The spread of misinformation has become one of the fundamental challenges of contemporary societies, its dimensions are not limited to the media sphere, but have far-reaching consequences on social, economic and political structures. The spread of this phenomenon has led to a decrease in public trust, weakening social capital, disruption of decision-making processes and increased social polarization. In such circumstances, the need to provide efficient solutions to manage and control the flow of information is felt more than ever. Meanwhile, artificial intelligence is emerging as a dual technology; in that it both provides significant capabilities to combat misinformation and can itself help to exacerbate this crisis. On the one hand, tools such as machine learning algorithms, big data analysis, and automated verification systems can be effective in identifying, monitoring, and reducing the spread of false content. On the other hand, the same technology, by enabling the production of advanced fake content such as deepfakes, enhancing user behavioral profiling, and precise information targeting, paves the way for the spread and sophistication of false information. This study, using a descriptive-analytical method and using library resources, examines the dual role of artificial intelligence in dealing with misinformation and analyzes its capacities and limitations. The research findings show that there is no single and absolute solution to control this phenomenon, but rather a combination of measures such as clarifying the functioning of algorithms, promoting media literacy, and developing effective regulatory frameworks is necessary. The research results also indicate that cooperation between governments, digital platforms, and users plays a key role in managing this challenge.