- Artificial Intelligence is rapidly transforming India’s aviation sector, driving smarter operations, cost savings, and enhanced passenger experiences.
- With strong government support and booming passenger demand, AI is set to play a pivotal role in unlocking growth and efficiency across India’s aviation ecosystem.
India’s aviation industry is expected to contribute approximately $250 billion to India’s GDP with the industry expecting to mirror the GDP growth of 7 per cent roughly. The number of airline routes in India has seen a whopping increase from 209 in April 2014 to 605 routes in April 2024. Tier 2 and Tier 3 connectivity has contributed a lot to this growth numbers. More than 40 per cent of the passengers are travelling between the Metro and Non-Metro parts of India.
As of Jan 2025, the number of passengers is expected to be roughly 162 million and the is expected to touch 3.8 billion by 2040. This underscores the massive opportunity that our airline industry has, and the next decade will be the golden period to spearhead the growth phase.
Artificial Intelligence and Growth Areas:
Faster technology adoption and integration of Artificial Intelligence help to have a healthy transformative shift with a promise to redefine the travel experience. Shifts in technology trends will play a pivotal role in streamlining operations, improving efficiencies, personalizing travel experiences, and capitalising on revenue-increasing opportunities. AI is not merely an enhancement but a catalyst for growth in India’s burgeoning aviation market.
AI’s transformative potential can be categorized into 2 critical areas:
1. Revenue Improvement
2. Cost Optimization
Let us explore these domains in depth to understand how the future of aviation can be redefined.
Revenue Improvement
Demand Sensing: Accurate understanding of the demand helps the airlines to have better pricing strategies. AI models can easily support doing multi-variate analysis using factors such as the number of ticket searches, festive seasons, local events, weather conditions, and demographics of the place, and understanding the multi-modal transport ecosystem to forecast the fluctuations.
Indigo’s AI models analyse the historical booking data, market trends, weather conditions, events, and social media trends and helped in better demand sensing that reportedly led to a ~25 per cent improvement in demand forecasting. Another example from SpiceJet involved their AI models predicting an increased capacity requirement during the 2024 Durga Puja festival, leading the airline to acquire the additional wet lease of aircraft to accommodate the temporary surge in demand.
Dynamic Pricing: Airlines consider multiple factors such as competition, frequency of flights, competitor fares, availability of alternate surface transport options, and inputs from demand sensing to adjust their price elasticity. In addition, customer data can also be added to deliver a personalized pricing offer to the customers. AI models have evolved so much to take inputs in larger chunks of data, and historical data to analyse and propose the best pricing offers in real time.
It is a proven fact by following dynamic pricing strategies, airlines can increase the number of seats sold by up to 4 per cent and sequentially drive the yield higher by up to 10 per cent in monopoly routes.
Upselling and Cross-Selling: With the ability to plug in multiple variables including passenger data, the models can predict ancillary services that can be promoted as a bundled offer having the highest probability of conversion.
Imagine a family with kids booking their journey to a popular tourist destination. AI models can offer a “Family Fun Pack” with extra bag allowance, discounted tickets to popular theme parks, local travel options along with a free recommendation on kid’s kid-friendly areas and activities to be done. This takes away a significant amount of stress and anxiety in planning and instead allows them to plan with peace of mind.
Airlines across the globe like KLM, Air France, and JetBlue use AI Models to drive up revenue through ancillaries. Studies suggest that it can contribute to incremental revenue by up to 10 per cent in ancillary revenues.
Cost Optimization:
Fuel Optimization: Fuel costs contribute to close to ~35% of overall airline expenses. It is important to identify the ideal flying route based on weather conditions, and wind patterns including real-time weather data. By analysing the past weather data, type of aircraft flown, and typical load factors carried for the same season, the models can easily help to save 1~2% of the fuel costs.
Philippines Airlines introduced a program powered by Artificial Intelligence named SkyBreathe OnBoard focussing on achieving fuel efficiency. In just 9 months of implementation in 2022, PAL reported a net savings of 3.7 Million Kilograms of Fuel resulting in $4.1 Million savings.
