A recent survey by Riverbed shows that while 88% of IT and business leaders believe they will meet their AI expectations, only 12% currently have AI in production. This disparity highlights the slow pace of AI project deployment, with less than 10% of projects reaching full implementation. Despite doubling investments in AI last year, many organizations lack the readiness to effectively deploy AI due to challenges related to data quality and governance.
Experts indicate that the overconfidence of IT leaders may stem from unclear expectations, as many organizations are unfamiliar with the technology’s requirements and compliance mandates. The impending EU AI Act has already shocked many CIOs who did not anticipate the level of documentation and bias testing required. To overcome current obstacles, organizations must invest in AI-native infrastructure and foster cross-disciplinary collaboration, ensuring that AI is integrated into core operations rather than treated as an isolated project.
Achieving mass deployment of AI will take time, as many leaders still do not grasp the significant shifts the technology will introduce to the nature of work. With just one in ten AI projects deployed, experts anticipate that organizations will need to adapt both their processes and infrastructures over the next few years to fully realize AI’s potential.
👉 Pročitaj original: CIO Magazine
