GenAI Doesn't Always Fit Low-Cost Economies: NTT DATA Almost 65 per cent of tech-enabled MSMEs report a lack of awareness about the deployment of AI tools and resources as the top challenge in adopting AI technologies.

While generative AI (GenAI) is delivering tangible efficiency gains, its implementation is a difficult task for low cost economies. Jan Wuppermann, SVP & head of data & AI in APAC, emphasized that cost and infrastructure remain hurdles in markets like India and Southeast Asia. "GenAI can be expensive to run (large models and GPU requirements) and it doesn't always fit with the low-cost structures these economies are built around," he explained. "Private AI is gaining traction as a cost-effective, data-secure alternative."

Talking about GenAI's adoption in India, particularly among MSMEs, John Lombard, CEO, Asia Pacific, NTT DATA, observed that while the challenges aren't entirely unique to India, the "post-pilot resistance" is real. "Some early adopters ran GenAI pilots that didn't pay off, and now there's skepticism. It's no longer about shiny tech, it's about impact on the factory floor. Many rushed into GenAI pilots early on, got their fingers burned, and pulled back. Now, they're reassessing. There's no surprise GenAI is delivering bottom-line results, but challenges like legacy infrastructure and lack of formal AI policies are slowing progress."

For instance, sectors such as manufacturing remain hampered by outdated infrastructure, workforce capability gaps, and lack of robust governance frameworks, when it comes to GenAI implementation. Regulatory pressure, coupled with global supply chain volatility and shifting customer demands, are pushing manufacturers to act. The absence of strong industry networks and peer mentorship programs is also a major obstacle for tech-enabled MSMEs in India, hindering their ability to share knowledge and learn from each other.

As per a survey report by Nasscom, 65 per cent of tech-enabled MSMEs report a lack of awareness about the deployment of AI tools and resources as the top challenge in adopting AI technologies. This lack of awareness hinders their ability to identify suitable AI solutions and effectively integrate them into their business processes. "As much as 57 per cent of tech-enabled MSMEs struggle with a shortage of technical expertise necessary for implementing AI solutions. This skill deficit hampers their ability to fully utilize these advanced technologies, as they often lack the in-house capabilities to develop, integrate, and manage AI systems," the report said.

That said, the outlook for India is promising. "India is investing. The government has laid out a national AI strategy and is partnering with private enterprise to build the infrastructure," Lombard said. "In many ways, India's strategic thinking is ahead of other countries in the region."

As per a report by NTT DATA, the numbers speak volumes. A surveyed 95 per cent of respondents said GenAI is already improving efficiency and profitability, with 94 per cent expecting the integration of IoT data to enhance the accuracy of AI outputs. In APAC, these figures were even higher, at 97 and 99 per cent respectively.

Both Lombard and Wuppermann reiterated infrastructure limitations, fragmented approach to Cloud adoption, and the need for upskilling as persistent issues for regional challenges in APAC and India.