The article addresses the common task of precise hole measurement in machine and equipment manufacturing, the automotive sector, aviation, and the defense industry. Attention is drawn to the challenges associated with this process, particularly when the hole depth to diameter ratio is significant, which considerably complicates the acquisition of accurate measurement data. Previously employed measurement solutions are also presented, including the use of coordinate measurement techniques and selected optical systems, such as triangulation-based laser systems, structured light systems, and computed tomography. Example results are shown, and the observed regularities during hole measurements using these systems are discussed. A modern approach to the hole measurement is proposed, based on the automatic extraction of geometric data from CAD models, along with the concept of automatic measurement tool selection using a multi-criteria tool selection matrix. Potential directions for the further development of the proposed methods are also discussed, especially considering the use of machine learning for the prediction of measurement uncertainty and the optimization of measurement strategy selection. The presented approach represents a novel and original contribution to the advancement of geometric measurement automation methods. The article emphasizes the growing importance of artificial intelligence based tools in coordinate metrology, highlighting the necessity of proper design and collection of measurement data in the form of databases, which serve as the foundation for the effective operation of intelligent algorithms. Key directions for the development of metrology are also indicated, and current trends that are expected to shape this field in the coming years are described.