Alan Ng is the Founder and CEO of QuikBot Technologies, a pioneering company headquartered in Singapore that is redefining urban logistics through autonomous delivery solutions. Under his leadership, QuikBot has developed the world’s first Autonomous Final-Mile Delivery Platform-as-a-Service (AFMD PaaS)—a groundbreaking innovation designed to address the rising demands of urban delivery with intelligent, scalable infrastructure.

As the visionary behind this next-generation logistics platform, Alan sees autonomous delivery not just as a technological advancement, but as a transformational force for smart cities. With urban delivery traffic projected to surge by over 60% by 2030—contributing to rising emissions and longer commute times—Alan believes autonomous delivery vehicles, particularly compact ground units, offer a cleaner, more efficient alternative.

QuikBot’s PaaS model empowers businesses and communities to adopt autonomous delivery without owning costly hardware, making logistics more accessible, inclusive, and sustainable. By operating off-road or in dedicated corridors, these systems ease congestion, free up road space, and align with the broader goals of public transit and active mobility.

Alan’s mission is clear: to position autonomous delivery as essential urban infrastructure—future-proof, democratized, and built for the cities of tomorrow. Through QuikBot, he is building not just a company, but a smarter, healthier vision for urban living.

‍

What role do AI and robotics play in improving the efficiency and sustainability of smart city logistics?

‍AI and robotics play a critical role in enhancing both the efficiency and sustainability of smart city logistics, and they are integral to QuikBot’s Platform-as-a-Service model.

AI powers real-time decision-making across the delivery network. From intelligent route planning and predictive fleet scheduling to advanced robotic fleet management, AI helps reduce travel time, lower energy consumption, and streamline the flow of goods through urban environments. It also supports demand forecasting and system-wide coordination, allowing for more effective use of delivery assets and infrastructure.

Robotics, particularly QuikBot autonomous ground delivery robots, form the operational backbone of this transformation. These compact, zero-emission robots are engineered for safe, reliable, and efficient navigation in complex city settings. When integrated with AI, they adapt in real time, avoid delays, and deliver with a high degree of precision and consistency.

AI also enables sophisticated fleet coordination. It can synchronise robot movements to eliminate inefficiencies, and monitor performance to ensure compliance with environmental and safety standards. The result is a responsive, low-emission logistics network that scales seamlessly with urban demand.

At QuikBot, AI and robotics are embedded within a connected platform that links logistics providers, building systems, and smart city infrastructure. This integrated approach is key to delivering measurable gains in both operational efficiency and environmental impact.

‍

How does CareStar collaborate with Keenon Robotics to enhance automation solutions in Southeast Asia?
CareStar collaborates with Keenon Robotics as an authorised reseller, focused on bringing their world-class service robots into key markets across Southeast Asia. As a reseller, CareStar identifies commercial opportunities, advises businesses on suitable deployment environments, and supports the sale and implementation of Keenon’s robotic solutions across sectors such as F&B, hospitality, and healthcare.

While we continue to fulfill this role, we recognized a growing shift in the market. Many businesses were no longer looking to purchase robots outright. Instead, they were exploring robotics-as-a-service models that offer more flexibility, lower upfront costs, and minimal maintenance responsibilities.

Purchasing robots typically requires companies to build internal technical teams or pay annual maintenance fees to external vendors. For many businesses, especially SMEs or those operating in resource-constrained environments, this is neither cost-effective nor scalable.

To address this, we launched QuikBot—a new venture that pivots away from traditional hardware reselling and moves toward a Platform-as-a-Service (PaaS) model for autonomous last-mile delivery robots. With QuikBot, businesses can subscribe to an all-inclusive service at a fixed monthly rate. We manage the entire lifecycle of the robots, from deployment to maintenance, so customers can focus on their operations while benefiting from automation.

‍

How do you foresee AI-driven robotics transforming industries like healthcare, F&B, and retail in the next 5 years?

‍AI-driven robotics is set to transform healthcare, food and beverage (F&B), and retail over the next five years by tackling key challenges in efficiency, service quality, and manpower shortages.

In healthcare, autonomous robots will handle non-clinical, labour-intensive tasks like medication delivery, specimen transport, and materials handling. These functions, often repetitive and time-sensitive, can be performed more reliably by robots, allowing clinical staff to focus on patient care. AI enables safe navigation through complex hospital environments and integration with existing systems.

