AI's biggest business value lies in solving problems that companies didn't know how to solve: Anthropic India MD
Artificial intelligence offers significant business value by solving complex problems. Frontier AI models create the most value when applied to intelligent and domain-specific challenges. Companies can unlock new value in sectors like healthcare a...

Speaking at 'Fireside Chat on AI Native Markets: Driving the Next Era of Financial Advantage' at the Global Fintech Fest 2026 in Mumbai, Ghose said frontier AI models can create the most value when businesses apply them to problems that require a high degree of intelligence and domain understanding.
"At the highest end, the intelligence when you put across to the largest complex set of problems is what defines what the ROI is kind of coming across from," Ghose said.
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She said frontier models such as Claude can be particularly valuable in areas where companies are dealing with complex or unexplored problems, rather than simply using AI for routine automation.
"When you look at the frontier models, Claude really shines across, when you look at discovering, doing things which you don't know," she said.
Ghose cited healthcare and banking as examples where AI could unlock new value. In healthcare, she pointed to areas such as drug discovery, while in banking, she highlighted the large volumes of legacy code that remain untouched in many institutions.
"Look at this, the legacy code even the conceptualisation of it, which would have taken months which would have taken a very high level of experienced users to do it, can now be done in days," she said.
According to Ghose, this ability can also democratise access to specialised expertise by allowing employees who may not have decades of experience with a particular system to work with complex technological problems much faster.
"Frontier AI can make that context available to people who've not possibly dealt with the experience and can start doing it very quickly," she said.
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Her comments come as enterprises increasingly move their AI strategy beyond experimentation towards applications aimed at measurable business outcomes. The Global Fintech Fest 2026 has placed agentic AI among the technologies expected to reshape financial services and enterprise workflows.
Ghose also argued that businesses should look beyond conventional efficiency metrics when assessing AI investments. While productivity gains can create additional capacity, she said companies should use that capacity to pursue innovation and new growth opportunities.
"Efficiency is bringing in headroom for capacity for innovation," Ghose said, adding that companies should also measure whether AI is helping them pursue "those big rocks or the large moon shots" that can drive growth.
The shift is significant for businesses as AI adoption moves from the question of what the technology can do to where it can create material economic value.
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