Pritam Deuskar on Why Industrial AI Will Create More Shareholder Value Than Consumer AI

 

The Artificial Intelligence investment has revolved mainly around chatbots, generative AI and consumer applications. But the bigger economic opportunity may emerge when AI moves from the screen into the physical economy—factories, machines, power networks and industrial infrastructure.

Let's get into the insights of Pritam Prabodh Deuskar, CIO, Wealthyvia Ventures and SEBI-registered research analyst, on how industrial Artificial Intelligence can directly improve productivity, utilisation, quality and costs, creating a clearer link between technology adoption and profitability, cash flows and ROCE.

The AI narrative has largely centred on chatbots, generative AI, search and consumer applications. But the more important investment question may be: what happens when AI moves from the screen into the factory? When applied to machines, production lines, power networks, logistics and industrial infrastructure, AI can directly improve productivity, asset utilisation and operating efficiency—making its economic impact far more measurable.

Consumer AI primarily monetises attention, engagement and software usage. Industrial AI, by contrast, improves the economics of businesses that already generate revenue. Predictive maintenance can reduce downtime, machine vision can lower rejection rates, production optimisation can improve throughput and energy-management systems can reduce costs. These improvements flow directly into profitability: better utilisation and productivity can increase output without proportional increases in assets, while lower downtime, wastage and energy consumption can expand margins, accelerate cash generation and ultimately improve returns on capital. A company therefore does not need to believe in AI as a concept; it only needs to demonstrate that the technology improves its economics.

Industrial AI can also create more defensible value because it sits within physical processes. Once AI is integrated with machinery, production systems or industrial workflows, replacing it can involve operational disruption, retraining and significant integration costs. The ecosystem extends from sensors and IoT to robotics, machine vision, industrial software, edge computing and AI models. Digital Twins further connect the physical and digital worlds by creating virtual representations of machines or factories that can use real-time data to predict failures, identify bottlenecks and optimise processes.

India could be particularly well positioned for this transition. The country is simultaneously expanding manufacturing capacity and seeking higher global competitiveness across electronics, automotive and EVs, aerospace and defence, pharmaceuticals, heavy electricals, renewable energy and precision engineering. Its combination of software expertise, engineering talent, ER&D capabilities and a growing manufacturing ecosystem creates a strong foundation for Industrial AI.

The opportunity therefore extends beyond companies selling AI software. Data centres and computing infrastructure provide the underlying capacity; sensors, robotics and automation create the physical intelligence; engineering and industrial software integrate these technologies; while manufacturers capture the benefits through higher productivity and margins.

More importantly, Industrial AI can create a broader investment cycle. Greater au tomation increases demand for sensors, connected equipment and computing; more connected equipment generates more industrial data; and more data improves AI-driven optimisation. As productivity rises, Indian manufacturers can become more competitive globally, encouraging further investment in capacity and technology. AI therefore has the potential to accelerate India's broader industrial transformation rather than operate as a standalone technology theme.
Investment Conclusion

India's most valuable AI opportunity may not be another consumer application; it may be the intelligence layer transforming the country's physical economy.

As factories, infrastructure and industrial systems become increasingly automated and connected, the companies that successfully apply AI can improve utilisation, productivity, quality and cost efficiency—ultimately strengthening cash flows and ROCE.

For investors, the more important question is therefore not “Which company will build the next ChatGPT?” but “Which companies will use AI to make factories and industrial systems dramatically more productive?”

The answer could create a new generation of Indian compounders.

“Industrial AI has the potential to convert technological progress directly into measurable improvements in productivity, profitability and capital efficiency, making it a potentially more tangible and durable long-term investment opportunity than consumer AI.” - Pritam Deuskar, Wealthyvia Ventures

About Pritam Deuskar

Pritam Prabodh Deuskar is a SEBI-registered research analyst. Pritam has worked in stock market research and business analysis for many years. He had earlier worked with reputed portfolio management companies and PMS houses. His views, interviews and articles have been published in all leading financial newspapers and TV channels like CNBC, CNBC Bazaar, Moneycontrol, Economic Times, Business Standard and so on. Pritam Deuskar is known for small and mid-cap multibagger companies and finding them at a very early stage has been his forte. He has worked with HNI and Institutional clients.


About Wealthyvia Ventures




Wealthyvia Ventures is a SEBI-registered AIF Category III Fund headquartered in Mumbai. The firm is dedicated to delivering high-quality public market investment solutions to Ultra-high-net-worth individuals (UHNIs), Family offices, Institutions, and Fund of funds.