Artificial intelligence adoption among venture capital and private equity-backed firms jumped to 71 per cent this year in Bangkok, up from 39 per cent a year earlier.
The headline surge conceals narrow implementation, with only 17 per cent of surveyed companies embedding artificial intelligence into their core business operations.
Data released by the International Finance Corporation at the IMF-World Bank Annual Meetings shows that more than half of adopting businesses still restrict deployments to isolated operational functions. The survey sampled 1,600 private equity and venture capital firms to evaluate how early-stage and portfolio enterprises deploy automated tools. Improved productivity ranked as the primary driver, cited by 54 per cent of respondents, yet operational bottlenecks persist across developing markets.
Skills Shortages and Local Integration Bottlenecks
Human capital constraints remain the primary hurdle to enterprise rollouts across emerging regions. More than 40 per cent of non-adopters identified acute skills shortages as their primary barrier, while broader institutional capacity deficits continue to stall deployments outside basic software tools.
Enterprise operators in Southeast Asia and South Asia frequently encounter tools designed for Western data sets and cost structures. Without local tuning, generic generative platforms fail to handle regional dialects, local commercial registries, and fragmented banking APIs. The practical value for regional businesses depends on engineering lightweight, localized models rather than purchasing expensive enterprise subscriptions that internal teams cannot maintain.
Cross-Border Payments and Merchant Infrastructure
Fintech operators are focusing on targeted agents to resolve transaction delays for small and medium-sized enterprises. Cross-border payments and remittance channels across developing corridors remain plagued by settlement delays and excessive processing fees.
Adeola Adewede, founder and chief executive of fintech platform Kredete, stated that autonomous AI agents configured for local language context and cost structures can transact on behalf of regional merchants across borders, lowering operating costs and speeding liquidity cycles.
Medical Imaging and Regulatory Clearance
Healthcare deployment demonstrates a similar pattern of targeted edge utility versus administrative obstruction. In India, medical imaging platform CARPL has deployed portable X-ray units powered by laptop-based AI models to screen populations for tuberculosis and breast cancer.
CARPL founder and chief executive Vidur Mahajan noted that the platform maintains an ecosystem of more than 300 imaging applications for hospitals. However, ambiguous medical software regulations across emerging markets delay rollouts, prompting industry calls for regulators to streamline domestic approvals for diagnostic algorithms already certified in developed economies.
On-Device Intelligence and Hardware Integration
Hardware providers argue that long-term productivity gains require local processing rather than continuous cloud connections. Running machine learning models directly on laptops, vehicles, and connected hardware eliminates latency and lowers connectivity costs for small businesses.
Veerabhan Kheterpal, co-founder and chief executive of semiconductor IP licensing company Quadric, noted that building intelligence directly onto devices allows systems to generate customized software adjustments in real time, expanding operational capacity for small enterprise operators.
Commercial focus now shifts to whether portfolio companies can convert functional experiments into revenue-generating workflows before early investment capital runs dry.
