Artificial Intelligence digital concept illustrate of modern internet technology and innovative processes 3D rendering
ARTIFICIAL intelligence (AI) has firmly entrenched itself as part of our lives and this is no different in the business industry.
Businesses worldwide have begun integrating AI into various functions to enhance efficiency, personalise customer experiences and inform strategic decisions.
These applications range from automating workflows and analysing data to powering creative processes and strengthening security.
But what are the implications of using AI in everyday businesses and can that work well at all? StarESG reached out to Greenie Web’s founder and chief executive officer Ian Chew on how this new technology can boost and augment the nation’s productivity.
Measuring, tracking and reducing carbon footprint
Chew mentioned that AI allows companies to move from annual, spreadsheet-based estimates to high-frequency, activity-level accounting.
“In Asean, that means pulling live data from factory meters in Batam, transport telematics in the Klang Valley, grid-emission factors in Singapore or Thailand, and even satellite imagery for land-use signals in Indonesia and Malaysia,” he said.
With those streams, models are able to automatically classify Scopes 1 to 3 activities, fill data gaps, flag anomalies (such as, diesel versus grid switching), and simulate abatement options, so firms can pick the lowest-cost tonne to cut, site by site.
Optimising energy use
Chew mentioned that there are three areas that AI can boost optimisation, the first being data centres. He said reinforcement-learning controllers can help tune cooling set-points, airflow and server workloads to local humidity and heat (critical in the tropical Asean climate), and shift non-urgent computations to off-peak or high-renewables periods.
For offices or retail spaces, computer vision and occupancy prediction can adjust heating, ventilation, air conditioning (HVAC) and lighting in malls from Manila to Bangkok, cutting wasted energy, while maintaining comfort.
In factories and warehouses, Chew pointed out that predictive maintenance can reduce compressor and chiller losses, or route algorithms that can minimise empty runs across cross-border corridors like Johor–Singapore and Bangkok–Laem Chabang.
Machine learning for circular business models
“Machine learning can forecast demand and failure rates so companies stock only what will be used and designed for repair,” said Chew. Vision language models grade returned goods and automate sorting for refurbish or reuse, powerful for e-commerce hubs in Jakarta and Ho Chi Minh City.
Ian Chew is the sole founder ofSingapore ClimateTech startupGreenie Web, which decarbonisesdigital infrastructure. He is a pioneerin the decarbonisation of the digitalworld and is the first in Asia to havecarried out such work. For his contributionsto the field of climatechange, Chew received theForbes 30 under 30 (Asia) honourfor Social Impact.
Digital twins of products track components from manufacture to second life, enabling “as-a-service” models for electronics, batteries and even uniforms in Singapore and Kuala Lumpur.
Improving transparency in ESG reporting and meeting standards
Chew mentioned that AI pipelines can map raw operational data to the International Sustainability Standards Board and the Sustainability Accounting Standards Board aligned disclosures and generate audit trails, showing where data came from, how it was cleaned and why an estimate was used.
Natural Language Processing tools scan supplier documents across multiple Asean languages, flagging missing attestations, such as for anti-deforestation or in labour, and reconciling them with shipment data. That reduces manual effort and greenwashing risk while making limited assurance or reasonable assurance faster and cheaper.
Sustainable logistics and last-mile efficiency
For an archipelagic region like the Philippines and Indonesia, AI can orchestrate multimodal routes, such as trucks, ferries or electric vehicles.
“It can group deliveries into micro-hubs, and appropriately assign the right vehicles to a certain location, such as large vans for wider roads while motorcycles can traverse narrow lanes better,” Chew said.
AI can help warehouses predict real-time traffic, weather and port congestion feeds better to reduce idling and cold-chain spoilage. When demand prediction is integrated in the system, suppliers can shrink their safety stock and empty returns on Asean’s mega-corridors, such as Penang–KL–Singapore and HCMC–Binh Duong–Dong Nai.
Affordable AI for SMEs’ sustainability
Small and medium sized enterprises (SMEs) should consider integrating AI into their operations to help them reduce their carbon footprint.
“Start with meter-less estimators, such as card or ERP (enterprise resource planning)-to-carbon systems,” suggested Chew, adding that freemium demand or route optimisers are also options to consider. They can then layer in internet smart plugs and Wi-Fi loggers to validate their savings.
They can also tap into public grants or credits (such as EnterpriseSG in Singapore, MDEC in Malaysia, DEPA in Thailand and DICT in the Philippines) as well as use cloud credits from hyperscalers’ sustainability programmes.
“The playbook would be to pick one hotspot (delivery routing or HVAC), run a four to eight week pilot, use bank savings and fund the next step,” suggested Chew.
Generating efficient, low carbon codes
Chew’s own Greenie Web platform analyses codebases with AI to identify energy-intensive patterns, which normally include inefficient loops or queries, over-fetching, chatty APIs, heavy client-side rendering.
It then auto-suggests refactors and configuration changes, such as batching, caching, algorithmic swaps, edge offload or offering greener frameworks to users.
“We pair that with runtime profiling and carbon-aware scheduling so workloads run when or where grid intensity is lower in Asean.
“The typical results we see are double-digit reductions in computational time and data transfer—translating to lower cloud bills and measurable carbon cuts —without sacrificing reliability,” explained Chew.
Competitive advantage
The most promising areas where AI and sustainability can intersect to create real competitive advantage for businesses include running operations that are more carbon-aware. Examples are methods of automatically shifting computing, cooling and production schedules to the cleanest hours or locations.
They should utilise supplier intelligence by running machine-learning risk scoring systems across Asean’s deep, multi-tier supply chains for compliance, deforestation and labour, as this becomes a moat for exporters.
There are also circular services that can run “predict-repair-refurbish” engines that unlock subscription and buy back models at scale. Similarly, they can provide a greener customer experience by offering ultra-fast, low-carbon digital products (lean code, plus smart caching) that load faster on entry-level phones—this is a big advantage in price sensitive Asean markets.
Lastly, companies do engage in remote-sensing AI for flood or heat risk pricing and plantation monitoring across the Mekong and Borneo—these methods help protect assets and open new insurance and finance products.
