Journal

Systems Before Tools: Why Most Agents Fail at AI

The Pattern I Keep Seeing

Every real estate agent I’ve interviewed in my research at RE/MAX Camosun has told me some version of the same story:

“I signed up for [tool]. Used it for two weeks. Now I’m paying for it but I don’t touch it.”

After 10+ semi-structured interviews and a 27-question survey, I’ve identified the root cause. It’s not that agents are bad at technology. It’s that they’re adopting tools without systems.

What “Systems Before Tools” Means

Most technology adoption follows this sequence:

  1. See a shiny new tool
  2. Sign up for a free trial
  3. Try to figure out where it fits
  4. Get frustrated when it doesn’t fit anywhere
  5. Abandon it

The sequence should be:

  1. Document your current workflow
  2. Identify where things break down
  3. Design the ideal process
  4. Select a tool that fits the designed process
  5. Implement with training and support

This is the “Systems Before Tools” framework. It sounds obvious. Almost nobody does it.

What the Research Shows

My survey instrument measures five dimensions of technostress, adapted from Tarafdar et al.’s framework:

Techno-overload: “I am forced by technology to work much faster.” Agents using 5+ tools without integration scored significantly higher on this dimension.

Techno-complexity: “I need a long time to understand and use new technologies.” This was the strongest predictor of tool abandonment.

Techno-insecurity: “I feel threatened by coworkers with newer technology skills.” In a commission-based environment, this is amplified.

Techno-invasion: “I feel my personal life is being invaded by technology.” Real estate agents already work irregular hours.

Techno-uncertainty: “There are always new developments in technology.” The pace of AI change is genuinely unprecedented.

The Framework in Practice

When I designed the AI workshop series for RE/MAX agents, I structured it around the Systems Before Tools framework:

Session 1 was not about AI at all. It was about documenting existing workflows. Agents mapped out how they currently handle: lead intake, follow-up, listing preparation, market analysis, and client communication.

Session 2 was about identifying decision points and bottlenecks. Where in the workflow does a human judgment call add the most value? Where is a human just copying data from one place to another?

Session 3 — only then — introduced specific AI tools. And because agents already had documented workflows with identified bottlenecks, they could immediately see where each tool fit.

Session 4 was about building sustainable habits. Setting up the tool in their actual workflow, creating templates, and establishing a 2-week practice period with support.

Key Takeaways

  1. Technology adoption failure is usually a systems problem, not a technology problem.
  2. Technostress is measurable and addressable.
  3. Training without context is theater.
  4. The “Systems Before Tools” framework reduces adoption friction.
  5. AI is not the hard part. The hard part is getting humans to change how they work.