In the dynamic landscape of modern media consumption, effective news categorisation is imperative. This study underscores the critical role of NLP integration in the evolution of news classification methods. It addresses the challenges of consistency and precision while also optimising categorisation efficiency. The aim is to minimise human intervention while improving accuracy. Notably, integrating NLP emerged as pivotal, as evidenced by achieving a 1.0 accuracy score, when the bart-large-mnli model of the zero-shot classification pipeline was used. While TF-IDF combined with KMeans did not yield optimal cluster distinction due to category overlaps, strategic sub-categorisation could enhance cluster differentiation.