A transport authority in the Middle East wanted to understand its current artificial intelligence (AI) capabilities and needs, and accelerate AI adoption and innovation across the organisation. The authority is responsible for the city’s transport networks and services, including public transport operations, road maintenance, traffic management and driver and vehicle licensing.
PwC’s Middle East Technology and Digital Consulting team was commissioned by the authority to undertake a comprehensive assessment of its current capabilities, including understanding the existing data, systems and AI use cases, and benchmarking against global transport-sector leaders and current industry trends. The goal was to develop an AI strategy and a five-year AI masterplan to action it. In addition, we were asked to design the enabling capabilities, including a refreshed operating model for AI and an enterprise AI platform.
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Overview
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Our role
During this 10-month project, which began at the end of 2019, we engaged with departments across the whole of the authority’s operations to understand the current capabilities related to AI and capture more than 50 ongoing and planned projects where AI can play a role. We also identified more than 80 AI use cases to be explored as potential future projects and developed proofs of concept (PoCs) for AI-enabled services. These included COVID-19-related use cases to demonstrate the ways AI can provide value to the authority and its customers.
In addition, we developed the authority’s AI Strategy, which aims to make it a world leader in AI in roads and transport, with a clear set of objectives and focus areas. The strategy is supported by a five-year masterplan for AI, which tracks all implementations across the authority, and a refreshed operating model for effective engagement. The enterprise AI platform provides the technical capabilities required to fully activate AI, building on the authority’s existing advanced capabilities in data management.
Background to the project
The authority wanted to define a clear strategy and coordinated path for activating AI throughout its different departments, building on its existing AI capabilities. The ultimate goal was to establish it as a global AI leader among transport authorities.
How we helped
From the start, we took an inclusive approach to engage all the authority’s stakeholders, enabling them to take ownership of their AI agendas in alignment with the overall AI Strategy, objectives and focus areas. Together, we identified use cases for AI that would either mitigate existing challenges or enable new opportunities. We also analysed ongoing and future projects and identified areas where AI could help.
Additionally, we developed a refreshed operating model for AI, formalising this inclusive approach and co-operation as the new way of addressing AI, and designed the authority’s enterprise AI platform. The platform provides the environment for testing AI concepts and also develops and hosts AI services within the authority to promote efficiency, reusability, collaboration and innovation.
Impact and potential
Our biggest impact was to demonstrate the practical and problem-solving potential of AI, drawing on PwC’s global industry and technology expertise in this field and also in transport and mobility. Our work has already produced a number of AI use cases that have been tested in PoCs and can be taken up further by the authority’s respective departments. These include:
- Bus Network Planning and Optimisation: This AI tool can study the authority’s public bus network across its all its lines, with the aim of identifying opportunities for improving efficiency and customer experience by rerouting connections between bus stops. Our AI model evaluated and scored millions of possible bus connections to maximise passenger utility, taking into account road restrictions, fuel consumption and other constraints. The model predicted the top connections that would be used immediately to satisfy unmet customer needs.
- Passenger Demand Modulation: This AI tool supports faster and safer commuting on the urban rail network, through dynamic demand redistribution and simulation. We designed an algorithm using advanced optimisation and dynamic programming to redistribute commuter trips at the busiest times. For example, during the morning rush hour, a mobile app can alert a customer that if they arrive at a station 10 minutes earlier than their normal time, they can save up to 20 minutes of waiting for their turn to board the train. Simulations of the AI tool demonstrated that it was possible to achieve reductions of up to 90% in passenger overflow at stations, while still delivering commuters to their destination on time and maintaining COVID-19 physical distancing.
- Chatbot Enhancements: This AI capability can enhance the current chatbot by automatically discovering accurate answers from the authority’s knowledge base without the need for the traditional manual data annotation that the current chatbot requires. Our PoC demonstrated great gains for the chatbot in automation, efficiency and coverage in discovering new topics from the knowledge base, in both Arabic and English.
We worked with the authority to take their ambitions in AI to the next level by helping them to institutionalise AI and embed it in their future projects. The AI masterplan and enterprise platform will enable our client to deliver more value and a better experience to customers, employees and partners.
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