Objectives:
The study evaluated the influence of digital design software on crown morphology, occlusal characteristics, fracture force, and marginal fit across varying preparation designs for an identical target tooth.

Methods:
A resin-based tooth (tooth 36) was digitized, manufactured (
), individually prepared and re-digitized. Five design groups were established using conventional software proposals, technician designs, two AI-based software solutions, and natural tooth-based reference designs. All systems employed consistent parameters. Crown designs were digitally assessed using quantitative morphological and occlusal metrics in reference to the original tooth. Crowns were milled, marginal fit was measured via digital microscopy, and fracture resistance was determined after thermal cycling and mechanical loading.

Results:
Morphological metrics revealed statistically significant deviations across groups, with the technician design achieving the best performance. Occlusal metrics showed high deviations in the positional accuracy of the contact points across all groups. Technician and AI-based designs exhibited comparable functional results. None of the design groups were able to achieve contact with all relevant antagonist teeth, due to high deviations in the mesiolingual cusp. Conventional software designs exhibited the lowest fracture forces. Significant improvements were achieved through technician intervention. Vertical marginal discrepancies remained comparable across groups.

Significance:
Improved functional and morphological design combined with high fracture resistance can reduce the need for clinical adjustments, minimize wear, and enhance crown longevity. Digital design software significantly influences crown morphology, occlusal characteristics and fracture forces. Vertical marginal discrepancies remain similar. AI-driven approaches demonstrate comparability with technician designs in terms of fracture forces, functional performance, and marginal fit.