Avian influenza (AI), caused by the avian strain of influenza A virus (AIV) is one of the significant health concerns globally. Human infections with AI viruses were reported sporadically and often exhibited high mortality and morbidity rate. AI outbreaks also influenced the safety of the food supply and caused significant economic losses. Immediate control measures are required during AI outbreaks in poultry to prevent further viruses spreading. Hence, accurate, sensitive, and rapid detection methods are pivotal for decision making. Traditional methods of detection, such as virus isolation in embryonated chicken eggs, immuno-based methods, and nucleic acid amplification method, pose different limitations. These always grab the attention of researchers to improve existing methods or invent novel diagnostic approaches to compensate for the shortcoming of current methods applied. However, the method of choice is highly dependent on the availability of facilities and resources. Among the detection methods, reverse transcription-polymerase chain reaction (RT-PCR) is the most favourable method used for detecting AIV. However, a constant review of the virus genome is crucial to maintain the assay’s sensitivity. More comprehensive research and evaluation study are needed for new diagnostic approaches.