Brief

Modernizing outdated IT infrastructure is crucial for organizations to effectively leverage artificial intelligence. Many companies attempt to implement AI on legacy systems not designed for current demands like cloud computing and real-time data access. This approach often leads to increased complexity, new risks, and stalled AI pilot projects, as the underlying foundations are not robust enough to support advanced technologies. Incremental modernization, rather than a complete overhaul, is presented as a safer and more realistic path forward, especially in sectors like financial services. AI

The adoption of AI is progressing at different rates across economic sectors, with financial and legal services leading due to their digital-native workflows and lower regulatory hurdles. In contrast, sectors like healthcare, manufacturing, and the public sector are adopting AI more slowly because of significant physical, regulatory, or accountability constraints that AI cannot easily bypass. Healthcare, for instance, is seeing rapid adoption of administrative AI for tasks like scheduling and billing, but clinical AI applications for diagnosis and treatment face much larger obstacles due to the high stakes and complex judgment involved. AI