Innovation is crushing adoption. The pace of change in AI is accelerating faster than most organizations can absorb. New models, tools and capabilities are emerging almost daily, creating opportunity, but also a level of disorientation for leaders trying to turn that momentum into real business value.
What I hear consistently from clients is not a lack of ambition—it’s where to start, and how to move from experimentation to execution.
Early on, it’s not about getting the technology stack perfect. It’s about getting hands on by building, testing, and learning quickly. Over time, architecture and platform decisions become critical to scale. But progress starts with developing the capability to execute. And that’s where many organizations are getting stuck.
While the term forward deployed engineering has evolved over the past decade, the core intent has remained consistent. PwC and Microsoft have been focused on solving our clients’ most important problems at the point of impact, combining PwC’s industry depth with joint engineering delivery.
That model, often referred to today as customer engineering, has been foundational. It aligns the right expertise to the problem in real time, accelerating the path from idea to outcome. But the environment has changed.
The pace of innovation has increased the volume of demand from clients. Backlogs are growing and simply adding more resources to traditional delivery models isn’t enough to keep up. In engineering terms, scaling requires a different approach.