How do you measure productivity? The research suggests that, with AI tools, perceived programmer productivity increases, while objective productivity decreases. In addition, maintainability decreases as more of your code base has never been seen by the human sent in to clean up the AI-generated messes.
That should indicate that we need to prove a massive increase in productivity to justify the use of AI tools. But how to measure it?
Lines of Code (LoC) was already a bad measurement. In the days of AI, it is a totally random measure, and a higher LoC might just as well indicate a decrease in functionality as an increase.
If you’re in the big enterprise/government world, you might use Function Points or Use Case Points. If you are running Agile, you can use team velocity (within each team). Ideally, you would measure business value. Unfortunately, few organizations can articulate and calculate the business value of their IT.
If you want to argue that AI tools increase productivity, you need to put a number on the productivity you claim to increase.