The pandemic interrupted businesses worldwide, with offline corporations, particularly restaurants, bearing the brunt of the worldwide lockdown. Despite the ease of restrictions, customers were too reluctant to dine out.

The global crisis has altered the user experience by balancing technology and authentic experiences and the customer’s role in the value chain. Market disruption has compelled restaurants to innovate and go digital in nearly every aspect of their operations.

The turning point in the food tech and online ordering space was the introduction of third-party delivery apps, also known as food aggregators. Consumers accustomed to doing everything online increasingly expected the same experience, convenience and transparency when ordering dinner.

Aggregators offer access to multiple restaurants through a single portal where consumers can opt for one-tap delivery, compare menus, prices, and reviews. The players in this category provide the logistics for the restaurant and are compensated by the restaurant with a fixed margin of the order.

While food aggregators give restaurateurs a good customer base and order volumes, paying commissions to aggregators takes away restaurants’ revenues. Also, the app owns customer data, not the restaurant.

While third-party apps offer restaurant delivery through their network, the last-mile delivery experience for the customer is still powered by the aggregator and not the restaurant.

Customer loyalty in the food industry is unparalleled to anything I’ve ever seen. Once you like food from a restaurant, you’ll end up ordering from them, no matter how difficult it is to order from them.

During the lockdown in Malaysia, a person got in a helicopter to get food from his favourite restaurant. Even on third-party aggregators, most orders that a restaurant receives are repeat orders. 

Therefore, restaurants soon realised it’s not enough to digitise just the ordering process. Restaurants that are successful develop strong relationships with their customers. This compelled restaurants to invest in technologies that aid in building a solid customer bond and delivery automation.

Taking control of both sides of the experience– ordering and delivery have helped restaurants engage customers with their brand experience and boost direct business, allowing the company to become self-sufficient in order fulfilment, thus supporting customer loyalty.

Restaurants went digital by introducing new technologies to automate ordering, like progressive web apps (PWA) and SMS/Whatsapp ordering. PWAs are Web-based experiences that resemble mobile apps but do not require users to download anything.

A PWA for restaurants would display menus, enable selection, place orders, and pay. With SMS or WhatsApp ordering, users can place their orders through messaging apps. Restaurants use both these technologies and multiple CX tools to maximise customer engagement.

Also Read: The spotlight on foodtech: Why we believe that what we put on our plate will determine the future

And, for all of these techniques to work around each other, they must be linked to the restaurant’s existing point-of-sale (POS) systems. While traditional POS systems enable restaurant operations to perform smoothly, new-gen restaurant Operating Systems (OS) will proactively help restaurant owners to make insightful decisions using data and help provide a superior UX for their customers.

In the future, restaurants will become more and more dependent on an ever-changing digital ecosystem. Apps, services, and personal AI assistants will serve as the eateries’ primary contact points with their customers. AI will play a significant part in consumer decisions, and restaurants will require access to relevant and detailed data.

The data collected would be used to create new menus or implement real-time pricing based on supply and demand changes. With all this new digital ecosphere evolving, restaurants will be forced to adapt or build entirely new data collection methods and IT structures.

Also Read: Meet the 10 agritech, foodtech startups pitching for Future Food Asia’s US$100K grand prize

Virtual assistant platforms would be used as direct marketing channels for brands, with algorithms responding to price fluctuations and other data. Because of these large datasets available, consumers’ choices will become easier to determine and will effectively lower costs for restaurants, both acquiring cost per user and delivery cost per user.

Initially, technology apps were intended to serve as two-sided marketplaces, connecting customers and restaurants. They were concerned with being a resource, joining the two parties, and stepping aside.

However, the perimeter between technology and the physical world is now being infringed due to consumption shifting to the digital turf.

It has become more critical than ever for restaurants to build self-sustained capabilities and become truly autonomous.

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We are living in an era defined by an explosion of data and digital content. The sheer volume of information available today is growing exponentially, fuelled by the internet, advanced computing, and now, generative AI.

By 2035, the world is projected to generate more than 200 zettabytes of data annually. AI can now produce high-quality articles, detailed reports, designs, and even medical analyses in seconds—tasks that used to take humans days or weeks.

