Transparency as the engine of trust
And what happens when something goes wrong, or we reach the limits of our current capabilities? Enter transparency. We need to be honest about what our technology can do and what it can’t. When it’s not up to a task, we need to say so. When it makes a mistake, we need to own up to it and correct it. As the Navy SEAL mantra goes, “Slow is smooth, and smooth is fast.” It’s only by building trust that we can achieve long-term growth.
In PwC’s 2025 Global AI Jobs Barometer, we’re already seeing what quality and transparency can mean for AI adoption. The greatest AI productivity gains are happening in industries where AI outperforms advanced humans (think software engineering) and in highly regulated industries, where transparency is legally required (think finance, insurance and manufacturing).
History proves the paradox that setting narrow trust perimeters enables sweeping technological change. In the early days of the cloud, for example, when enthusiastic early adopters would ask if it was possible to get an exabyte of data immediately, the providers that ultimately led the industry were the ones who said, honestly and cautiously: “not yet.” Those innovators achieved progress step by step, setting achievable goals and not overpromising. Eventually, they overhauled decades of data processing and storage norms.
