5. Data security and privacy risks

The most powerful enterprise-level AI integrations rely on your organization’s own data. Enrollment data. Membership data. Donor data. That often means personally identifying information, bank accounts, trade secrets. This raises concerns about data leakage, unauthorized access, and privacy violations.

This adds a new layer of security and privacy risks. To mitigate these risks, minimize the amount of data you feed the tools. Carefully assign roles and permissions. Train your teams on safe prompting. AI can be a powerful tool for segmentation, personalization, campaign planning, and marketing metric analysis. Use it wisely and use it carefully.

Why these fears matter for strategy

These anxieties aren’t just psychological. They have real strategic implications. AI anxiety can reduce job satisfaction, weaken organizational commitment, and slow innovation. Without clear guidance, teams may either avoid using AI altogether (missing efficiency gains) or use it irresponsibly (creating compliance or security risks).

For mission-driven organizations—where trust, brand voice, and stakeholder relationships are crucial—these fears can shape decisions about whether to integrate AI into marketing, content creation, and member engagement workflows.

So it’s not just a question about how you work, but who you are as an organization.

How we’ve addressed our own anxieties

Our agency has been deliberate with our adoption of AI. As a people-first organization, we started our AI journey with an assessment of our team’s attitudes about the technology. We wanted to see where everyone stood and how everyone was feeling. Periodic check-ins keep our finger on the pulse to track how attitudes change.

From there, we established a committee to draft an AI policy (internal-facing, more technical and tactical) and AI philosophy (external-facing, capturing our approach and ethos).

We also created a chat space where our whole team shares use cases, tips, and relevant news articles related to AI—the good and the bad. This helps us keep the conversation going about where we stand on AI as an agency.

Now, we have regular show-and-tells, pilot projects, an AI council, and “open office” hours where our AI-curious team members can get guidance from our AI power-users. To date, we’ve developed custom apps that support project management, time tracking, budgeting, proposals, and smaller task-based processes.

But the most important component of our AI adoption is that it remains driven by curiosity, collaboration, and candor. Experimentation is OK. We see it as an investment. And even a dead end gives us more clarity about pitfalls and how we can advise clients.

Still feeling anxious about AI?

We get it. Identifying and defining your anxieties can sometimes make you feel even more anxious. It’s a lot to think about, and there are no clear answers. And what works for one organization may not work for another.

Whether you want a sympathetic ear or some guidance on creating an organization-wide AI strategy, reach out!