From recording to institutional practice.
Application of AI in Indian Railways
On 04 May 2026, I had the opportunity to deliver a two-hour webinar on “Application of AI in Indian Railways” for 170 railway officers and staff representing 18 railway zones and departments.
The session was moderated by Shri Mudit Anand, Senior Professor, IRITM, and focused on a question that is increasingly relevant across public institutions:
How can officers use AI to become more effective without compromising accountability, security or professional judgment?
The objective was not to overwhelm participants with technical concepts, but to make AI accessible, practical and relevant to their everyday work.
The session explored the core capabilities of AI and demonstrated how it can assist with tasks such as:
- Drafting and refining official communications
- Summarising lengthy reports and documents
- Analysing data and identifying patterns
- Reviewing tender documents
- Preparing inspection notes
- Prioritising incident responses
- Handling and analysing passenger complaints
- Processing staff representations
- Supporting financial and operational analysis
Through practical railway-related scenarios, the discussion demonstrated how AI can reduce the time spent on repetitive and information-intensive tasks, allowing professionals to focus more on analysis, judgment and decision-making.
At the same time, significant attention was given to what AI cannot do reliably.
AI does not possess the contextual judgment or institutional accountability of an officer. It can also produce inaccurate or misleading outputs, particularly when the underlying information is incomplete, ambiguous or incorrectly interpreted.
Therefore, the central message of the session was:
AI is a force-multiplier—not a decision-maker.
The officer's judgment, responsibility and accountability remain non-negotiable.
Responsible AI and Data Security
One of the most important discussions during the webinar concerned data security.
In a sensitive ecosystem such as Indian Railways, knowing what not to share with a public AI platform is just as important as knowing how to use AI effectively.
Participants were advised to exercise particular caution with:
- Passenger and personal data
- Financial information
- Internal and confidential documents
- Security-related information
- Sensitive operational information
- Unpublished organisational information
The session also highlighted the importance of using secure and approved platforms for government use cases.
Particular emphasis was placed on indigenous and government-focused digital initiatives and platforms, including BHASHINI, IndiaAI Mission tools, BharatGPT and RailCloud, as part of the broader movement towards secure and responsible AI adoption in public institutions.
AI Already Being Applied in Indian Railways
The webinar also discussed AI initiatives already being implemented within the railway ecosystem, including applications involving AI-enabled CCTV surveillance, automated announcement systems and AI-based solutions developed by CRIS.
These examples helped demonstrate that AI in Indian Railways is not merely a future concept—it is already becoming part of the digital transformation of railway operations.
From Awareness to Adoption
A key message throughout the session was that organisations do not need to transform overnight.
AI adoption can begin with small, practical and low-risk use cases.
Officers can start by identifying repetitive tasks where AI can assist, experimenting responsibly, evaluating the quality of outputs and gradually sharing successful applications within their teams.
I strongly believe that meaningful technology adoption happens when domain experts are actively involved in identifying and implementing use cases.
IT teams can enable the technology and provide the necessary safeguards, but officers who understand the operational realities of Indian Railways are often best positioned to recognise where AI can create genuine value.
The session concluded with an interactive discussion, with participants raising questions around practical implementation, data security and the challenges of introducing AI into railway operations.
The strongest takeaway from the session was simple:
AI can enhance productivity and support better decisions—but the final responsibility always rests with the human being.
I am grateful to Shri Mudit Anand, Senior Professor, IRITM, and IRITM, Lucknow, for providing this platform and to all 170 participants for their active engagement, thoughtful questions and willingness to explore how AI can be used responsibly in public service.