In the F&B sector, robots will support both front-of-house delivery in food courts and campuses, and back-of-house operations like kitchen prep and inventory movement. These solutions help manage rising labour costs and improve consistency, especially as younger workers move away from physically demanding roles.

In retail, AI-powered robots will enhance micro-fulfilment, restocking, and doorstep delivery. As e-commerce demand grows, businesses are struggling to secure enough delivery personnel. Autonomous systems offer a scalable, 24/7 alternative, free from shift constraints or workforce turnover.

Across all sectors, AI-driven robotics goes beyond automation by enabling intelligent, adaptive workflows and reducing environmental impact. It is also helping industries respond to structural labour shortages driven by demographic change and shifting workforce expectations.

At QuikBot, we see autonomous delivery as shared infrastructure that supports  multiple industries in building more efficient, resilient, and sustainable operations.

What are the biggest misconceptions about AI and robotics in Southeast Asia that you’d like to address?

‍One of the most common misconceptions about AI and robotics in Southeast Asia is that they are only relevant to advanced economies or high-tech industries. In reality, these technologies are highly adaptable and can deliver immediate value in emerging markets, particularly in urban logistics, healthcare, and retail.

Another frequent misunderstanding is that robotics refers only to flashy, humanoid machines. In practice, the most impactful solutions today are compact, purpose-built systems designed for repetitive tasks such as autonomous delivery. These robots are not here to replace people, but to support human teams by taking on work that is physically demanding, time-consuming, or hard to scale.

The most persistent myth is that AI and robotics are taking jobs from humans. In fact, we are seeing a shift in job roles, especially in last-mile delivery. As autonomous systems are deployed, there is growing demand for skilled technicians and operators to manage, maintain, and monitor them. This creates more technical, knowledge-based roles that are safer, more stable, and better aligned with the aspirations of today’s workforce.

In Southeast Asia, where industries compete for the same limited pool of delivery workers across food, parcels, and e-commerce, automation offers a practical solution. With younger workers increasingly avoiding repetitive, low-growth roles, AI and robotics help close the labour gap while opening new pathways for upskilling and career development.

At QuikBot, we view AI and robotics not as a threat to jobs, but as a driver of economic upgrading, one that is modernising city logistics while preparing workers for the demands of a more digital and resilient future.

‍

‍

Which emerging markets in Southeast Asia do you see as the next big opportunities for business expansion?
In Southeast Asia, we see strong long-term potential in emerging markets such as Indonesia, Thailand, Vietnam, and the Philippines. These fast-growing urban centres are experiencing rising demand for more efficient and reliable delivery, fuelled by rapid e-commerce growth, urbanisation, and increasing consumer expectations.

However, in much of the region, with the exception of Singapore, the dominant mindset is still shaped by the relative affordability of labour. Many businesses continue to rely on human-based delivery models, believing that hiring more workers is more cost-effective than investing in automation. As a result, autonomous delivery is often seen as a future consideration rather than a present need.

This cost-based approach is unlikely to remain sustainable. Demographic changes, rising labour costs, worsening congestion, and a growing reluctance among younger workers to take on repetitive delivery roles are already beginning to affect the labour supply. When these cities reach a tipping point and begin actively searching for autonomous solutions, QuikBot will be ready to support that transition with a mature, proven platform.

Currently, our focus remains on markets that are actively investing in smart city infrastructure and regulatory readiness. These include Singapore, the United Arab Emirates, and Japan. In these environments, autonomous delivery is seen as a strategic part of urban transformation, allowing us to deliver real-world results, refine our technology, and develop scalable deployment models.

QuikBot’s long-term strategy is to lead in progressive cities today while preparing to support emerging Southeast Asian markets as they evolve toward autonomy and smart logistics.

‍

How do you see AI and robotics evolving in the next five years, especially in the APAC region?
Over the next five years, we expect AI and robotics to evolve from isolated pilots into integrated, city-scale infrastructure across the Asia-Pacific (APAC) region. This evolution will be shaped by a combination of demographic pressures, urban growth, and rising expectations for speed, reliability, and sustainability in everyday services.

