MFEC, Confluent see real-time data as core to Thailand’s AI future

As organisations race to adopt artificial intelligence, the next phase in Thailand will be shaped less by access to models and more by how quickly companies can connect, process, and govern their own data for use across the organisation, executives from MFEC and Confluent said.

They argued that while many businesses have already experimented with AI, few have yet turned those trials into measurable commercial returns.

“AI may make individuals better at their jobs, but that does not automatically improve the profit and loss statement,” said Siriwat Vongjarukorn, chief executive officer of MFEC. “If data cannot become a weapon, everybody ends up using AI at the same level.”

From MFEC’s perspective, that is the defining issue in Thailand’s AI landscape. Chips, data centres and large language models are increasingly accessible, meaning they no longer offer a durable competitive edge on their own.

What still sets one organisation apart, Siriwat said, is the quality of its data and the knowledge embedded in its people, systems and operations.

Why real-time data matters

MFEC and Confluent said the real opportunity lies in transforming static data into connected, real-time data that can support action the moment conditions change. In their view, information only becomes commercially valuable when it can move instantly from source systems into decisions, workflows and customer interactions.

Using airlines as an example, Kenny Chin, regional director of Southeast Asia and Emerging Markets at Confluent, said AI chatbots may be able to answer questions, but they cannot carry out useful tasks such as changing a flight unless they are connected to live operational systems, including ticketing, seat availability, customer preferences and destination conditions.

“If it is not in real time, I cannot buy you a ticket,” Chin said, noting that by the time a system acts, the seat may already have been taken.

The same logic applies across industries. Siriwat pointed to fraud prevention in finance, where suspicious transactions or mule-account signals must be detected and shared across systems immediately rather than weeks later.

He also cited retail and logistics, where real-time data can support instant price changes, live inventory visibility and faster responses to disruption.

“AI without data is a hollow brain,” Siriwat said, warning that too many companies still treat AI as a promising proof of concept rather than an operational capability that can scale across the business.

Where Thai organisations are struggling

Chin said businesses in Thailand are clearly moving into AI, with many firms setting up teams, launching initiatives and issuing mandates. But one weakness continues to surface: the underlying data foundation is often not ready for production use.

Siriwat argued that the challenge in Thailand is not purely technological, but also organisational. Many companies are trying to bolt AI on to old structures and processes, or hand responsibility to a single technology executive, instead of redesigning the business around shared data and a clear strategy.

He said AI will not deliver real value if it remains trapped in silos, duplicated across teams or disconnected from broader business goals.

“The question should not be whether an organisation has an AI strategy,” Siriwat said. “The question is what that AI strategy is.”

He added that once a company has an AI strategy, the person responsible for putting it into practice must understand more than IT or infrastructure. That person, he said, must also understand the structure of the business and be able to explain how data and AI can create a comparative advantage over competitors.

In MFEC’s view, AI must move beyond personal productivity and start driving revenue, reducing risk and strengthening competitiveness at enterprise level.

Why data streaming is part of the answer

That is where data streaming platforms come in. According to Chin, data streaming platforms such as Confluent help organisations connect fragmented systems and push updates in real time whenever source data changes, allowing downstream applications and teams to respond immediately.

He said this must be backed by strong governance. Confluent highlighted capabilities such as role-based access control, stream lineage and schema registry to ensure the right people can access the right data, trace where that data travels across the organisation and maintain consistent formats across systems.

Those controls, Chin said, are essential if businesses want to scale real-time AI without creating fresh data chaos.

MFEC and Confluent deepen push into Thailand

The growing cooperation between MFEC and Confluent is aimed squarely at this gap in the Thai market.

MFEC is positioning itself as a partner that can help businesses turn AI ambition into operational outcomes, while Confluent sees Thailand as a major market, with especially strong demand from banking and financial services, alongside growing interest from telecoms and retail.

Together, the two companies argue that the future of AI in Thailand will not be decided by the firms with the loudest pilots, but by those that can connect their data, break down silos and act in real time.