As organizations build their AI strategies, I keep hearing a version of the same plan:
“We’ll use AI to handle the low-hanging fruit, the simple questions, so our staff can focus on the more complex calls.”
It makes perfect sense. Until you think about what that actually means for the person answering the next call.
A recent ICMI article, “AI Took the Easy Calls. Now Your Best Agents Are Leaving,” raises an important issue that I don't think is getting nearly enough attention. When AI takes away the simple interactions, it doesn't just reduce call volume. It changes the work that remains.
Those quick calls asking for basic information, hours, eligibility requirements, or a simple referral may seem like the obvious interactions to automate. And in many cases, they are.
But those calls also provide something we rarely measure: a mental reset.
A relatively simple interaction between two difficult ones gives a Community Navigator a moment to breathe, regroup and prepare for whatever comes next.
Now imagine taking those interactions away.
Instead of handling a mix of simple, moderate and complex calls throughout the day, staff may increasingly move from one complicated situation directly into another.
*Housing crisis.
*Food insecurity.
*Caregiver exhaustion.
*Mental health concerns.
*Transportation barriers.
Someone who doesn't know where else to turn. Then the phone rings again. That is a very different job.
Efficiency Cannot Be the Only Measure
I am a strong believer in the potential of AI in Community Navigation. Used well, it can improve access, strengthen our workforce and help people find information faster.
But our AI strategy cannot simply be:
Automate the easy work and give humans everything that's left.
Because what is left may be the most emotionally demanding work we do.
The ICMI article points out that traditional workforce planning can compound the problem. If automation lowers call volume, organizations may assume they need fewer staff. But lower volume doesn't necessarily mean lower workload when the remaining interactions require more time, judgment, empathy and problem-solving.
That's especially important in Community Navigation.
A ten-minute conversation that helps someone navigate multiple systems, understand their options and leave with a real path forward isn't inefficient, that's the work.
Burnout Needs to Be Part of the AI Strategy
Employee burnout is already real in our field.
Community Navigators spend their days helping people through situations that can be incredibly difficult. We ask them to listen, problem-solve, de-escalate, research, empathize and remain present, sometimes call after call after call.
If AI removes many of the easier interactions, we have to recognize that we're changing the emotional makeup of their workday.
That means organizations implementing AI should be asking more than:
How many calls can we automate?
We should also be asking:
- What will the average human interaction look like after automation?
- Are our staffing and occupancy expectations still realistic?
- Do employees have enough recovery time between difficult interactions?
- Are we measuring complexity, not just volume and handle time?
- Are we investing some of the efficiencies created by AI back into the people doing the hardest work?
- Most importantly, are our Community Navigators part of the conversation as we design the strategy?
The Human Side of AI
The future of Community Navigation will absolutely include AI.
But I don't believe the goal should be to remove humans from the process. The goal should be to use technology in ways that allow people to do what people do best.
Listen. Understand context. Build trust. Exercise judgment. Show empathy. Help someone see a path forward when the answer isn't simple.
AI may be very good at handling the easy calls.
Our responsibility as leaders is making sure we don't make every human call a hard one.
That needs to be part of the AI strategy, too.
Inspired by Natalie Perez's ICMI article, “AI Took the Easy Calls. Now Your Best Agents Are Leaving.”
Read the ICMI article