In the short term, we’ll see broader adoption of AI-driven robotics in sectors facing manpower shortages and high operational demands—such as logistics, healthcare, hospitality, and facilities management. Autonomous systems will move beyond controlled environments into more dynamic, real-world settings, supported by better connectivity, regulation, and public acceptance.

In Southeast Asia, affordability of labour has historically delayed large-scale investment in robotics. But this is starting to shift. As wages rise and younger workers seek more skilled, technology-enabled roles, automation will become a necessity rather than an option. Cities will increasingly turn to robotics to support essential services like last-mile delivery, cleaning, food transport, and intra-building logistics.

Japan, Singapore, and South Korea will continue to lead in regulatory readiness, R&D investment, and deployment at scale. These markets will set the blueprint for how AI and robotics can be embedded into national infrastructure and daily urban life.

At QuikBot, we see the APAC region as a diverse landscape—some cities are ready now, others will follow in the coming years. Our approach is to focus on mature markets while preparing our platform for rapid deployment in emerging ones as they accelerate their smart city transitions.

AI and robotics are not just technological shifts. In APAC, they will become key enablers of economic resilience, sustainability, and workforce transformation. The next five years will be about building systems that are not only intelligent, but also inclusive, adaptable, and deeply embedded in the way cities function.

‍

What inspired you to focus on AI-driven robotics with CareStar, and what are its most innovative applications?
The inspiration behind CareStar came from a clear and growing need across Southeast Asia: businesses were looking for reliable automation to address labour shortages, improve service efficiency, and raise operational standards. We saw an opportunity to bring proven robotics solutions into real-world environments, particularly in F&B, hospitality, and healthcare, through a straightforward sales and deployment model. CareStar’s role has always been to act as a trusted reseller and implementation partner for Keenon Robotics, helping businesses adopt best-in-class service robots for their day-to-day operations.

However, as we worked closely with clients, it became clear that many organisations didn’t just want to buy robots, they wanted solutions. They were looking for flexibility, scalability, and outcomes without the burden of upfront costs, maintenance overheads, or technical complexity. This shift in mindset inspired us to start QuikBot.

Unlike CareStar’s traditional hardware reselling model, QuikBot operates on a Platform-as-a-Service (PaaS) approach. This service-based model doesn’t just involve delivering robots, it requires us to constantly improve our technology, software, and fleet operations to meet evolving customer needs. We handle everything from deployment and integration to remote monitoring and maintenance, allowing clients to adopt robotics without having to invest in their own support teams.

Because of this model, QuikBot is built to innovate. Our clients expect reliability, adaptability, and performance as part of the service. That drives us to continuously enhance route optimisation, robot-facility integration, uptime performance, and user experience across the board.

What are the biggest technological challenges in scaling autonomous robotics for healthcare and service industries?
One of the biggest technological challenges in scaling autonomous robotics for healthcare and service industries lies in real-world integration. Unlike controlled environments such as warehouses or factory floors, hospitals, clinics, hotels, and commercial buildings are highly dynamic, human-centric spaces. Robots must be able to navigate unpredictable layouts, interact safely with people, and adapt to rapidly changing conditions in real time.

Another key challenge is system interoperability. In healthcare settings, for example, robots must integrate with hospital management systems, lift controls, access points, and secure areas, and often across legacy infrastructure. Achieving seamless and secure integration across these different systems requires robust APIs, custom engineering, and tight coordination with facility managers.

Reliability and uptime are also critical, especially in healthcare where service disruptions can affect patient care. Robots need to perform consistently across long operating hours, and any technical failure must be quickly diagnosed and resolved. This places high demands on both the hardware design and the remote monitoring systems that support them.

Furthermore, regulatory compliance and safety add another layer of complexity. In environments involving food, medicine, or patient interaction, robots must comply with strict hygiene, traceability, and operational standards. Meeting these requirements while maintaining performance and affordability is a major balancing act.

Lastly, there is the challenge of scalability through service delivery. As adoption increases, providers must manage not just robot fleets, but also customer support, predictive maintenance, software updates, and user training. This is where the Platform-as-a-Service model, like QuikBot’s, becomes essential. It allows us to centralise fleet management, push updates remotely, and ensure consistent performance across multiple client sites—all without placing the burden on the customer.

