Argument — the bigger case.
For most of the last 30 years, enterprise software had a fairly clear job.
- Capture information.
- Organize it.
- Analyze it.
- Show someone what happened.
Then a person took over.
- A manager decided.
- An analyst interpreted.
- An engineer implemented.
- A services team executed.
The software stopped at the edge of the work.
AI starts to erase that boundary.
A system can increasingly understand context, determine what should happen next, initiate actions, evaluate the result, and continue.
That sounds like automation. It is bigger than automation.
Automation follows a path someone already designed. Execution systems increasingly determine the path.
That changes where value accrues.
- The most valuable model may not win.
- The prettiest application may not win.
- The company with the most engineers may not win.
The advantage starts moving toward whoever can combine:
- Context.
- Data.
- Policy.
- Decision authority.
- Workflow.
- Execution.
That is the layer I am watching, because the gap between knowing and doing has always been expensive. AI is starting to collapse it.
The next generation of enterprise technology will not be defined by what software can tell you. It will be defined by what software can reliably get done.
Find the boundary where your systems hand the work back to a person. That boundary is probably where the next redesign starts.
Written by Jason Wojahn. AIorDie is a personal publication about what breaks when software starts doing the work.
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