MBPP smart city unit staff Alia Jasmani and S. Shanmugapiriya giving an explanation to new user Lee Tzyy Chii, 38, on ChatMBPP during the launch in Bayan Lepas. — ZHAFARAN NASIB/The Star
Penang Island City Council (MBPP) has launched its Gen.AI chatbot called ChatMBPP.
Developed by MBPP’s Smart City Unit with input from all 19 internal departments, the artificial intelligence (AI) chatbot supports four languages – Bahasa Malaysia, English, Mandarin and Tamil.
ChatMBPP can respond to queries and initiate actions such as generating complaint tickets and routing them to relevant departments automatically.
The system is also part of MBPP’s agentic AI phase, enabling it to not only respond but trigger internal processes.
Rajendran says ChatMBPP will be a game changer in public service delivery.
The system is currently in beta, with MBPP noting that responses were AI-generated and for reference only, with accuracy to be improved over time.
Penang island mayor Datuk A. Rajendran said ChatMBPP was a game changer in public service delivery, offering round-the-clock access for users to obtain information, lodge complaints and use the city council services.
“It brings MBPP closer to the people and moves us towards a smarter, more responsive digital administration.
“It serves as a simple, fast and user-friendly digital platform that operates 24/7, enabling seamless interaction between the public and local authority.
“ChatMBPP is specifically designed to handle queries related to MBPP’s city management functions, including services, procedures, public complaints, enforcement, taxation and responsibilities.
“The initiative aligns with national efforts to build AI-driven cities and complements frameworks such as Penang2030 and the Malaysia Smart City agenda, while maintaining human oversight to ensure accuracy and quality,” said Rajendran.
Gen.AI was launched by Chief Minister Chow Kon Yeow at Queensbay Mall, alongside Penang local government, town and country planning committee chairman Jason H’ng Mooi Lye and Digital Ministry secretary-general Datuk Fabian Bigar.
Chow said the launch represented a shift in how the government engaged with the public.
Chow: ChatMBPP serves as a key entry point into a Penang AI City ecosystem.
“As we move towards Industrial Revolution 4.0 and adopt AI, government service delivery must also evolve to be faster, more accurate and without bureaucratic hurdles.”
Chow said Penang, which contributed 44.2% or RM65bil to Malaysia’s exports as of January 2026, could no longer rely on traditional and slower administrative methods.
He added that the initiative laid the foundation for a “Penang AI City”, where data was used to improve quality of life in an inclusive manner, with ChatMBPP serving as a key entry point into that ecosystem.
The chatbot is built on Amazon Web Services infrastructure and is tailored specifically for PP’s scope of services, including city management, enforcement, taxation and public complaints.MB
Fabian said the move represented a new benchmark for local authorities, describing it as a model for how generative AI could be applied in public service delivery nationwide.
He added that Digital Ministry had approved a 5G grant to support the initiative, enabling faster, real-time responses through robust infrastructure
Leading companies are moving beyond experimentation as a third of “AI future-built” firms have deployed agentic solutions and are demonstrating measurable value.
MALAYSIA stands at a critical inflection point in the global artificial intelligence (AI) race.
After the surge of generative AI, a new wave is emerging in the form of agentic AI.
Agentic AI are AI execution models involving autonomous agents that coordinate across workflows, tools and systems with minimal human input.
While it stops short of true autonomous decision-making, agentic AI’s ability to make actionable decisions within predefined parameters is a game changer.
Malaysia has a solid foundation to build on.
According to Boston Consultant Group’s AI Maturity Matrix, which benchmarks 73 economies globally on AI exposure and AI readiness, Malaysia is classified as a “steady contender”.
It places the nation just one tier behind AI pioneers such as the United States, the United Kingdom and China.
This position reflects Malaysia’s significant exposure to AI, particularly in large sectors like retail and wholesale, telecommunication and financial services.
At the same time, it indicates a solid level of AI readiness, supported by forward-looking ambitions, policies and regulatory frameworks on AI.
An evolving AI landscape
AI is rapidly becoming a critical national infrastructure that empowers wider opportunities.
As a result, geopolitical shifts, compute access and sovereign capability increasingly determine economic outcomes and geopolitical influence.
The US and China lead the global AI race.
Tech companies from these two superpowers created 59% and 26%, respectively, of top-performing large language models (LLM).
This presents a conundrum for competing nations.
Relying solely on external technology providers poses challenges for corporate leaders and governments, especially since local regulations, data requirements and model availability are subject to shifting policies.
Against this backdrop, a small group of “GenAI middle powers” is emerging across Europe, Asia and the Middle East.
