Threat intelligence is the procurement of evidence-based knowledge about current or potential threats. The interest of threat intelligence comprises of advancement in efficiency and boosting effectiveness in terms of analytical and prevention capabilities. Cybersecurity represents serious interest for numerous organizations because maximum of them are using Internet-connected data devices which are opening doors for cyber attackers. Outstanding threat intelligence within the cyber sphere requests for the knowledge base of threat information and a thoughtful way to represent this knowledge. This study proposes a clear rationale of significant artificial intelligence (AI) techniques used for recognizing a cyber-attack. Data analysis can be formulated to guide industries and Internet-connected systems such as smartphones or robotic factories on what to do in the appearance of an incident. AI techniques will analyze past incidents and summarize knowledge from experts and will continue to adapt or reform new branches as it reviews from the new incidents. In addition, various data mining approaches used in boosting threat truthfulness in cybersecurity data are also studied. To conclude, we discussed that; AI will robotize the collation of machine-readable external threats and will improve the efficiency and accuracy of the data for each smart organization’s specific framework.