By Sreyashi Bhattacharya

Copyright techgenyz

AI Empowerment in Railways: In 2025, Indian Railways integrates AI for smart ticketing, fraud prevention, and multilingual assistance through Aadhaar authentication and the BHASHINI AI engine.Smart Operations & Crowd Management: AI-driven video analytics, behavior detection, and predictive models enhance passenger safety, optimize crowd flow, and improve real-time decision-making in major stations.Opportunities & Challenges: While AI boosts efficiency, inclusion, and safety, concerns remain around privacy, technology reliability, and ensuring accessibility for all passengers.

India’s railway system carries millions on a daily basis, and logistical engineering has created a monumental undertaking for ticket booking, crowd flows, police and safety operations, and multilingual users of this service to navigate. Fast forward to 2025, through artificial intelligence and allied technologies will be usefully embedded into a railway system to decrease complexity in bookings, manage crowds, limit fraud, and improve the comfort of riding as a passenger . This feature discusses the application of AI in India today in smart ticketing, crowd control, and station operations.

Functions, Policy-, and Technological Events

The BHASHINI multilingual AI engine (government-sponsored) is being built into railway systems (e.g. NTES, RailMadad) in order to cater language use in queries. From 2025, IRCTC App outlined a mandate for Aadhaar authentication for online ticket bookings with the intention of decreasing fraud and duplicate bookings. Additionally, through use of Aadhaar as an authentication application, will allow Indian Railways to enforce accountability for momentarily claimed seats.

As a programmatic response to the Digital India / IndiaAI mission has led to expanded landscapes of compute and AI infrastructure.

Smart Ticketing and Fraud Prevention

1. Aadhaar Integration and Authentication

As mandated by the Indian Railways, the verification of Aadhaar via biometric or OTP (mobile number associated with the Aadhaar) will imperatively change ticket bookings on IRCTC. This new systems is for fraud and duplicate bookings and can help protect quotas (Tatkal) more effectively who purchase Taktal tickets immediate from the computer system.

Using Aadhaar in the system also may significantly contribute to accelerating KYC process while ensuring accountability expected from a service system operated by government but also increases privacy and exclusion risk (when users do not have an Aadhaar-mapped mobile or biometric system to access).

Predicting Demand & Dynamic Pricing

AI-driven models are increasingly being deployed in the railway sector to predict passenger demand on popular routes, during peak seasons, and around festivals. These systems leverage historical booking data, travel trends, and special event calendars to estimate seat availability, suggest quotas, and forecast waitlist probabilities. Some modern ticketing interfaces now provide users with near real-time predictions for the likelihood of waitlist clearance, offering transparency and aiding travel planning (Source: [Indian Railways Digital Initiatives, Press Releases]).

To combat bulk booking and automated fraud, especially under high-demand schemes like Tatkal, AI-based pattern recognition tools are employed to identify suspicious booking behavior. These models analyze transaction sequences, booking intervals, and user activity patterns to flag anomalies. Graph-based fraud detection techniques, commonly used in Indian fintech, are also being adapted to the railway booking ecosystem, enabling proactive monitoring of coordinated or high-volume booking attempts. Human validation and computerized checks ensure that flagged transactions are verified before final confirmation (Source: [Railway Ministry AI Deployment Reports, 2024–2025]).

Crowd Control & Station Management

1.Video Analytics & Density Mapping

Major stations can now run AI-based CCTV analytics that could monitor crowd density, alert control rooms to crowds becoming overcrowded, à la monitor flow and redirect flow, open another gate, or restrict access. For events occurring closer to the now remote peer (Kumbh, festival season, etc.) AI capability to also help predict and control.

2. Behavior Detection & Anomaly Alerts

AI models also can monitor for identifiable behaviors by scanning camera feeds to produce alerts for undesirable/theat behavior to determine whether human interference, if that event occurs (ate hit not responding) numerous possible alerts for “luggage / bags unattended” to lingering dudes or ladies in restricted zones, etc. Alerting security personnel to investigate seems appropriate, especially when there are a reasonable supply of “much-needed” humans to investigate alerts.

3. Multilingual Assistance for Passengers With BHASHINI, announcement systems, helplines, and chatbots can assist in multiple Indian languages in stations and trains. Automated chat or voice bots (through multilingual AI), can help passengers with platform information, delays, connecting trains, via any language.

Case Studies & Pilot Testing

In select large junctions (e.g, New Delhi, Mumbai), we are already using density analytics to re-rout passengers during peak load times. During festivals or religious gatherings (such as in Nagpur at Deekshabhoomi), city police used drone technology + AI + CCTV to monitor various crowds; rail stations generally coordinate during such large gatherings. The integration of BHASHINI to the National Train Enquiry Systems (NTES) and RailMadad, is in advanced testing.

Benefits and Risks

Benefits: Better crowd safety, fewer stampede events or dangerous over crowding

Lower booking fraud, duplicate usage

More inclusive access, via languages.Resource allocation based decision making (staffing, security, platform usage)

Risks / Concerns:

Privacy / surveillance creep: excessive video watching, facial recognition, aadhaar-mapped… raising civil liberties issues.

Reliability of technology: false positives or failure to detect anomalies

Exclusion: individuals not having Aadhaar-mapped mobile phone numbers, or biometric mismatches, could be excluded

Change management within operations: training required for station staff and controllers; integrating across existing systems is administratively difficult.

What to expect and what is new

These are plausible as future plans or pilot ideas, but not yet widely confirmed:

Scaling AI-based control systems to smaller stations and rural operations.AI-enabled predictive maintenance of tracks, signals, rolling stock.Real-time translation and assistance through voice assistants in trains.Dynamic allocation of quotas at a more granular level using AI forecasting.Exploration of XR/AR for navigation assistance for people entering platforms.

In 2025 Indian Railways is realizing a contemporary inflection point. AI is now more than a concept, as it is being deployed to improve ticketing security, multilingual access, and crowd safety in major stations. The subsequent journey will be the navigation between technology potential, citizen rights and delivery across a vast and diverse railway system in India. But, if executed appropriately, the combination of AI, privacy, and humans, could create a new transportation future for inhabitants of India, who travel via the railway system.