Each has distinct strengths that might allow it to compete as a regional or global technology supplier.
This race now expands beyond software to encompass hardware, infrastructure and technology adoption.
Malaysia must actively build its domestic AI capabilities to avoid high technology sovereignty risks as it looks to the future of agentic AI.
Execution speed and scale will dictate whether Malaysia leads in Asean or falls behind.
Encouragingly, the Digital Ministry, through the establishment of the National AI Office (NAIO), is driving a coordinated national AI agenda – spanning governance frameworks, cross-sector adoption and ecosystem development.
These efforts lay the critical foundations for more advanced applications, including the next wave of agentic AI.
Productivity multiplier
Globally, the shift is already underway and early signs indicate that the rise of agentic AI will be rapid.
BCG’s Build for the Future 2025 study shows that agentic AI’s share of AI-driven value is expected to nearly double from 17% in 2025 to 29% by 2028.
Leading companies are moving beyond experimentation – one-third of “AI future-built” firms have deployed agentic solutions and are demonstrating measurable value.
Early adopters are already unlocking tangible benefits. BCG’s study shows that while companies are exploring agentic AI across operations, support functions and innovation, customer experience is emerging as the top priority.
Leading use cases include deploying intelligent agents to autonomously handle Level 1 and Level 2 customer support, as well as optimising digital marketing campaigns – continuously adjusting bids to maximise returns, reallocating spend to high-performing channels and testing creatives in real time.
AI undoubtedly represents a powerful productivity multiplier for Malaysia.
It can strengthen key economic sectors such as manufacturing, financial services and many other industries. For SMEs, agentic AI can lower the cost of sophistication, providing access to capabilities once reserved for large enterprises.
Beyond the private sector, agentic AI can modernise public services and improve policy-making decisions and delivery in healthcare, education and justice.
It can help bridge urban-rural divides by expanding access to digital services and decision support.
In a nation balancing growth ambitions with demographic and fiscal constraints, agentic AI is not merely a technology upgrade – it is a lever for sustainable and inclusive growth.
Four strategic priorities
To compete effectively in this next phase of AI, Malaysia must act with clarity and intent across four priorities.
> Build sovereign AI capabilities. Malaysia could strategically build sovereign AI capabilities in areas where it has natural strengths and where risk mitigation matters most.
This includes expanding reliable access to compute, leveraging its growing data centre ecosystem.
A pragmatic and technology-neutral approach that combines global technology partnerships with targeted domestic capability-building will be more effective than pursuing full-stack independence.
Technology partnerships could focus on leveraging leading AI innovations from both Western and Eastern ecosystems in a neutral manner.
Open-source AI models offer a practical pathway to reduce dependency risks, accelerate adoption and support local customisation.
At the same time, efforts could focus on enabling responsible use of high-quality local datasets.
> Invest aggressively in talent. Malaysia must pair global talent attraction with sustained local capability development to build the AI workforce needed to compete at scale.
It could aggressively attract top global AI talent through competitive incentives, strong research ecosystems and vibrant innovation hubs, while simultaneously building a deep domestic pipeline of AI talent.
This requires strengthening STEM education, expanding university–industry collaboration, embedding AI in technical and vocational training and accelerating workforce upskilling across sectors.
> Scale national platforms. Malaysia must move from fragmented pilots to scaled national platforms, anchored on high-impact use cases – such as a unified government interface linked to MyDigitalID.
This platform provides a common foundation to embed AI agents that deliver personalised public services.
Scaling up such platforms will catalyse greater private-sector participation and ensure sustainable adoption of agentic AI.
In addition, Malaysia could strengthen exchange platforms that bring together the government, industry and academia to accelerate collaboration, capability-building and use case development.
Associations such as AI Malaysia (AIM), Malaysian Autonomous Intelligence & Robotics Association (MyAIRA), along with other industry associations, can play a critical role in sharing best practices, mobilising talent and aligning stakeholders to drive ecosystem-wide adoption of agentic AI.
> Implement pro-innovation regulation. Malaysia needs regulations that protect users but also preserve competition.
Policymakers could favour a flexible model over rigid frameworks, particularly in a fast-evolving technological landscape.
Malaysia could pursue a balanced approach – combining principle-based guidelines, regulatory sandboxes and sector-specific standards that can evolve alongside the technology.
Priming Malaysia for growth is critical, but it is essential that this is done through a forward-looking and ethical approach.
Malaysia has the opportunity to differentiate itself by championing ethical, inclusive AI.
