Founders say New Delhi should stop benchmarking itself against US–China model wars and double down on orchestration, affordability and ROI-led AI
As the global artificial intelligence race is increasingly framed as a contest over trillion-parameter foundation models, Indian industry leaders are urging a strategic recalibration arguing that India’s competitive advantage lies not in replicating US or China’s model-building muscle, but in mastering the application and orchestration layer.
At the India AI Impact Summit, founders told Firstpost that comparisons with the United States and China often overlook India’s structural strengths: cost engineering, systems integration and large-scale deployment across complex, multilingual markets.
“You have to compare apples with apples and oranges with oranges,” said Raj K Gopalakrishnan, CEO and Co-Founder of KOGO AI. “India is very strong in the orchestration and application layer. Foundational model development is stronger elsewhere.”
From models to money
Foundation models, such as large language models and other advanced AI systems trained on huge amounts of data, need billions of dollars in computing power and expensive, high-end chips to build and run.
In contrast, application-focused companies use these existing models to create practical tools, such as AI assistants, automation systems and industry-specific solutions, that help businesses improve efficiency, increase revenue and solve real-world problems.
“Agentic systems and AI applications create real value for the end user. That is where the business case lies,” said Angad Ahluwalia, Chief Spokesperson at Arinox AI.
Industry leaders argue that while global headlines focus on model size, enterprises ultimately pay for productivity gains, efficiency improvements and revenue expansion—not for parameter counts.
The Mars analogy
Speakers invoked India’s space programme to illustrate the country’s frugal innovation model. Referring to India’s cost-efficient Mars mission, Raj argued that the same philosophy applies to AI.
“We sent a rocket to Mars at a fraction of global costs. Similarly, India can build small language models and nano models at 1/100th the cost,” he said, suggesting that India’s focus on smaller, domain-specific models could prove more commercially viable than chasing ever-larger systems.
From experimentation to implementation
Executives from Beyond Key, including Growth Manager Ananya Sharma and AI Solution Architect Vishal Gupte, said India’s AI ecosystem is now moving decisively “from experimentation to implementation.”
“AI is no longer optional,” Sharma said. “With Industry 4.0, automation and smart factories, AI becomes mandatory.”
According to him, India’s strength as a global IT services hub gives it a natural advantage in integrating AI into enterprise workflows at scale. Small and medium enterprises (SMEs), he added, will play a pivotal role in driving grassroots adoption, particularly as competitive pressures intensify.
Gupte said that innovation is no longer confined to large corporations. “We are seeing startups building practical applications in agriculture, education and public services. These may look small today, but they are very close to real-world usability,” he said.
People-centric, not behind
Founders also addressed criticism that India’s “people-centric” AI push—focused on agriculture, education and digital public infrastructure—could leave it trailing corporate-heavy AI ecosystems in China and the US.
“Why should people-centric and tech-centric be mutually exclusive?” Raj asked. “AI ultimately serves human systems.”
Ananya Sharma added that integrating AI into digital public platforms could widen the adoption base and create long-term structural advantages. “If AI is embedded across governance, education and industry simultaneously, that’s a more balanced ecosystem,” he said.
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