Together with Per Aarsleff we explored various aspects of the bid management journey and decided on three key areas. First we looked into how we could generate structured bid outlines by analysing past successful bids and tender requirements. This AI tool streamlines the initial planning phase, ensuring a comprehensive starting framework for bid managers.
Secondly, we developed a solution that helps create an overview of a broad data catalog, focusing on specific topics and related subjects, while presenting the information in a relevant manner. This context-based search engine can process large volumes of data, assisting bid writers in quickly finding and connecting relevant information. It enhances the ability to gather comprehensive insights, streamlining the research phase and ensuring a more informed approach to bid creation.
The final layer was an AI assistent that would scan completed bids against tender requirements, identifying potential gaps or areas for improvement. By providing actionable suggestions, it enhances bid competitiveness and completeness. This automated quality assurance step helps catch oversights and ensures all tender requirements are adequately addressed before submission.
Successful AI implementation requires collaboration between AI experts, domain specialists, and business stakeholders. This cross-functional approach ensures that AI solutions are technically sound, business-relevant, and aligned with organisational goals. Per Aarsleff's deep involvement and expertise were crucial in achieving this alignment.
Identifying and focusing on AI applications that address significant business challenges is crucial. By prioritising use cases with the highest potential impact, companies can maximise the value of their AI investments. Per Aarsleff's thorough understanding of their bid management process was instrumental in identifying these high-impact areas.
Starting with proof-of-concept solutions allows for quick validation and learning. This iterative approach enables companies to refine their AI strategies based on real-world results before scaling up implementation. Per Aarsleff's willingness to embrace this approach was key to the project's success.