This is a core foundation of effective AI adoption, and should align with national values, ensuring that trust and confidence underpin the next wave of innovation in agentic AI.
Defining the future
The stakes are clear. AI investment compounds rapidly. Early movers attract capital, talent and vibrant ecosystems.
The choice is not whether AI will reshape the Malaysian economy.
The choice is whether Malaysia will shape that transformation with speed, clarity and ambition while remaining anchored to core Malaysian values.
CF Ong is managing director and senior partner in Boston Consulting Group.
Low cost, high impact ai models surge in global usage
Making inroads: A woman descends a staircase in a book store in Beijing.
Despite considerable geopolitical tensions, Chinese open-source AI
models are winning over a growing number of programmers and companies in
the United States. — AFP
NEW YORK: As the United States embarks on a bitter
rivalry with China over the deployment of artificial intelligence (AI),
Chinese technology is quietly making inroads into the US market.
Despite
considerable geopolitical tensions, Chinese open-source AI models are
winning over a growing number of programmers and companies in the United
States.
These are different
from the closed generative AI models that have become household names –
ChatGPT-maker OpenAI or Google’s Gemini – whose inner workings are
fiercely protected.
In contrast, “open” models offered by many
Chinese rivals, from Alibaba to DeepSeek, allow programmers to customise
parts of the software to suit their needs.
Globally, use of Chinese-developed open models has surged from
just 1.2% in late 2024 to nearly 30% in August, according to a report
published this month by the developers’ platform OpenRouter and US
venture capital firm Andreessen Horowitz.
China’s open-source
models “are cheap – in some cases free – and they work well,” Wang Wen,
dean of the Chongyang Institute for Financial Studies at Renmin
University of China said.
One American entrepreneur, speaking on
condition of anonymity, said their business saves US$400,000 annually by
using Alibaba’s Qwen AI models instead of the proprietary models.
“If you need cutting-edge capabilities, you go back to OpenAI,
Anthropic or Google, but most applications don’t need that,” said the
entrepreneur.
US chip titan Nvidia, AI firm Perplexity and California’s Stanford University are also using Qwen models in some of their work.
The
January launch of DeepSeek’s high performance, low cost and open source
“R1” large language model (LLM) defied the perception that the best AI
tech had to be from US juggernauts like OpenAI, Anthropic or Google.
It
was also a reckoning for the United States, locked in a battle for
dominance in AI tech with China, on how far its archrival had come.
AI
models from China’s MiniMax and Z.ai are also popular overseas, and the
country has entered the race to build AI agents, programmes that use
chatbots to complete online tasks like buying tickets or adding events
to a calendar.
Agent friendly, and open-source, models, like the
latest version of the Kimi K2 model from the startup Moonshot AI,
released in November, are widely considered the next frontier in the
generative AI revolution.
The US government is aware of open-source’s potential.
In
July, the Trump administration released an “AI Action Plan” that said
America needed “leading open models founded on American values”.
These could become global standards, it said.
But
so far US companies are taking the opposite track. Meta, which had led
the country’s open-source efforts with its Llama models, is now
concentrating on closed-source AI instead.
However, this summer,
OpenAI, under pressure to revive the spirit of its origin as a
nonprofit, released two “open-weight” models – slightly less malleable
than “open-source”.
Among major Western companies, only France’s
Mistral is sticking with open-source, but it ranks far behind DeepSeek
and Qwen in usage rankings.
Western open-source offerings are “just not as interesting”, said the US entrepreneur who uses Alibaba’s Qwen.
The Chinese government has encouraged open-source AI technology, despite questions over its profitability.
Mark
Barton, chief technology officer at OMNIUX, said he was considering
using Qwen but some of his clients could be uncomfortable with the idea
of interacting with Chinese-made AI, even for specific tasks.
Given the current US administration’s stance on Chinese tech companies, risks remain, he said.
“We
wouldn’t want to go all-in with one specific model provider, especially
one that’s maybe not aligned with Western ideas,” said Barton.
“If Alibaba were to get sanctioned or usage was effectively blacklisted, we don’t want to get caught in that trap.”
But Paul Triolo, a partner at DGA-Albright Stonebridge Group, said there were no “salient issues” surrounding data security.
“Companies can choose to use the models and build on them, without any connection to China,” he explained.
A
recent Stanford study published posited that “the very nature of
open-model releases enables better scrutiny” of the tech. — AFP
Recently, during a maglev experiment conducted by the maglev team of China's National University of Defense Technology, a ton-class test vehicle was successfully accelerated to 700 kilometers per hour within just two seconds, state broadcaster CCTV News reported on Thursday
