I’ve spent most of my career in recruiting, helping companies figure out who they need, what those people should do, and how to build teams that can grow with the business.
One thing has always bothered me: companies are often much better at defining jobs than understanding the value inside them.
Someone gets hired. They learn the business, build relationships, develop judgment, solve problems, and accumulate years of experience.
Then technology changes.
Suddenly the conversation becomes: Can we automate this job?
With AI, that question has become even more important, and potentially much more dangerous.
I believe companies should absolutely use AI to eliminate unnecessary work and become dramatically more productive. But I don’t believe the right starting question is simply, “What jobs can AI replace?”
Not the whole job: the specific tasks inside it that a capable assistant could already carry.
The judgment, relationships, and accountability that lose their value the moment they’re handed off.
Timing matters as much as feasibility. “Eventually” is a plan; “now” is a decision.
The question almost nobody asks, and usually the one with the most upside.
That’s where Agentic Quotient came from.
AQ starts with the organization: it maps you to one of six AI maturity stages, from AQ0 to AQ5, shows the stage your work actually needs, and spells out the gap between the two.
The two halves are one story. The leadership team first agrees where the organization really stands and what AI is for, because a workforce plan built on five different pictures of the business does not hold. With that shared view, the same work can be done role by role: deciding where people are augmented, what stays human, and where people can grow into higher-value work. Aligning leaders is how the people strategy gets made once, for the whole organization, instead of team by team.
Then it looks inside roles rather than simply labeling entire jobs as “automatable” or “safe.” It shows where AI can augment people today, where automation may eventually make sense, the likely timeframe for that change, and where existing employees could evolve or be repurposed into higher-value work.
the answer will be automation.
it will be augmentation.
the biggest opportunity is giving a person the tools to become dramatically more capable.
Automatable work isn’t the same as replaceable people.
I built AQ because I believe productivity and human value can move in the same direction.
The goal isn’t to protect every job. It’s to make better decisions about work, technology, and people; and to give organizations a way to evolve their workforce instead of automatically reducing it.
We’re entering a period where AI will fundamentally change what organizations are capable of. I want AQ to help them ask better questions about what that means for their people.
The future of work shouldn’t just be about what AI can replace. It should be about what humans can become when AI changes what work is possible.
- Ben · ben@agenticquotient.com
Agentic Quotient (AQ) maps where your organization sits on the six AI maturity stages, and the gap to where it needs to be.
Disclosure. AQ’s founder also works at Dynagentic, an AI services firm. Your scores are calculated the same way for every organization, and nothing in them depends on Dynagentic.
36 Questions · 7–10 minutes. Your AQ Readiness scores, your AQ Constraint, and the gap to where you need to be. The score is free; the full report is $25. Or bring your whole leadership team.