AI is not a technology problem: Designing the operating model that wins the race (www.wavestone.com)

A recent survey by Wavestone involving 200 CIOs across the UK highlights crucial challenges facing organizations in the rapidly evolving landscape of AI adoption. For the third consecutive year, it was confirmed that while 64% of leaders aim for cost reduction through AI, there is a stark contrast in focus between smaller organizations, which prioritize cost savings, and larger ones, which seek automation and productivity enhancements. Alarmingly, 70% of surveyed organizations have yet to fully integrate AI into their Technology Operating Model, indicating a significant gap in executing comprehensive AI transformations that go beyond mere technological upgrades. The findings underscore a pressing need for organizations to prioritize AI-ready skills and robust data governance, as only 14% and 23% of respondents respectively view these areas as investment priorities. This misalignment risks hindering the scalability necessary for realizing the full potential of AI. As technology teams shift from traditional roles to ones that emphasize AI-driven transformation, hybrid profiles that bridge operational and AI knowledge are increasingly in demand. Moving forward, companies must embed AI into their operational frameworks and focus on practical execution to achieve sustainable value, thus making effective governance and upskilling pivotal in this AI-first era.