Precision agriculture provides innovative farm information tools for improved decision making regarding crop growth and yield. Creating awareness for future applications of precision agriculture among progressive farmers in Pakistan was an instrumental force to conduct this study. The purpose was to appraise the awareness level of the respondents for applications of precision agriculture in the field. The objectives such as assessing the awareness level, available information sources, future needs, factors responsible for the applications, the constraints for the implementation of precision agriculture, and farmers’ attitude towards current and future agricultural practices were evaluated.  Four out of 37 districts were purposively selected. Sample of 150 respondents using systematic sampling with K=10 respondents from the list of 1500 progressive farmers was selected. Average age was 52 years with 20 years farming experience. The respondents were sentient in only four concepts out of 19. Hence, there is a dire need that policy makers should develop supportive policies to create resourceful PA environment for farmers to boost up awareness level and training opportunities. The Factor analysis applied to understand the role of different factors in espousal of precision agriculture. The first factor alone explained 42% variation, and by adding second factor, the explained variation goes up to 71%. So, two factors found enough to achieve the desired level of explained variation in the dataset. By using Varimax factor rotation technique, variables of interest were differentiated. The first component was explained by two variables; training needs and responsible factors for applications of precision agriculture, with maximum loadings of 0.950 and 0.951 respectively and called as “respondents’ training needs in the specific concepts” where PA has strong applications.  The second principal component called as “demographics of the respondents” since age and experience were highly correlated variables having maximum loadings of 0.903 and 0.926 respectively. The cross tab analysis described that there was no statistical significant association between current and future agricultural practices since χ2 (4) = 7.048, p = 0.133 that means both practices were independent in usage. However, very weak association observed between the two practices with Phi and Cramer's V value = 0.217.