Air India Crash Raises Questions About AI Safety Measures

Air India Crash Raises Questions About AI Safety Measures

The recent crash of Air India Flight 171, a Boeing 787 Dreamliner, has reignited urgent concerns regarding airline safety and the adequacy of current safety protocols. The disaster, which resulted in the deaths of at least 270 people after the aircraft collided with a hostel block at BJ Medical College in Ahmedabad, marks the deadliest aviation accident worldwide in the past decade. With only a single survivor, the tragedy has intensified public anxiety and prompted renewed scrutiny of both Air India and Boeing.

Safety Challenges and Public Trust

Since its debut 14 years ago, the Boeing 787 Dreamliner has encountered multiple safety challenges. Data from the Aviation Safety Network reveals that six incidents in 2025 alone were attributed to technical difficulties involving this aircraft model. While human error has traditionally been the primary cause of aviation accidents, the increasing frequency and scale of recent incidents have led experts and the public to question whether advanced technologies—particularly artificial intelligence (AI)—could play a more significant role in preventing such catastrophes.

The repercussions of the crash extend beyond the immediate loss of life. Research by Skift indicates that 51% of Indian travelers now avoid certain airlines due to safety concerns, signaling a substantial erosion of public confidence. The incident is also expected to tighten conditions in the aviation reinsurance market, with insurers and reinsurers both in India and internationally reassessing their risk exposure, according to GlobalData. For Air India, the tragedy presents a formidable challenge to its Vihaan.AI transformation program, which aspires to position the airline as a “world-class global airline” within five years.

The Role of AI in Aviation Safety

In response to mounting demand and increasingly stringent regulations, Boeing and other aircraft manufacturers have progressively integrated AI-driven solutions to enhance safety and operational efficiency. Technologies such as robotics, AI-based analytics, digital twin systems, and machine vision have become central to aircraft manufacturing and maintenance processes. A recent study titled “Artificial Intelligence in Aviation Safety: Systematic Review and Biometric Analysis” underscores how AI is revolutionizing aviation safety through predictive analytics, real-time monitoring, and proactive risk management.

Machine learning algorithms are capable of analyzing vast datasets to identify patterns and forecast potential safety issues before they escalate. Alexis Lope-Bello, CEO of ComTrade Group, noted that “machine learning—anomaly detection is a mature and well-understood technology with a proven positive impact.” He emphasized that when applied to aviation, such technologies can significantly enhance safety, improve service quality and reliability, reduce maintenance costs, and boost operational efficiency.

AI also aids decision-making for pilots and air traffic controllers by improving the speed and accuracy of critical judgments. Predictive maintenance powered by AI enables airlines to detect and address mechanical problems early, thereby reducing the risk of in-flight failures. Furthermore, data science and big data analytics are increasingly vital in optimizing aviation safety, with techniques such as Natural Language Processing (NLP) helping to identify human factors in accidents and minimize errors.

Ongoing Investigation and Future Imperatives

As investigations into the Air India Flight 171 crash continue, the tragedy highlights the imperative for proactive safety measures. Experts stress that solutions must be developed and rigorously tested before failures occur, rather than in response to loss of life. Although air travel remains statistically one of the safest modes of transportation, this incident underscores the necessity for continuous innovation and vigilance to maintain public trust and ensure passenger safety amid rapid technological advancements.