A tale of two AI implementation journeys

Without strong governance and transparency, AI models risk bias, compliance failures, and erosion of stakeholder trust. Trust isn’t just a compliance requirement. It’s a foundation that determines whether AI delivers on its promise or becomes a liability.

AI adoption has become a central focus for many organizations across industries, especially those looking to boost efficiency, customer service, and innovation. Despite this, adoption is far from uniform. Without tailoring strategies to industry context, AI initiatives risk falling short of their full potential.

Across the enterprise, data assets hold massive, untapped advantages—yet they’re often trapped in silos, unstructured, or hard to access. As critical enablers of AI, this mix of potential and obstacle defines the data transformation journey.