Many companies are heavily investing in artificial intelligence (AI), yet they often lack the necessary infrastructure and skilled personnel to fully realise its potential. A significant challenge is building a robust data infrastructure, with many firms addressing data issues inconsistently on a project-by-project basis. Poor data quality, stemming from messy and siloed information, hinders even advanced AI models. Furthermore, organisations struggle to find talent in areas like machine learning and face internal resistance to AI adoption, sometimes leading to waning enthusiasm. To succeed with AI, companies need to develop cohesive data strategies, invest in automation for data management, upskill their workforce, and foster a culture that embraces AI.

This discussion is based on the following CNBC article:

AI implementation projects are far from intelligent inside companies

https://www.cnbc.com/2025/01/22/ai-implementation-isnt-being-done-intelligently-inside-most-companies.html