79 AI technology is rapidly advancing in healthcare, and cervical cancer screening is one area where it could make a meaningful impact. With cervical cancer remaining a significant health threat, particularly in low- and middle-income countries, healthcare professionals are investigating AI’s role in screening and detection. AI-powered methods offer hope for overcoming resource constraints and improving diagnostic accuracy, ultimately aiming to reduce cervical cancer’s global impact. The findings were published in the journal Cancer Biology & Medicine. Traditional cervical screening involves procedures like HPV testing, cytology, and colposcopy, each requiring skilled professionals and considerable resources. In low-resource areas, these limitations make comprehensive screening challenging. This is where AI steps in, with the potential to provide efficient, automated analysis of medical images. AI algorithms, particularly those in machine learning and deep learning, have shown promising results in detecting pre-cancerous lesions and classifying cell abnormalities accurately. This technology can quickly process large datasets, improving diagnostic accuracy while reducing reliance on a limited pool of healthcare professionals. Notably, AI’s impact extends beyond resource-limited areas. In high-income countries, AI is enhancing diagnostic efficiency and supporting clinicians by reducing the workload associated with manual screening. AI algorithms can process cytology and colposcopy images, detect patterns, and identify abnormalities with precision, significantly reducing false positives and improving detection rates. This enables clinicians to focus on complex cases, while AI handles routine analysis, enhancing the overall efficiency of cervical cancer screening systems. Despite its promise, integrating AI into cervical cancer screening still faces challenges. A critical hurdle is the accuracy of AI algorithms, particularly in balancing sensitivity and specificity in diagnosis. Misdiagnosis remains a concern, and AI tools must be fine-tuned and validated in clinical settings before they can be widely adopted. Additionally, a lack of quality datasets and standardised protocols limits AI’s effectiveness across different populations. Collaboration among research institutions, healthcare providers, and tech companies is essential to address these limitations and build robust datasets that enhance AI’s diagnostic accuracy. AI also faces resistance due to its perceived lack of transparency. Clinicians have voiced concerns about the interpretability of AI-generated results, as understanding how an AI model arrives at a diagnosis is essential for ensuring patient safety and maintaining trust. Regulatory bodies are working on guidelines to address these issues, with the goal of establishing frameworks that ensure ethical and transparent use of AI in healthcare. As AI technology continues to evolve, it has the potential to reshape cervical cancer screening, providing a powerful tool for early detection and prevention. While challenges remain, continued research and development could enable AI to play a vital role in eliminating cervical cancer as a public health threat, aligning with global initiatives aimed at eradicating the disease.