Harnessing Generative AI: A Case Study of Amman Express
This case study explores how Amman Express, a Quick Service Restaurant (QSR), leveraged generative Artificial Intelligence (AI) to enhance data accessibility and improve decision-making for its franchisees. Traditional data analysis methods were slow and inaccessible, leading to frustration among franchisees and missed opportunities for the brand. By implementing a Large Language Model (LLM) behind their firewall, Amman Express enabled franchisees to ask questions and receive reports within seconds. This generative AI solution streamlined data access, freed the data analytics team from routine tasks, and improved overall business efficiency and strategic decision-making.
The introduction of generative AI had a significant positive impact on various aspects of the business. Franchisees gained faster access to data, allowing for more informed decisions and local innovations. The data analyst team shifted from routine query generation to deeper analysis and strategic initiatives, enhancing their overall productivity. The Business Intelligence team became more agile and responsive to franchisee needs, fostering better collaboration and tailored intelligence reports. Overall, the AI implementation led to streamlined decision-making, improved operational efficiency, and tighter alignment with strategic goals, positioning Amman Express for future success in the competitive QSR industry.