Kieran Gilmurray highlights that many AI initiatives fail not due to technology issues but because organizations often pursue AI without a clear business problem, leading to ineffective projects. Poor data quality, inadequate governance, and insufficient executive support are common obstacles. For AI to succeed, it requires alignment with business goals, rigorous project management, and a focus on measurable results.
To transition from pilot projects to operational AI, businesses should prioritize a select number of high-impact use cases, ensuring that teams consist of both technical and business experts. A structured approach enhances collaboration and accelerates the development and implementation of AI solutions. The way AI is perceived also matters; when integrated with business strategy, the focus shifts from novelty to value creation, paving the way for broader adoption and trust in AI initiatives.
👉 Pročitaj original: CIO Magazine
