Cindy B. asked a question to Aly M.
Hi Cindy,
One of the most recent and impactful innovations I’ve contributed to at Nokia has been driving AI adoption in R&D in a way that translated directly into measurable efficiency gains and potentially customer value.
I led an adoption‑first AI execution that shifted teams from isolated experimentation to consistent, measurable use of AI embedded in daily engineering work. Within roughly eight weeks, this increased active usage of AI‑supported coding capabilities by around 45 percent and drove more than a fivefold increase in AI‑enabled specifications and requirements insights.
The impact was tangible. This unlocked a sustained ~1,160 engineering hours per week, equivalent to roughly 31 engineer‑years annually, achieved with approximately 560 hours of focused, non‑BAU execution effort. The freed capacity was reinvested in higher‑value activities such as system design, quality improvements, and faster iteration cycles. For customers, this translated into improved execution predictability, higher quality, and shorter feedback loops that support faster innovation and delivery.
What made this innovative was not the technology itself, but how it was operationalized. We treated AI as part of the operating system of R&D rather than a separate initiative. That shift enabled sustainable productivity gains and created headroom for teams and customers to grow without simply scaling cost or complexity.
Outstanding accomplishment, with end results that created growth and increased revenue.
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