Hey! I am incredibly excited to finally release our industry report on how engineering teams are using AI.
We have been running a big newsletter survey for the past two months, plus we held 1:1s and sat with several engineering teams to figure out what they are doing. The result is a ton of data points, both quantitative and qualitative, which should help us navigate what is it that teams are getting right, wrong, the challenges, and the opportunities of using AI in the software development lifecycle.
We have been doing this together with the team at Augment Code, which provided plenty of support and funded part of the work, making it possible. This is the largest scale research we have ever run at Refactoring, and it was possible thanks to them!
So here is the agenda for today:
🌐 Demographics — let’s look at who replied to the survey.
🙋♀️ Personal adoption — how people are using AI for individual work.
👯 Team adoption — how companies are adopting AI at a team level: practices, process, use cases, and challenges.
🎓 Skills & Jobs — how AI is impacting the job market in terms of skills, hiring, and seniority levels.
🪴 Adoption path — finally, we’ll try to put all of this together and sketch an adoption journey made of a few key steps, that takes from all the answers we got.
Let’s dive in!
🌐 Demographics
We collected 435 respondents to the survey.
As we did with other surveys in the past, we intentionally went for quality over quantity, which meant the survey was substantial, with plenty of free-form questions that took a while to answer.
We took this route because AI is an extremely nuanced topic, and in many cases we didn’t want to pidgeon-hole answers by making people choose from predefined lists for things.
A lot of free-form answers also mean a lot of manual work to clean up, categorize, and collect insights from such data. We reviewed every single answer, attached tags to it, and drew correlations.
Here is more about the people who joined this:
1) Geographies
Respondents come from all over the world, with the following breakdown:
2) Roles
About 52% of the respondents are pure ICs, while 34% are managers. There is also a 14% of tech leads that falls pretty much in the middle.
All in all this fits the distribution we have seen in previous surveys, with ~60% ICs and ~40% managers.
🙋♀️ Personal adoption
About personal usage of AI, here are our key insights: