Generative AI in digital product engineering

Generative AI offers significant potential in digital product engineering, but new research shows that only a few organizations are realizing its value.

Based on our survey of hundreds of product and engineering leaders worldwide, organizations are struggling to scale generative AI in product development—whether it’s early idea generation, building, testing, or support. One in five haven’t even started experimenting with gen AI.

And for those that have made progress, the technology hasn’t delivered as predicted. Just 27% report having achieved the functional value they initially anticipated, and only 23% say they have realized the financial returns they expected. 

Why the challenge? Our analysis reveals a compelling truth: the habits teams cultivate matter significantly more than the AI tools they use. The most successful digital product teams aren't just experimenting with generative AI—they're fundamentally transforming how they work to harness its power. 
 

Product team work habits—not just AI tools—determine gen AI success.

The teams seeing strong results—55% return on their investment:

• Deliver in small steps. They release improvements bit by bit, learning and adjusting along the way—not waiting for one big launch.
• Work as one multidisciplinary team. Designers, engineers, and analysts collaborate closely, reducing delays and handoffs.
• Turn user data into action. They don’t just collect data—they use it to make real product decisions.
• Keep standards flexible. They adjust their standards and ways of working as needed based on feedback and experiential learning.

These practices help teams turn gen AI from an experiment into a regular part of making better products. The real breakthrough happens when teams shift their focus from merely using AI to focusing on measurable results and continuous learning—making gen AI part of how they work.

Download the presentation of benchmark data to delve deeper into where organizations are today in their use of gen AI in digital product engineering, where they are seeing value, and how leaders work differently. Recommendations on best practices for optimizing gen AI ROI through high-performing teams are included.