NLP therefore facilitates the relationship between man and machine so that the two work hand in hand in providing complimentary services to the enhancement of generation of content and decision-making processes. Literature review of NLP points out that integrating creativity and efficiency in the generation of content and decision, in this case, is suboptimal. The role of this work is therefore to present thoughts and cases on how the human–machine cooperation can be applied in the generation of the NLP content and in the decision support processes. Similar to any other data acquisition process for any other applications, it is mandatory to define the specific NLP tasks of interests as well as the target beneficiaries for the data to be gathered in order to serve or benefit them, the kind of data that should be gathered including the text files, web data, and the role of human beings in validating the data collected and annotating it. To increase the data quality and relevance as input to NLP applications, the following pre-processing procedures are used: preprocessing methods—stemming/lemmatization methods of preprocessing; and, removing stop words preprocessing with assistance of human beings in correcting the data annotation mistakes. This way also produces more accurate, as well as consistent results because the outcome of the semi-automated process can be verified or edited if necessary. The analysis methods such as, sentiment analysis, topic models and named entity recognition make it easier to extract important information out of this data and enhance human–machine interfaces. They help to minimize the time spent in NLP and procedures regarding NLP models in machine processing encompass the configuration of these models for particular tasks; however, these tasks do not end with: summarization, sentiment analysis, information extraction, trend identification, as well as content generation. The future scope is in applying expert NLP methods for enhancing the cooperation between people and machines for more effective content creation and decision support.