Artificial intelligence in Aviation Market Trends

Growth Drivers

• Rising adoption of latest technologies - With the lucrative global population along with the boosting economies, there is also a significant demand for the adoption of the latest technologies to ease out the service and make the operations smooth. According to a recently published report, digital airports are growing at a surge with more than a 10% increase in domestic airports and about a 5% increase in international airports.
• Slated investments in aviation - There is an increase in capitalist investments, especially in the aviation industry, which will increase the demand for artificial intelligence in the aviation landscape. According to a report, the Airport, Authority of India is predicted to invest more than USD 3.58 billion in the coming years, mainly for the betterment of infrastructure and facilities at the airport.
• Slated usage of cloud-based technologies - As Airways is not counted as an important medium of automotive & transportation worldwide, this demand for a cloud-based service is for the ease of travelers as well as the users. According to a report, more than 94% of organizations and enterprises have upgraded to cloud computing services. Moreover, there was a drop of about 40% in the costs of infrastructure ownership after cloud technology came into the picture and further spread.

Challenges

• Dependency on an Internet connection - AI systems require real-time data processing coupled with communication, as they completely rely on Internet access, which has to be uninterrupted. In several airspace-constrained or remote regions, connectivity may be intermittent or limited; due to this, the effectiveness of AI applications can be hindered. This dependency can alter several functions, such as weather monitoring, communication, and flight planning with ground control.
• Limited availability of professionals - The implementation and development of AI solutions, especially in the aviation landscape, require specialized expertise in both aviation operations and AI technologies. However, this domain remains relatively specific, which results in the scarcity of several qualified professionals. This could alter the timely optimization and deployment of AI applications in aviation, which leads to delays, suboptimal performance, and increased costs.