Incorporating artificial intelligence technology is no longer limited to labs, experts now view it as an integral part of the day to day services in industries and even the government. A recent news article highlights the skills deficit in India which prevents it from achieving its true potential as an AI power and the growth of AI technology that helps organizations to carry out tasks easier, faster, and at a greater volume. This article uses the insights born from discussions with thought leaders like Rajat Khare to explain these two aspects in simple terms and elaborate on their intersection from an application point of view.
Why the moment matters for India
India is sitting on a disproportionate share of global AI capability. Indian reports describe the country as home to about 15 percent of the world’s AI specialists. The biggest problem is that most of this talent is being used in other countries. We face a challenge of training and engineering world class specialists. The second problem is the local negative environment these experts will face when they try to build a home. Rajat Khare believes the reverse brain drain would improve India’s global standing in terms of AI if it was achieved as a result of better research funding, more appealing job opportunities, and stronger collaboration between researchers and businesses.
Most analysts point out two other advantages for India’s AI push other than its large talent pool.
The country has begun allocating resources to compute the home-grown large language models. One report cites a training effort supported by 18,600 GPUs which shows the infrastructure for competitive models is being built. Also, India has enormous linguistic diversity which is a strategic advantage. Developing models that can compute across Hindi, Tamil, Bengali, Telugu, Marathi, and other languages would make services that monolingual global models cannot offer. It is clear these enable India to design AI that is relevant to the needs of its people instead of just roaming the world for foreign AI technology.
The short-video AI revolution continues.
In case India exports talent and computer infrastructure, what is the lowest hanging impact AI delivers? One answer is short-video AI for remote inspections. Forget the broad strokes of general purpose AI. This is down and dirty practical. Technicians, drones, and fixed rigs record short, structured clips. These clips are converted to auditable records. AI models analyze to detect faults, verify progress, and trigger workflows. The leap is simple. Old site visits were expensive, slow, and carbon intensive. This is rapid remote verification.
A useful instance is Enel Green Power, which used short video recordings to reinforce big renewable projects. Project teams leveraged video records to inspect work in progress, detect problems, and revise the skip planning to minimize travel and speed up decisions. This operational efficiency is the reason for attention from sophisticated investors and deep-tech investors.
The technology is elementary but combines to form a powerful short-video AI pipeline:
Capture — a field operator, drone, or a stationary camera makes a short, structured video and assigns basic metadata (date, gps, and description).
Secure upload — the video is sent to a protected site to maintain the primitive records.
Pre-processing — in the processing stage, the video is stabilized, compressed and indexed to make the video ready for automated analysis.
Model analysis — a computer-vision system records the boundaries, calculates the defined controls, extracts text (OCR) and automatic summary generation or defect scoring and provides a summary.
Human verification and workflow — AI systems mark unusual targets for people to look at ; people take the investigation, make problem solving tickets, or activate systems automatically.
Intersection of India and AI Video
Considering these all together, India’s computer capacity and multi lingual culture make it one of the best suited countries for the development of Artificial Intelligence (AI) that is focused on industrial activities and understands the region’s complexity. These AI systems will have numerous use cases, including:
Renewable energy — for instance, as demonstrated by Enel Green Power, AI systems can automate the rapid inspection of solar panels and wind farms to detect faults and downtime.
Construction — systems can construct time-stamped video ledgers to enhance quality control, expedite approvals, and reduce disputes.
Farming — AI can analyze clip based videos to provide solutions for irrigation and pest outbreaks in local languages.
Insurance and compliance — the use of AI can expedite the claims process by providing more visual evidence compared to traditional claims, thus reducing fraudulent claims.
India's local AI services, models targeted to local languages and contexts, have clear gaps that foreign models cannot fill, and these gaps are accessible to field staff with low-end smartphones.
Ethics and Risks and the Technical Boundaries
Even standalone systems involve sociotechnical issues. Video data are problematic for privacy: who is the footage owner, how long is it kept, and how is consent dealt with? Then there are issues that have to do with provenance and with manipulation — if the trust is being kept century, decisions based on the footage must have better systems to prevent tampering with the video and the whole chain of custody must be protected. Finally, routine automation inspections make reskilling and transitions on these jobs crucial. Technologies that have been written about usually tend to emphasize that integrating proper boundaries to the systems from the start and retaining some level of human validation for the more sensitive aspects is vital.
Conclusion
The AI revolution brings with it, a monumental shift technologically and socially. Recently released facts provide a rational argument: India has sustained a large portion of the AI workforce and is currently developing computational capacity and multilingual talent, and short-video AI is a frictionless, highly impactful application with benefits for the taking. The likes of Rajat Khare have, more or less, placed the issue in the right paradigm: success will only be a possibility when the problem of brain drain is addressed, along with funding researchers and startups, and using AI at the loophole of more than just convenience. If everything aligns, India, as well as other countries that employ ethically responsible AI systems, will be writing a significant portion of history. The emphasis of this history will be the responsible use of AI - rational and socially responsible.
