AI in Engineering: Moving Beyond Hype Into Reality

No two engineering teams use AI the same way. But with the right data, leaders can finally understand whether their AI investments are actually paying off.

In this analysis from Jellyfish, in partnership with OpenAI, we explore the real-world impact of AI on software development – from how it changes team performance to how it reshapes the nature of engineering work.

Then, we review the Jellyfish AI Impact Framework, a practical model designed to help organizations move from AI adoption to measurable outcomes, driving efficiency, quality, and innovation across your teams.

In this deck, you’ll gain access to:

✓ Coding assistant and code review agent adoption by tool
✓ New data on growth of AI generated code
✓ The impact of AI on PRs and cycle times
✓ Sample templates to help you roll out the AI Impact Framework