About EffGap

Why EffGap exists

EffGap started with a simple question:

What happens when AI adoption moves faster than the people and organizations around it can adapt?

We talk a lot about what AI can do. Less attention is often given to the conditions that determine whether it actually improves work: leadership, learning, time, processes, trust, human judgment and the ability to adapt.

EffGap explores that space.

Rather than looking only at technological readiness, it looks at the relationship between AI adoption and the human and organizational conditions around it.

The aim is not to slow down AI adoption.

It is to understand what helps people, technology and organizations work well together.

Human Factors perspective

EffGap is influenced by Human Factors thinking — the study of how people, technology, tasks and organizations interact.

This means asking not only:

“Are people ready to use AI?”

but also:

“Is the way AI is introduced designed around how people actually work?”

As AI becomes a more active part of everyday work, Human–AI Teaming also becomes increasingly important: understanding where AI can support people, where human judgment remains essential, and how people can effectively question and verify AI-generated outputs.

Who is behind EffGap?

EffGap was created by Christopher Eff.

My background is in Human Factors & Ergonomics, Sport Science and organizational development, with experience across project management, process improvement, technology implementation, learning and change.

Over the past years, I have become increasingly interested in what happens to the human side of work as AI becomes more capable and more integrated into everyday tasks.

EffGap grew out of conversations with people from different industries about those changes.

Instead of trying to predict exactly what work will look like in the future, I wanted to start by asking better questions about what is happening now.

EffGap today

EffGap is currently a pilot.

The assessment and the Human Efficiency Profile are being developed through real responses, conversations and feedback.

The current assessment explores:

• AI Usage
• Productivity
• Leadership
• Learning
• Human Factors
• Future Readiness

Human–AI Teaming is also being explored across these areas.

The goal is to understand where AI adoption and organizational readiness move together — and where meaningful gaps begin to appear.

If you have thoughts, criticism or would like to explore EffGap in your organization, I would be happy to hear from you.