How do you see AI-powered robotics transforming industries like healthcare, F&B, and retail?
AI-powered robotics is poised to transform industries such as healthcare, F&B, and retail by addressing structural labour shortages, enhancing operational efficiency, and improving service quality.

In healthcare, AI-enabled robots will increasingly manage routine yet essential tasks such as medication delivery, specimen transport, and linen handling. While non-clinical, these functions are critical to smooth hospital operations. Automating them allows medical staff to focus on patient care. These robots can navigate complex hospital environments, respond to real-time changes, and integrate with existing systems such as lifts, ward access controls, and hospital scheduling platforms.

In the F&B sector, AI-driven robots will support both front-of-house and back-of-house operations. They can assist with food running, tray returns, cleaning, and light preparation work. These solutions help standardise service, improve hygiene, and alleviate labour shortages, particularly as fewer younger workers enter physically demanding roles. With AI, robots can optimise movement, adjust to busy periods, and streamline overall workflows.

In retail, combining AI with robotics will enable smarter fulfilment and customer service. Autonomous units can manage restocking, order picking, and last-mile delivery, while AI helps predict demand, personalise offers, and fine-tune inventory flow. This allows retailers to operate leaner, respond faster to customer needs, and maintain accuracy at scale.

Across all three sectors, the challenge of attracting and retaining workers for repetitive tasks is growing. Businesses are competing for the same limited talent pool, while younger generations are gravitating toward roles with greater technical depth. AI-powered robotics offers a sustainable alternative, automating low-skill tasks while creating new opportunities in system operations, fleet management, and technical maintenance.
‍

‍

What are the key AI and robotics trends that businesses should be preparing for in 2025 and beyond?
As we approach 2025, several key trends in AI and robotics are set to reshape how businesses operate, scale, and deliver services. This shift is especially relevant in logistics, healthcare, retail, and facilities management, where the demand for automation, consistency, and efficiency continues to grow.

One major development is the growing adoption of Platform-as-a-Service (PaaS) models for robotics. Instead of purchasing and managing their own robots, businesses are subscribing to fully managed services that include hardware, software, maintenance, and support. This model reduces capital expenditure, ensures consistent performance, and allows companies to scale usage based on operational needs without added complexity.

Human-robot collaboration is also gaining ground. Advances in AI are enabling robots to work alongside people, respond to real-time conditions, and adapt through continuous learning. This supports more flexible and efficient workflows, particularly in environments where human judgement and adaptability remain essential.

As autonomous systems become more common, integration with existing infrastructure is becoming a priority. Robots must interact seamlessly with lifts, access systems, automated doors, and facility management platforms. Businesses that invest in robotics-ready environments will be better prepared for large-scale deployment with minimal disruption.

Workforce transformation is another key focus. As automation takes over repetitive tasks, there is growing demand for skilled roles such as robotics technicians, fleet operators, and system supervisors. Upskilling employees into these positions not only supports technology adoption but also strengthens job security and long-term career development.

Finally, as robotics and AI become more embedded in daily operations, regulatory compliance and data governance are increasingly important. Companies must navigate evolving standards around safety, privacy, and interoperability. Proactive engagement with regulators and adherence to compliance frameworks will be essential for responsible and sustainable growth.

At QuikBot, we are building our platform to align with these shifts. Our Platform-as-a-Service model provides businesses with a scalable, low-risk way to adopt AI-powered robotics, thus ensuring performance, innovation, and seamless integration with the smart city infrastructure of the future.

With the rise of automation, what new business models do you foresee emerging in the service and logistics sectors?
With the rise of automation, several new business models are beginning to take shape in the service and logistics sectors. These models reflect the growing need for operational flexibility, cost-efficiency, and the ability to scale quickly without heavy capital investment.

One key model is Platform-as-a-Service for robotics. Instead of purchasing and maintaining their own robots, businesses can now subscribe to a fully managed service that provides the hardware, software, maintenance, and system support as a monthly package. This approach lowers the entry barrier for automation, especially for businesses that lack the internal resources to manage robotics infrastructure on their own.

Another model gaining momentum is micro-fulfilment-as-a-service. In urban areas, businesses are turning to shared micro-warehouses that use automation for storage, order picking, and dispatch. These facilities allow for faster last-mile delivery while reducing the need for each company to invest in its own logistics footprint.

