The AI Impact Report 2025
How is AI adoption really changing the face of software engineering? Here’s what 880+ engineering leaders had to say.
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Read the full report to learn how AI adoption is impacting developers, budgets, processes, and talent pipelines.
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What’s inside
- How AI coding tools are impacting engineering roles
- How orgs are investing in AI coding tools and LLMs
- The biggest challenges leaders face with AI adoption
Key takeaways
Two years into the generative AI boom, we’re still trying to effectively understand how coding assistants and LLMs are impacting engineering teams. Here’s what 880+ engineers think.
Of respondents said their AI investments focus on internal engineering tasks like dashboards, testing, and code assistance.
Of respondents feel more productive using AI coding tools.
Plan to focus on managing AI agents, and 53% on prompt engineering, to build AI expertise in the next year.
Of respondents expect hiring of junior engineers to decrease.
Which of the following challenges have your organization experienced with AI in the past 6-12 months?
Organizations face major AI adoption challenges like hallucinations, poor code, security risks, and unclear metrics.
Download the report
Read the full report to learn how AI adoption is impacting developers, budgets, processes, and talent pipelines.
