Artificial intelligence (AI) is set to transform the field of colonoscopy through the implementation of computer-assisted detection and diagnosis. While over 20 randomized controlled trials have demonstrated the efficacy of AI in increasing adenoma detection rate, the broader implementation of these technologies faces hurdles due to economic considerations and reimbursement challenges. Cost-effectiveness analysis plays a crucial role in determining the viability of integrating AI into clinical practice, highlighting both the potential long-term benefits and the initial economic burdens. Comprehensive evaluation and large-scale studies are essential to realize AI's potential in optimizing colonoscopy procedures and reducing health care costs.