We are also seeing the emergence of autonomous delivery networks. In this model, multiple businesses share access to a centralised fleet of autonomous delivery vehicles, operated by a third-party provider. This makes it possible for companies of all sizes, including SMEs, to benefit from robotic delivery without owning or managing a fleet.

In the service sector, particularly in food and beverage, healthcare, and hospitality, automation-as-a-service is becoming increasingly attractive. Businesses can deploy service robots for tasks such as food running, cleaning, or transport within buildings, all on a subscription basis. These packages often include installation, technical support, and regular system updates.

Finally, performance-based service models are beginning to take root. Clients pay based on actual usage metrics such as deliveries completed, operational uptime, or task volume. This aligns the interests of automation providers and their customers, ensuring service reliability and measurable value.

At QuikBot, we are building around these evolving models, offering solutions that help businesses adopt automation in a more accessible, efficient, and future-ready way.

‍

How do you see autonomous delivery reshaping last-mile logistics in smart cities?
Autonomous delivery is set to redefine last-mile logistics in smart cities by enabling a more efficient, sustainable, and responsive urban delivery network.

For over 3,000 years, delivery has depended on human labour to move goods. QuikBot’s Autonomous Final-Mile Delivery (AFMD) Platform marks a major shift, bringing automation and intelligence to an essential service that has remained largely unchanged. This evolution meets the growing demands of modern cities facing congestion, emissions, and rising delivery volumes.

A key benefit of autonomous delivery is its ability to reduce road congestion and emissions. Traditional delivery methods rely on vans and motorcycles that contribute significantly to traffic and air pollution. Compact, ground-based autonomous units operate on pavements or designated paths, easing the strain on urban roads and supporting low-emission transport targets.

Autonomous systems also enhance operational efficiency. They can function beyond normal working hours, adjust routes in real time based on traffic conditions, and remove human error from delivery processes. The result is faster, more reliable service with consistent performance.

These platforms generate valuable real-time data that city planners can use to optimise infrastructure, manage loading zones, and improve urban mobility strategies. This makes autonomous delivery not just a logistics solution but a data asset that strengthens broader smart city planning.

Additionally, automation enables decentralised logistics. Micro-fulfilment hubs paired with autonomous units allow goods to be dispatched from locations closer to end users, shortening delivery routes and increasing responsiveness—particularly useful in high-density areas where traditional models face limitations.

Autonomous delivery also addresses structural labour challenges. Recruiting and retaining workers for repetitive delivery roles is increasingly difficult, especially as younger workers seek more meaningful and skilled jobs. Automation fills this gap and creates new technical roles in operations, fleet monitoring, and systems management.

At QuikBot, we are building the infrastructure for the next generation of urban logistics—one that delivers cleaner air, smoother traffic flow, and smarter services that align with the future of city living.

How does QuikBot Technologies integrate AI, IoT, and 5G to improve autonomous delivery systems?
QuikBot uses 5G for wireless communication between our devices such as robots and lockers as well as IoT-enabled lifts to share information with our cloud service. Our robots employ AI technology to plan and execute navigation based on data collected by a myriad of on-board sensors, so that deliveries are performed safely and efficiently without the need for human intervention.

What innovations in smart city infrastructure do you think are crucial to supporting widespread autonomous mobility?
Several key innovations in smart city infrastructure are critical to enabling the widespread adoption of autonomous mobility. These advancements support safe, efficient, and scalable operations for autonomous vehicles across last-mile logistics, public transport, and service robotics.

One essential development is the creation of digitally managed urban spaces. Roads, pavements, and access points are being equipped with sensors, smart signage, and connected systems that help autonomous vehicles navigate safely and adapt to changing conditions. Features such as adaptive traffic lights, automated pedestrian crossings, and dynamic loading zones create a responsive environment where autonomous systems can operate reliably.

High-speed, low-latency connectivity is equally important. Technologies like 5G and dedicated IoT networks ensure continuous communication between autonomous vehicles, control systems, and cloud platforms. This connectivity supports real-time decision-making, remote monitoring, and efficient fleet coordination at scale.

