ROI on the AI adoption might be measured in tech companies.💡My insights
1️⃣
AI can lead up to 25% increase in productivity (10% median)2️⃣
AI works best if your workload is following the best SE practices (tests, modularity, types)3️⃣ You can measure AI adoption effect just using the git history and comparing past vs present
4️⃣ They provided example of one company of our size, after AI adoption
* number of PR grew up 📈 , but code quality decreased 📉
* Rework type of code changes increased
x2.6 (a lot)* Effective output gain only
+1% 🤯What does it all mean? 🤔
It does not mean that we will stop using AI, but that we will use it more consciously and improve in the areas where we are lagging. The fact that code is now cheaper is not the final answer. We have gained a new tool, and this tool helps (as proven by
+25%), but achieving those +25% (or even +10%) is not a default outcome.