Bengaluru: Kempegowda International Airport’s operator, Bangalore International Airport Limited (BIAL), has entered a strategic collaboration with KPMG in India to develop a Generative AI (GenAI) platform aimed at enhancing operational efficiency and data-led decision-making.
The initiative between BIAL and KPMG marks a broader shift towards integrating emerging technologies in core airport management functions.
Focus on Predictive Insights and Operational Efficiency
The GenAI platform will be tailored to BIAL’s operational needs and is designed to process and analyse large datasets in real time. By using predictive analytics, the system is expected to support informed decision-making, enabling airport teams to anticipate disruptions and adjust operations accordingly.
Officials say the project is structured around real-world operational goals rather than speculative technological promises. The emphasis lies on using AI to automate routine tasks, enhance resilience, and support day-to-day functions across airport systems through real-time insights.
Scalability and Responsible AI Key to the Project
The architecture of the platform will incorporate responsible AI principles, with a focus on data privacy, cybersecurity, and scalability across various airport functions. Rather than being a one-size-fits-all solution, the system is expected to evolve alongside BIAL’s operational demands.
George Fanthome, Chief Digital and Information Officer at BIAL, noted that the partnership aligns with the airport’s broader goal of becoming “future-ready” by integrating adaptive technologies that are scalable and secure.
KPMG India’s Role in Technical Deployment
KPMG in India will provide technical expertise and guidance in developing and deploying the platform. The consulting firm brings its knowledge of AI systems and aviation sector workflows to tailor the solution for real-time airport environments.
According to Girish Nair, Partner and Head of Aviation at KPMG in India, the project is a step toward redefining airport operations using emerging AI capabilities, though its success will depend on how well the platform performs under operational stress and user adoption.
