## 5 Conclusions  
The study concluded that NLP and AI is the preferred system for enterprise management in the era of Industry 4.0 to understand customers' demands and achieve customer satisfaction. The study uses text content as part of NLP and AI demonstrated by way of example in the methodology section to let us understand how companies capture customers' insight and how they use IoTs to influence the way we react, respond, and engage with their products. The result from analyses indicates the least score of 12 out of 15 grades for all the measurements on a behavior-oriented drive and influential function of IoTs on customers. The study findings are based on text content as part of NLP and AI that IoTs use to influence human reactions, responses, and engagement with enterprise management in Industry 4.0. The \"Behavior-oriented drive and influential function of IoTs on Customers in Industry 4.0\" concept are critically examined. Statistics show that the influence of Industry 4.0 evolution on customers is real and is helping a lot of businesses sky rock on their rate of returns on investments. The results of the \"Behavior-oriented drive and influential function of IoTs on Customers in Industry 4.0\" study concluded that NLP and AI is the preferred system for enterprise management in the era of Industry 4.0. This is because the system of NLP and AI integrated with IoTs enables Companies quickly understand customers' demands and achieve customer satisfaction, NLP and AI techniques are a necessity to attain business goals.  
The integrated system level by Industry 4.0 with NLP and AI embedded IoTs is very important to industrial growth as represented and analyzed in Section 4 method applied in the study. Companies use simple text or speech of customers to determine their loyalty to the company's products. A loyalist of Company 'A\" will always speech positive about that company while non-loyal customers \"B\" will speak against the company products. With all the data collected, companies use this data to tailor products to their needs and desires. Based on the text below, the company can understand which of the company's products a customer likes. With a well-structured NLP, companies do not run  
Figure 13: Artificial neural network classification of NLP text.  
expensive advertisements nowadays. The cost and time that were supposed to be spent by companies to run ads is now shifted to text analysis of customers via social media applications. Nowadays consumers spend time following social media entertainment shows, events, and activities that are oriented to understanding how consumers think. With the help of NLP and AI with support from IoTs, companies target their customers before initiating the product test phase. Based on comments, pop-up items, and shot videos that appear before long videos and online newspapers, companies use these ads to predetermine their product's needs.  
Conceptualization: P.M.M.; Methodology: P.M.M.; Formal analysis and Investigation: P.M.M.; Writing--original draft preparation: P.M.M.; Writing--review P.M.M.; Resources material for methodology: P.M.M. and J.M.; Supervision: I.S. and editing: P.M.M. and J.M. All authors have read and agreed to the published version of the manuscript.  
We verify that we have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. We have no financial or proprietary interests in any material discussed in this article.  
All data underlying the results are available as part of the article and no additional source data are required or reserved somewhere.  
The authors declare no conflict of interest.