I Think You Can Buy Capability, But You Have to Earn Commitment
Hi all 👋
I spent some time last week talking about the human side of technology deployment, specifically why a tool doesn’t deploy itself. I sat with Ben Seligson on the Energy Trade Show podcast to talk about how easy it is to focus entirely on the software, even as the actual bottleneck is almost always the processes you are dropping it into.
What's Happening in AI
AI can dramatically expand an organization's ability to deliver.
I completely agree with that. I think we all do. Using Claude or any other AI might speed up the output, but that doesn't mean people suddenly become less important. If anything, I think the opposite is true.
Technology doesn't deploy itself. It still needs people who are willing to adopt it, understand it, and build it into the way work actually gets done.
You can buy the software, but you still have to earn that trust and commitment.
That's why I think more people are going to lose opportunities to the operators who know how to work alongside AI than to the technology itself.
The episode with Ben is dropping soon, but for now, you can watch a clip here.
This Week's Case Study
You see this exact same reality when you look at legacy operations.
We recently looked at an accounts payable setup where the team was spending most of their day just preparing to do their jobs. They were manually cleaning email subject lines, matching extracted data, and managing exceptions before the actual work could even begin.
If a process requires manual cleanup before it can even start, you don't have a workflow. You have a bottleneck. Period. In many cases, that’s your first candidate for automation and/or AI deployment. But read on for a fantastic resource on that.
The goal of bringing technology into a setup like this isn't to replace the team. It is to remove the robotic transcription work they shouldn't have been doing in the first place.
When you finally strip away those manual layers, the result isn't just speed. It's accuracy. By redesigning how data moved through the system, data errors dropped by around 70%.
I broke down why the real goal of automation in a setup like this is never about replacing the team.
→ Read the takeaway here.
A Useful Resource
One question I get quite often is: "How do I know if a process is actually worth automating?"
That's why we built the Administrative Tax Calculator. It shows you how much you're paying premium salaries to do low-value work, chasing updates, manual entry, bridging gaps between systems. Before you hire another person, see how much you're already losing to broken processes.
That's it for this week.
— Robbie
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Hi all 👋
I spent some time last week talking about the human side of technology deployment, specifically why a tool doesn’t deploy itself. I sat with Ben Seligson on the Energy Trade Show podcast to talk about how easy it is to focus entirely on the software, even as the actual bottleneck is almost always the processes you are dropping it into.
What's Happening in AI
AI can dramatically expand an organization's ability to deliver.
I completely agree with that. I think we all do. Using Claude or any other AI might speed up the output, but that doesn't mean people suddenly become less important. If anything, I think the opposite is true.
Technology doesn't deploy itself. It still needs people who are willing to adopt it, understand it, and build it into the way work actually gets done.
You can buy the software, but you still have to earn that trust and commitment.
That's why I think more people are going to lose opportunities to the operators who know how to work alongside AI than to the technology itself.
The episode with Ben is dropping soon, but for now, you can watch a clip here.
This Week's Case Study
You see this exact same reality when you look at legacy operations.
We recently looked at an accounts payable setup where the team was spending most of their day just preparing to do their jobs. They were manually cleaning email subject lines, matching extracted data, and managing exceptions before the actual work could even begin.
If a process requires manual cleanup before it can even start, you don't have a workflow. You have a bottleneck. Period. In many cases, that’s your first candidate for automation and/or AI deployment. But read on for a fantastic resource on that.
The goal of bringing technology into a setup like this isn't to replace the team. It is to remove the robotic transcription work they shouldn't have been doing in the first place.
When you finally strip away those manual layers, the result isn't just speed. It's accuracy. By redesigning how data moved through the system, data errors dropped by around 70%.
I broke down why the real goal of automation in a setup like this is never about replacing the team.
→ Read the takeaway here.
A Useful Resource
One question I get quite often is: "How do I know if a process is actually worth automating?"
That's why we built the Administrative Tax Calculator. It shows you how much you're paying premium salaries to do low-value work, chasing updates, manual entry, bridging gaps between systems. Before you hire another person, see how much you're already losing to broken processes.
That's it for this week.
— Robbie
