Introduction”AI is not intelligent”—this is not a clickbait! In the 21st century, artificial intelligence has become almost synonymous with Generative Artificial Intelligence (GAI) and Large Language Models (LLMs), often regarded as the core of AI. However, it is essential to ask: what exactly is artificial intelligence?Artificial Intelligence (AI) refers to the simulation of human intelligence in machines, enabling them to perform tasks such as learning, problem-solving, perception, and language understanding (Stryker & Kavlakoglu, 2024; AWS, n.d). Over the years, AI has been defined in various ways. John McCarthy in 1956 described it as ”the science and engineering of making intelligent machines, especially intelligent computer programs,” (Kersting, 2018) while Alan Turing in the 1950s introduced the ”Turing Test” to measure AI’s ability to mimic human behavior (Mirror, 2023). Russell and Norvig (2021) further classified AI based on whether systems think like humans, act like humans, think rationally, or act rationally.AI has evolved through several phases, from symbolic reasoning in the 1950s to data-driven approaches in the 1990s and the deep learning revolution of the 2010s (DataCamp, 2023; Oracle, 2020; Sestili). Today, AI applications such as speech recognition, personlised systems, and autonomous systems have transformed industries (Siemens, 2024; Rumyleyet al ., 2023; Casaca & Miguel, 2024; Brainvire, 2025). However, misconceptions about AI’s capabilities persist, often fuelled by media hype and industry marketing (Cocato, 2025; Sharps, 2024; SAP, 2024; Stryker & Kavlakoglu, 2024, Yadav, 2024; Firstpost, 2024). Many believe AI possesses superhuman intelligence, creativity, and emotional understanding (Marwala, 2024; Hermann, 2021; Nikolopoulou, 2023; Joyceet al ., 2024). In reality, AI excels in narrow, well-defined tasks but lacks general adaptability, ethical reasoning, and emotional intelligence (Glover, 2022; Lumenalta, 2024; Brookhouse, 2023). The portrayal of AI as an autonomous, self-learning entity capable of independent decision-making is misleading. AI systems rely on algorithms and large datasets, requiring human intervention for training and fine-tuning (Marusarz, 2022; Pardo, 2022; IBM, 2021). While AI enhances productivity and innovation, it should be viewed as a tool that complements human capabilities rather than replaces them.AI is simply a computer that operates on the principle of “garbage in… garbage out” and the overreliance on AI without recognizing its limitations can lead to unintended consequences, such as biased decision-making, ethical concerns, and security vulnerabilities. Hence, this paper critically examines the common misconceptions surrounding AI, exploring its actual capabilities, limitations, and the ethical considerations necessary for responsible AI adoption.