UST Malaysia Turns to Local SMEs and Manufacturers as AI Adoption Picks Up

A technology company that has spent two decades serving multinationals from Malaysia now wants local businesses as customers. In an interview with StarBiz published on Monday, 19 October 2026, UST Malaysia vice-president and country head Amar Chhajer said the company plans to work with more Malaysian manufacturers, banks, government agencies and small and medium enterprises (SMEs) as they adopt artificial intelligence (AI) and automation.

UST has operated in Malaysia since 2006, providing digital transformation services to multinational clients, including major American semiconductor companies, banks and tech firms. Its Malaysian operation is now the group's third-largest global delivery centre, with about 1,600 staff, 87% of them Malaysians, and more than 10,000 people have gone through its training over the years.

From importing skills to building them locally

Amar recalled that on a specialised manufacturing software project in 2011, about 35 of roughly 40 people involved at one stage were expatriates, because the skills were hard to find locally. Since then, he said, UST Malaysia has grown its own pool of niche engineering talent in semiconductor design, software engineering, cloud computing and cybersecurity, which it now wants to put to work for local firms.

Where SMEs can start with AI

Amar argued that AI is not just for large corporations, since smaller businesses can gain efficiency without big infrastructure budgets or large development teams. He said generative AI can help level the playing field:

"In fact, it's easier for an SME or a startup to get more done in the age of generative AI than they could do earlier." Amar Chhajer, UST Malaysia, speaking to StarBiz

The practical uses he listed for SMEs were:

• Automating replies to customer enquiries
• Processing invoices
• Preparing quotations
• Managing inventory
• Improving sales forecasting

For manufacturers, he described physical AI applications UST is developing that could let one operator oversee 10 machines instead of five workers handling the same number, which could reduce reliance on foreign labour. He also stressed that AI should support experienced engineers rather than replace their judgement, and that the real challenge is connecting AI to core systems such as finance, inventory, production and customer platforms, not just running trials.

What this means for Malaysian readers

The list of SME use cases is a useful checklist because none of it needs a huge budget. Enquiries, quotations and invoices are high-volume, repetitive tasks where small time savings add up every week. Amar's closing advice is worth following too: start with a specific operational problem you can measure, rather than buying a large AI project with no clear goal.

His other point, that AI cannot scale when it is cut off from your business data, is the part many small firms overlook. If customer records, stock levels and invoices still live in scattered spreadsheets and chat threads, the first step is often getting those into a proper system so that automation has something reliable to work with. With Budget 2027 setting aside money for SME digitalisation and AI adoption, this is a good time to map out which process to fix first.

Source: The Star (StarBiz), "UST Malaysia targets local firms as AI adoption gains momentum", by Kirennesh Nair, 19 October 2026. This article is an independent summary and commentary by R4XN.