Planning a geotechnical site investigation for a mega transportation project is a challenging task especially if a large quantum of information and data must be managed. Traditionally, the focus in planning investigations is on the product itself with little care given to the data and information used to get to the product. This paper explains how to simplify the delivery of products and reduce costs by managing the data and the information correctly. It describes: how large language processing, optical character recognition, and machine learning models can accelerate data extraction from geotechnical logs; the fundamental qualities and functions of a cloud-based geotechnical database to improve collaboration and configuration management; how parts of the reliability assessment of historic ground data can be automated; how geographical information system (GIS) can summarize the desk study information into a singular site plan to enable a more holistic interpretation of subsurface conditions. This paper discusses how novel methods can enhance the efficiency, accuracy, and precision of the desk study, geotechnical risk assessment and the scoping processes. It is based on a highway upgrade project in Queensland, Australia involving multiple new interchanges and bridges, and where novel methods were used to deliver a cost-effective scope.