<p>Conventional breeding methods for improving vegetable crops are time-consuming and have several disadvantages, including longer turnaround times. The efficient and extremely accurate trait modifications provided by gene editing (GE) using CRISPR/Cas9 has produced some beneficial results. Although the field of GE in vegetable crops is still in its infancy, the recent increase in the accessibility of genome sequences accessibility provides a platform to further the field’s potential. The promise of CRISPR/Cas technology to transform the creation of novel vegetable genotypes is highlighted in this review, along with its use in improving vegetable crops. Furthermore, deep learning (DL) and machine learning (ML) tools based on artificial intelligence (AI) offer strong data processing and analytical capabilities that are quickly revolutionizing conventional GE techniques. These tools also demonstrate efficacy in predicting off-target genes, optimizing editing processes, designing guide RNAs (gRNAs), and predicting genome editing outcomes, all of which contribute to an overall improvement in editing precision and efficiency. The CRISPR-AI contributes to better accuracy and efficiency of CRISPR-based GE tools. The review concludes by summarizing the existing uses of CRISPR-based GE, the implications of AI for successful GE, the difficulties in altering vegetable crops, and AI applications. The consequences of CRISPR-Cas applications in conjunction with AI tools have led to trait improvement of several vegetable crops, such as potato, tomato, watermelon, and lettuce, among others. Applications of such tools, research gaps, and future opportunities for additional vegetable crop improvement are discussed in this review.</p>