Defining the Gray
I've been thinking a lot lately about the gray.
Part of that has come from conversations about AI. Part of it has come from thinking about my own career and trying to put words around what I've actually spent the last 15+ years doing.
I've worked in technology. I've worked in delivery. I've led teams. I've spent time thinking about operations, customers, systems, data, and organizational problems.
But I've never felt like any one of those boxes completely described the work.
The place where I've always been most comfortable is somewhere in between them.
Between the people, the systems, and the tools.
The gray.
And I think that space is about to become a lot more important.
AI Is Making Me Rethink the Work
Like a lot of people, I've been experimenting heavily with AI.
Not just asking it questions or having it write something for me.
I've been trying to figure out what happens when you actually put AI inside the way work gets done.
One small example came up recently with our delivery organization.
We have RAID logs. We have project status reports. We have Jira. We have meeting notes. We have project plans.
All good things.
But then you look at what a project manager is actually doing.
Update the RAID log.
Go into Jira.
Pull the numbers.
Update the status report.
Rewrite some of the same information that already exists somewhere else.
Prepare for the meeting.
Then probably explain all of it again in the meeting.
And I caught myself asking a pretty simple question:
Why are we doing this?
Not why are we managing risks. Of course we should.
Why are talented people spending so much time moving information between systems?
If the RAID log is being managed well and Jira tells us what's happening with delivery, shouldn't those things help create the status update?
And if AI can consume those inputs, identify patterns, draft the narrative, flag inconsistencies and help prepare the PM for the conversation...
Then maybe the PM can spend more time actually managing the project.
That's a very different conversation than, "How can AI write our status reports?"
That's the Gray
I've started seeing versions of this everywhere.
A technology problem turns out to be a process problem.
A process problem turns out to be an ownership problem.
A customer issue looks like a delivery problem until you realize the information needed to make a decision is sitting in three different systems.
Someone says, "We need another person," when what we might actually need is a better process, better tooling, or clearer accountability.
And sometimes the opposite is true.
We try to solve a people problem with another tool.
I've been guilty of that too.
The more I've thought about my career, the more I've realized that a lot of the work I'm proudest of has happened right there.
Not inside the boxes.
Between them.
Connecting a business problem to a technology solution.
Connecting executives to delivery teams.
Connecting strategy to the people who actually have to make it work on Tuesday morning.
Connecting data and systems to the relationships they're supposed to support.
That's the gray.
AI Makes the Gray More Important
There's a lot of conversation about what AI is going to replace.
I'm increasingly interested in a different question:
What becomes more valuable because AI exists?
I think judgment is one answer.
Context is another.
Curiosity might be an even bigger one.
AI can summarize a meeting incredibly well.
But someone still has to recognize the sentence in that meeting that actually matters.
AI can look at 150 Jira stories and tell you what's moving.
Someone still needs to understand why the customer is nervous.
AI can produce five recommendations before I finish my coffee.
Someone still has to say, "Yeah, but that won't work here."
That doesn't diminish AI.
That's what makes the combination powerful.
We Have to Stop Thinking in Boxes
I recently had a conversation that forced me to explain my career differently.
Instead of talking about titles or technology platforms, I found myself
talking about this idea of living in the gray.
How do technology and relationships work together?
How does better data create better engagement?
How do you take something that historically depended on institutional knowledge or individual heroics and build a system around it without losing the human part that made it work?
Different environment. Different problems.
Same gray.
And that stuck with me.
Because organizations love boxes.
Sales owns this.
Delivery owns that.
IT owns this system.
Operations owns that process.
And then the really hard problem shows up and somehow manages to sit perfectly between all four of them.
Those are usually the problems worth solving.
Don't Automate the Mess
This is probably the part of AI that interests me most.
I don't want to take every process we have today and sprinkle AI on top of it.
Some processes shouldn't be automated.
They should be questioned.
If someone is entering the same information into three places, don't give them an AI assistant that helps them enter it faster.
Ask why there are three places.
If a report takes four hours every Friday to create, don't immediately celebrate when AI gets it down to 30 minutes.
Ask what decision the report is supposed to help someone make.
Maybe AI should build the report.
Maybe the report shouldn't exist.
Maybe the human should spend those four hours talking to the team instead.
AI gives us an opportunity to rethink the work, not just accelerate it.
That's a much more interesting opportunity.
So, Define the Gray
I think we're entering a period where leaders are going to have to get much more intentional about the intersection of people, systems, and tools.
What should the system do?
What should AI do?
What should the person do?
And maybe most importantly:
Where does human judgment matter most?
Because the goal isn't to remove humans from work.
It's to remove enough friction that humans can spend more time doing the things we actually need humans to do.
Ask better questions.
Build relationships.
Challenge assumptions.
Make decisions.
Create.
Lead.
And occasionally look at something we've been doing for years and ask:
Why are we doing it this way?
I've spent a lot of my career in that space without having a great name for it.
Now I do.
Define the gray.
And here's my challenge to you:
Look around your organization and find one piece of gray.
One process everyone complains about. One handoff that never quite works. One report that takes hours to build. One place where people, systems, and tools aren't working together the way they should.
Don't start by asking how AI can fix it. Start by asking why it works that way in the first place. Then define what the human should own, what the system should handle, and where AI might help connect the two.
I'm spending a lot of my time thinking about these problems right now, and I'd love to hear what other people are seeing.
What's the gray in your organization?
Send me the messy process. The weird handoff. The “we've always done it this way” problem. I'd genuinely love to talk about it; because I have a feeling some of the most interesting opportunities in the next few years aren't going to be found inside the boxes.
They're going to be found between them.
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