Stop Chasing the Shiniest Tool — Start Measuring What Matters

 

 

As Thailand's economy stalls, MFEC chief Siriwat Vongjarukorn urges organisations to ditch tech for technology's sake and embrace AI that pays for itself from day one.

 

 

Thailand finds itself in an uncomfortable position. GDP growth languishing below two per cent — the weakest in ASEAN; a stagnant domestic market; and a workforce caught between the promise of artificial intelligence and the paralysis of not knowing quite what to do with it.

 

Against that backdrop, Siriwat Vongjarukorn, chief executive of MFEC, has a blunt prescription for local organisations: stop buying technology, and start buying outcomes.

 

"It is no longer about which technology is the best or the most famous," he says. "You have to buy the technology that is most appropriate for you — the one that actually works for your situation."

 

The distinction matters enormously in the current climate. For years, the conventional wisdom held that investing in the boldest platform would eventually pay dividends. That logic has quietly collapsed. When revenues are flat, Siriwat argues, rising technology costs do not sit alongside profitability — they race ahead of it.

 

"When the cost of technology overtakes your net profit, IT stops being a weapon and becomes a burden," he warns.
 

 

 

 

 

 

The Promptless Imperative

MFEC's own experience selling AI over the past two years crystallised the problem. Clients purchased licences, attended training sessions, and waited for productivity to arrive.

 

It rarely did — not because the technology failed, but because adoption did. Thai employees, Siriwat observes, share a cultural tendency: when they do not understand something, they stay silent rather than asking for help. When pushed, they resist.
 

 

 

 

 

The company's response was to rethink the model entirely. Rather than expecting staff to master prompting, MFEC began packaging AI capabilities into what Siriwat calls "mini-apps" — purpose-built tools embedded directly into existing workflows, requiring no prompting expertise whatsoever.

 

"Every time you open the app, you get a return," he explains. "A task that once took six hours is done in thirty minutes. You profit from every single use."

 

It is a philosophy MFEC has branded its "AI Native System Integration" approach, built around four pillars: handling any data an organisation holds, securing any environment in which AI operates, embedding AI into any business process, and deploying any model — including open-source alternatives — at the most cost-effective price point.

 

For organisations paying flat per-seat licences for tools that only a fraction of staff use, the shift to token-based consumption alone can dramatically reduce costs.

 

 

 

A Thailand-Only Problem

Asked whether there are distinctly Thai dynamics at play, Siriwat does not hesitate. The country has no homegrown AI models, no domestically owned data centres, and no meaningful stake in the global AI stack.

 

"The only thing that is ours is our data," he says. That makes proprietary organisational knowledge the single genuine competitive differentiator available to Thai businesses. 

 

Organisations that train open-source models on their own internal data — their accumulated expertise, historical records, and processes — will have something rivals cannot simply purchase.
 

 

 

 

He uses The Nation as an illustration: a media group with fifty-plus years of archives that, properly fed into a private AI, would yield an editorial assistant no newcomer could replicate overnight. Without that step, every news organisation buying the same commercial AI ends up equal — which is to say, none of them are differentiated.

 

 

 

 

 

The Medicine Analogy

For executives hesitating at the threshold, Siriwat offers a characteristically direct metaphor. "AI has side effects," he concedes, "but not using AI can kill you outright. Nobody with diabetes refuses medication because it has side effects."

 

He believes large Thai conglomerates are already moving — quietly restructuring, shifting headcount, reorienting processes around AI — and expects that pressure to accelerate as economic conditions tighten further. The wave of corporate restructuring seen across American technology firms is coming, he says, it has simply not yet broken onshore.

 

MFEC, for its part, is positioning itself as the firm that helps organisations navigate that transition — not as a vendor selling licences, but as an integrator ensuring that every deployment is measurable, secure, and genuinely embedded in the way people actually work.

 

"Adopt AI," Siriwat says, "but do it in a way that you can measure."

 

In today's Thailand, that may be the only technology strategy that makes sense.