The rapid development of artificial intelligence technology demands higher requirements for employment and talent training. The integration of industry and education is an important way to solve the mismatch between industrial demand and talent supply. Therefore, this study starts from the perspective of the integration of industry and education. We collect recruitment texts from the perspective of “industry” and mine the specific requirements of the artificial intelligence post system through the LDA topic model and the combination of Word2Vec and K-means. We then conduct expert consultations and adjust the selected indicators from the perspective of “education.” Finally, we construct a four-dimensional vocational ability grade evaluation index system, including basic vocational skills of artificial intelligence, database, network skills, algorithm and design skills, and research and practice skills. The intuitionistic fuzzy analytic hierarchy process, which can eliminate the subjective uncertainty of experts in the scoring process, is applied to calculate the index weights. We find that the weight of algorithm and design skill is the highest, which is an important criterion for artificial intelligence professional ability evaluation. Among the second-level indicators, practical indicators such as team spirit, innovation ability, and communication ability are the focus of investigation from the perspective of industry, while in education, the cultivation of knowledge and skills such as programming ability, applied mathematics ability, data structures, and algorithms are more important.