Predictive Maintenance: Aircraft and their Engines are typically multi-million dollar assets. Typical A320 kinds of aircraft have 340,000 individual components put together to make flying easier. Imagine the kind of maintenance required and safety is paramount in aviation. It is a mammoth exercise to maintain and repair as every individual component requires attention here. Real-time collection of data from airframes and engines and feeding them into Software Analysers that are fitted with AI models help to identify and recommend parts that will require “Predictive Maintenance”.
OEMs have enabled the collection of all airframe and engine-related data during flying hours and the same is to be transmitted via SIM Data connection to the back-end servers for every landing of the aircraft. This helps the airline’s maintenance team to be on top of their game analysing any errors or warning messages.
Imagine this scenario from the OEM perspective where they will be able to collect and analyse data about individual aircraft types across the globe. They will get a ton of data feed across the globe (irrespective of airline) and this will help the OEMs to study the performance pattern as the data is coming from diversified geographies, weather conditions, and mode of operations. The models help in identifying patterns, behaviour analysis, identifying root causes, and suggesting alternatives thus improving the overall health of the aircraft and avoiding ground time for airlines.
Optimized Crew Scheduling: Indigo Airlines has an employee count of 37,000 and Air India group has 18,000 in their organization. Most of them form the Airport Operations Team, Cock Pit Crew, and Cabin Crew where they will operate on 3 shift patterns. This is an industry that works 24/7/365 days and it involves massive roster planning.
There are heavy regulations when it comes to rostering placing the highest importance on the Safety of Operations and Passengers. Hence, factors like travel related to duty, fatigue management, accommodation of hotel and related travel outside the base stations are key parameters. It is a mammoth task to get these activities done in the most optimized manner to have lesser cost of operations.
Imagine if the rosters are not planned correctly for an international flight, airlines will be forced to make another set of crew travel from the base station to that international station just to start their duty from there. This involves double the cost of travel + accommodation due to poor planning. AI Engines identifies anomalies considers multiple factors that may go wrong and helps to come up with optimized planners. Artificial intelligence can easily help airlines to save up to 1.5 per cent of costs in this area.
Governmental Attention
While the industry is progressing at a breakneck speed in terms of technological advancement, there is a lot for the Government to benefit from the same. If you think about what role government can play in this, let us understand how it can benefit.
AI Sandbox Environment – The government can form the Innovation Hub as a platform encouraging multiple start-ups, evolved airlines, airports and other ecosystem members in the travel chain to collaborate and exchange ideas.
Regulatory Sandbox for AI – This shall allow airlines to innovate and test the solutions in a controlled environment while fully being compliant with the regulations. When this is achieved during the POC stages, it makes it easier to scale solutions at industry levels thus speeding the efforts to take the product to markets quicker.
The following benefits can easily be achieved with this platform
- Encourages Private Sector Investment in cutting edge technologies and the government gets a wonderful chance to understand the industrial and consumer trends and patterns.
- The government shall encourage Open Data Access with the centralized platform where the travel ecosystem partners can have access to limited/anonymous and non-competitive data. This will help the AI models to train better which can be of larger benefit to the Government Planning and Execution.
- Insights generated from this can be used by the government to identify potential investment and infrastructure opportunities such as identifying new airport needs in tier 3 and tier 4 towns and also upgrading the facilities in tier 2 cities.
- This data-driven approach by the government agencies will help to generate direct and indirect employment opportunities around the travel ecosystem thus adding to GDP contribution.
Singapore’s Changi Airport launched the Changi Airport Living Lab with a similar idea in 2017 where it collaborates with multiple government and private entities. The airport’s revenue increased by 45% in 2023 to S$2727 Million, partly aided by the slew of initiatives from the Living Lab.
Japan has launched the Airbus Tech Hub in Tokyo in collaboration with the French government with a focus on enhancing R&D activities on decarbonization technologies, improving operational efficiencies etc.
Concluding Thoughts:
Embracing AI is not just a choice but has become a necessity. This will play a pivotal role in transforming the Indian Aviation sector in the coming decade. The potential of Artificial Intelligence to increase revenue, and optimize costs is unparalleled. With the able support and ecosystem from the Government in setting up AI Sandboxes, and Innovation Hub, it will help the industry to accelerate towards global competitiveness at a faster pace. By aligning the private sector advancements in technology and innovation with the national infrastructural goals, India can make great strides in creating jobs, last-mile connectivity and significant contribution to GDP.