In Singapore, the Open Digital Platform at Punggol Digital District is a strong example of how digital infrastructure supports autonomous systems. Acting as a central operating system for the district, it allows government agencies, businesses, and technology providers to access and share real-time data. With integrated digital twins and predictive analytics, the platform enables coordinated, intelligent operation of autonomous services in a live urban environment.

Smart building integration is another key requirement. For autonomous systems to function end-to-end, buildings need to support automated access with features like intelligent lifts, turnstiles, and secure delivery lockers. This ensures smooth transitions between public spaces and private infrastructure.

Interoperable data platforms also play a vital role. These systems enable secure data sharing between city planners, logistics providers, and infrastructure managers, allowing for better routing, urban planning, and coordination of services.

Finally, modular microhubs are essential for decentralised logistics. These facilities support charging, maintenance, cross-docking, and local storage. Strategically placed microhubs reduce delivery distances, ease congestion, and improve the operational efficiency of autonomous fleets.

Together, these infrastructure elements form the foundation of smart, autonomous cities, enabling technology to serve urban populations with speed, intelligence, and sustainability.
‍

What trends in connected mobility and autonomous vehicles should businesses watch closely?
In the evolving landscape of connected mobility, several key trends are redefining last-mile delivery. These developments offer businesses new ways to improve efficiency, lower costs, and remain competitive in rapidly changing urban environments.

One major trend is the emergence of connected autonomous delivery fleets. Enabled by vehicle-to-everything (V2X) technology, these vehicles communicate with traffic systems, infrastructure, and cloud platforms in real time. This connectivity allows for dynamic routing, responsive navigation, and better coordination in congested areas, resulting in faster and more reliable deliveries.

The shift toward Platform-as-a-Service models is also reshaping how businesses adopt autonomous delivery. Rather than owning and managing delivery robots or vehicles, companies are subscribing to full-service platforms that cover hardware, software, maintenance, and operations. This model reduces capital expenditure, simplifies scaling, and provides greater operational flexibility.

Decentralised microhub networks are playing a growing role in last-mile strategies. By positioning goods closer to consumers, microhubs shorten delivery distances and support round-the-clock operations. When integrated with autonomous fleets, they help reduce congestion and emissions while improving delivery responsiveness.

Autonomous delivery systems also generate valuable operational data—from route performance and energy use to delivery success rates. With AI and analytics, businesses can turn this data into insights that improve decision-making, reduce costs, and enhance service quality.

Smart infrastructure integration is becoming essential. Buildings equipped with automated lifts, secure lockers, and smart access systems enable seamless handover between robots and recipients. Businesses that invest in robotics-ready facilities will be better positioned to adopt autonomous solutions at scale.

Regulatory trends are also accelerating the shift toward cleaner, smarter last-mile delivery. As more cities implement low-emission zones and curb access controls, autonomous electric vehicles offer a practical, compliant alternative that maintains delivery performance while meeting urban sustainability goals.

‍

How do you see quantum computing influencing AI and robotics in the near future?
Quantum computing has the potential to reshape the future of AI and robotics, though its immediate impact will remain exploratory. Still, the foundational capabilities it introduces are significant, particularly for industries operating in data-heavy and dynamic environments like autonomous robotics.

One of the most promising applications lies in solving complex optimisation problems. Tasks such as delivery route planning, fleet resource management, and real-time decision-making often overwhelm classical systems when variables increase. Quantum algorithms may eventually offer faster, more accurate solutions, enhancing the responsiveness and efficiency of autonomous platforms.

Quantum computing could also accelerate machine learning. Training advanced AI models typically demands substantial computational power and time. Quantum methods may reduce this burden, especially for large datasets and deep learning models, enabling faster development of AI systems that are more adaptive and context-aware.

In robotics, particularly for autonomous delivery and service operations, critical functions like sensing, path planning, and environment mapping depend on rapid data processing. While quantum systems are not yet suitable for real-time control, they could support simulations, scenario planning, and decision pre-processing, helping robots navigate uncertainty more effectively.

Although the technology is still in its early stages, hybrid models that combine classical and quantum computing offer a practical path forward. These systems let developers explore quantum capabilities while relying on stable, existing infrastructure for core operations.

Over time, quantum computing could significantly enhance the way AI systems are trained, deployed, and scaled. For robotics companies managing complex urban navigation or fleet orchestration, early exploration of quantum technologies will be key to unlocking future performance gains and staying ahead in an increasingly automated world.

