PETALING JAYA: After over two decades of building its technology and engineering capabilities in Malaysia to serve multinational clients, UST Malaysia is looking to expand its reach among local businesses, particularly in helping them adopt artificial intelligence (AI) and automation.
UST Malaysia vice-president and country head Amar Chhajer said the company wants to work with more Malaysian manufacturers, financial institutions, government organisations and small and medium enterprises (SMEs), particularly as they look to adopt AI to improve productivity.
“Although we have not been working with a lot of government organisations, local banks or local manufacturers, that is what we want to change.
“We want to participate in this journey of bringing AI adoption,” he told StarBiz.
UST has operated in Malaysia since 2006, providing digital transformation services to multinational corporations, including major American semiconductor companies, banks and technology firms.
Its Malaysian operations have grown into the group’s third-largest global delivery centre, employing about 1,600 people, 87% of whom are Malaysians.
More than 10,000 people have also undergone training through the company over the years.
Amar said building this talent base required years of investment, particularly as specialised engineering skills were initially difficult to source locally.
Amar recalled that when UST Malaysia worked on a specialised manufacturing software project for an American technology company in 2011, it relied heavily on expatriate engineers due to a shortage of specialised skills locally.
Of the roughly 40 people involved at one stage, about 35 were expatriates brought in from countries including India, the Philippines, the United States and Europe.
Over time, UST Malaysia developed local talent to take on more specialised engineering work, supported by the local ecosystem and efforts to build up its skilled workforce.
“What we have created is a lot of niche engineering talent workforce,” he said.
Amar said the company’s Malaysian operations have developed specialised capabilities in areas such as semiconductor design, software engineering, cloud computing and cybersecurity, which can now be applied to the needs of local businesses.
He noted that UST Malaysia already undertakes complex engineering projects for international clients, including companies that do not have a physical presence in the country.
The company now hopes to leverage that experience to help more Malaysian manufacturers, financial institutions and SMEs adopt AI and other technology solutions to improve productivity and modernise their operations.
Amar said UST’s global customer base provides access to technology solutions and industry practices that could be adapted to the Malaysian market.
He said this experience, together with partnerships with technology and software providers such as Anthropic, Salesforce, SAP and Workato, could help Malaysian businesses move beyond experimenting with AI towards deploying it across their operations.
Amar said the benefits of AI are not limited to large corporations, as smaller businesses could also use the technology to improve efficiency without having to invest heavily in technology infrastructure or large development teams.
He believes generative AI could help level the playing field between SMEs and larger companies by making technology development and automation more accessible.
“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,” he said.
For SMEs, he said potential applications include automating customer enquiries, processing invoices, preparing quotations, managing inventory and improving sales forecasting.
These are areas where businesses could achieve productivity improvements without having to overhaul their entire operations.
Asked how AI could improve productivity and quality in Malaysia’s manufacturing and semiconductor sectors, Amar said the country was “well positioned” to benefit, given the sectors’ data-rich and engineering-intensive operations.
However, he noted that the opportunity was not limited to a single use case.
He said AI can support the entire value chain, from product and process engineering to factory operations, quality management, maintenance, supply chain planning and customer fulfilment.
“The value is highest when AI is combined with strong operational data and connected to the systems that manage production, maintenance, inventory, quality and logistics,” he said.
“UST’s role is to bring together digital engineering, manufacturing transformation, AI and integration expertise.”
One area of opportunity is the use of AI in manufacturing, where automation could allow companies to operate more machines with fewer workers.
Amar said UST is developing applications using physical AI that could enable one operator to oversee 10 machines, compared with a setup requiring five workers to manage the same number.
Such applications could help manufacturers mitigate their dependence on foreign labour while improving productivity, he said.
Against this backdrop, Amar said UST’s partnership with Critical Manufacturing was relevant as it combines the company’s AI and engineering capabilities with a platform designed for semiconductor and electronics manufacturing.
He said the collaboration is intended to help manufacturers modernise production, connect factory systems and improve operational visibility across South-East Asia and India.
Amar claimed that UST’s semiconductor validation platform, iDEC, can also automate validation workflows and reduce engineering cycle times by 50% or more, depending on the client’s environment and deployment scope.
“The critical point is that AI should complement experienced engineers and help them focus on more complex decisions, rather than be treated as a replacement for engineering judgement,” he noted.
While many companies have begun testing generative AI, Amar said the challenge is integrating the technology into existing “core business operations” to deliver measurable improvements.
“That is where UST can play a role. We work with organisations from strategy and use case identification through to engineering, integration, implementation, governance and ongoing operations,” he said.
“AI cannot scale effectively when it is isolated from enterprise data, customer platforms, finance systems, supply chain applications, manufacturing systems or employee workflows.”
He said businesses should begin by identifying specific operational problems where AI could deliver measurable improvements, rather than pursuing large-scale implementation without a clear business objective.
