The evolution of the internet and ever increasing advances in techno-science have resulted in masses of information available to employees who are now being overwhelmed by this array of information. This work examines current effects of Information Overload, the Information Needs of employees, and the possibility of reducing these effects through the use of an Artificially Intelligent Search Assistant. The proposed framework begins by using observation and survey techniques to obtain a current state analysis. Employees spend approximately 20 % of their time obtaining information and nearly 20 % of design and development work is duplicated because searches are not successful in identifying previous work. The framework continues by examining user information needs through the use of a Data Flow Diagram, followed by the creation of user-requirements using Personas and User-Stories. A holistic information platform was proposed, validated and verified. Proposed solutions were found to be 70 % faster than existing solutions for some search tasks, and had a significantly higher Mean Average Precision than currently used search tools. The framework and technical solutions were developed, applied, and validated in an industry setting. The potential of the novel framework and proposed solutions has been demonstrated through various validation and verification techniques. The developed framework was implemented in an automotive assembly unit development branch, however, transferability to other information-intensive jobs is realistic, and should be investigated in further work.