‍

What industries do you believe are still underutilizing AI and robotics, and why?
Despite the increasing maturity of AI and robotics, several sectors remain underutilised. Healthcare logistics, facilities management, and education still offer significant opportunities for automation, particularly in non-core, repetitive tasks that continue to rely on manual labour.

In healthcare, robotics is still largely confined to clinical or surgical applications, while non-clinical logistics such as medication delivery, specimen transport, and waste handling are often performed manually. These tasks consume valuable staff time and introduce inefficiencies. Autonomous robots can manage them safely and reliably, but adoption is slowed by regulatory concerns, legacy systems, and resistance to operational change.

Facilities management faces similar challenges. Many buildings, campuses, and mixed-use developments still depend on human labour for cleaning, security rounds, and internal logistics. Robotics can standardise service quality, reduce costs, and enable 24/7 operations, yet uptake remains limited due to fragmented ownership structures, tight budgets, and a lack of integration-ready platforms.

In education, especially on large campuses, AI and robotics are typically focused on teaching tools, leaving operational processes overlooked. Tasks like document transport, meal delivery, and sanitation could be handled by autonomous systems, improving efficiency without disrupting learning environments. However, investment continues to prioritise academic technologies over service automation.

In each of these sectors, the main barriers are not technical but organisational. As Platform-as-a-Service models become more accessible and scalable, these industries will be better equipped to modernise operations and realise the benefits of intelligent automation.

How can startups leverage AI and emerging tech to gain a competitive advantage in highly saturated markets?
Startups can gain a competitive edge in saturated markets by leveraging AI and emerging technologies to prioritise speed, precision, and clear differentiation. Unlike larger companies constrained by legacy systems, startups have the agility to build technology-first operations from the outset.

AI enables hyper-personalisation and decision automation, allowing startups to tailor customer experiences, streamline workflows, and respond quickly to market shifts. Tools like recommendation engines, dynamic pricing, and predictive analytics help target niche segments more effectively and improve operational agility.

By adopting platform-based or infrastructure-light models, startups can avoid heavy capital investment. Cloud-native systems and automation reduce the need for physical fleets or manual labour, making this especially valuable in logistics, healthcare, and retail, where scale and efficiency are critical.

Data also becomes a strategic asset. Startups can generate and analyse real-time data from sensors, user behaviour, or autonomous systems to gain insights that guide product development, improve service delivery, and personalise engagement. In crowded markets, owning and using high-quality data offers a lasting competitive moat.

Emerging technologies like computer vision, natural language processing, and edge computing further allow startups to build smoother, more intuitive user experiences. These tools enhance service quality and strengthen customer loyalty.

Most importantly, startups can challenge legacy models by using AI and robotics to replace outdated processes, reduce cost, and reshape customer expectations. This ability to innovate quickly and rethink how value is delivered sets them apart in even the most saturated industries.

‍

Looking ahead, what technology-driven disruptions do you foresee reshaping the APAC business landscape?
Several major technology-driven shifts are set to reshape the APAC business landscape. One of the most immediate is the rise of AI-led automation across logistics, services, and administrative functions. With rising labour costs and ongoing talent shortages, businesses are adopting AI to manage last-mile delivery, warehouse operations, finance tasks, and customer service. This is particularly impactful in sectors like retail, healthcare, and facilities management, where automation can improve efficiency and reduce reliance on manual labour.

Smart city infrastructure is another area of rapid transformation. Governments across the region are investing in connected urban systems, with initiatives like the Open Digital Platform at Punggol Digital District in Singapore showcasing what’s possible. By integrating real-time data, autonomous systems, and public-private collaboration, these platforms enable businesses to deploy autonomous fleets, optimise energy use, and deliver seamless tech-enabled services within digitally managed environments.

Sustainability and cross-border digitalisation will also play defining roles. Businesses are being pushed to adopt green technologies and emissions tracking tools as regulations tighten and consumer expectations shift. At the same time, digital trade frameworks and blockchain-enabled supply chains are making it easier for small and medium enterprises to access regional markets. The expansion of 5G and edge computing will further enable real-time services and help businesses reach underconnected areas, creating more equitable access across the digital economy.

‍

Contact Mr. Alan Ng