This flood of data is both a benefit and a burden. While AI can quickly generate and process information, humans are best at using it for human needs. We excel at functional thinking, planning for the future, and making decisions that require ethics and context. But our ability to process large amounts of information is limited.

Take Nia Patel, a financial analyst. Her work involves analysing market trends, regulations, and customer feedback—a task that becomes harder each year as the data piles up. Despite her skills, she often found herself overwhelmed, wondering, How can one person keep up with so much information?

The reality is no one can. Human brains are powerful, but they have limits. When the volume and speed of data outpace our abilities, fatigue, bias, and errors set in. That’s where AI comes in, not to replace humans, but to help them succeed.

Humans and machines: A partnership for the future

The idea of humans working alongside machines isn’t new. During the Industrial Revolution, machines helped humans produce more goods faster and more efficiently. In the future, AI will do for knowledge work what steam engines did for physical labor—freeing us from repetitive tasks so we can focus on creativity, strategy, and innovation.

Also Read: The benefits of custom skills based training in the modern workforce

In the 21st century, businesses aren’t driven by war or borders; they’re shaped by consumers and their ever-changing needs. The focus is on understanding people’s preferences, behaviours, and lifestyles. Instead of mass-producing generic goods, companies use AI to create personalised products and services that align with specific customer needs.

By 2040, businesses will rely on AI to predict trends, analyse markets, and adapt to demographic changes in real time. The companies that succeed will be those that use AI to understand their customers on a deeper, more scientific level. This will allow businesses to stay ahead in a world where consumer expectations evolve faster than ever before.

Humans have always sought to build better, more powerful tools. From the plow to the printing press, from steam engines to computers, each invention has pushed society forward. AI is the next step in this journey. It will help humans tackle challenges that once seemed impossible, giving us capabilities we’ve never had before.

The science of future consumerism

In the 21st century, businesses use neuroscience, psychology, and behavioural science to create products that people can’t resist. AI analyses brain activity, emotional triggers, and decision-making patterns to design products and services that meet consumers’ needs perfectly.

For example:

• Retail: AI personalises your shopping experience, suggesting products you didn’t even know you wanted.
• Advertising: AI makes sure you see ads that feel relevant and timely, boosting sales and satisfaction.
• Product design: AI gathers feedback and market trends to design products that match what consumers want.

Companies that embrace this AI-driven, data-rich approach will thrive in the future economy. Those that ignore it risk falling behind.

Also Read: Human-driven interaction in an AI driven world

The future of work: A new collaboration

The partnership between humans and AI will transform industries:

• Healthcare: AI analyses medical data and scans quickly and accurately, helping doctors make more diagnoses and treatment plans per day, addressing doctor shortages.
• Law: AI handles legal research, finding relevant cases in seconds, while lawyers focus on strategy and client advocacy, solving backlogs and reducing errors.
• Engineering: AI runs simulations and stress tests, giving engineers the freedom to innovate and solve complex problems.

Humans will excel at planning, decision-making, and creative thinking, while AI handles data processing, automation, and routine tasks. Together, they will create a seamless workflow where each does what they do best.

The workplace will no longer be about humans vs. AI. Instead, it is about humans and AI thriving together. Productivity will soar, errors will drop, and people like Patel will be free to focus on meaningful work—creating, strategising, and imagining the future.

In this world, knowledge workers won’t be limited by their own minds. AI’s processing power will amplify human creativity and judgment. This new era—the Age of Symbiosis—will be one where humans and AI lift each other to new heights.

The future is collaboration

As Patel closed her laptop at the end of the day, she knew her AI partner was still at work, analysing and refining data. She smiled, knowing the future wasn’t about humans or AI working alone, but about what they could achieve together.

It’s not the end of work; it’s the beginning of better work.

The future isn’t people or machine. The future is people with machine.

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At Echelon Singapore 2025, a panel delved into Southeast Asia’s progress in tackling climate change and the growing role of its climate tech ecosystem.

Referencing an ESCAP report that warns the region has just five years left to meet its decarbonisation goals, speakers underscored that urgency often drives innovation—and climate change presents one of the most pressing opportunities for entrepreneurship. They emphasised the importance of regulation in setting clear decarbonisation standards, noting Europe as the global benchmark and Singapore as Southeast Asia’s closest example of effective implementation.

The discussion also explored how to nurture and accelerate climate tech startups, focusing on building sustainable, investment-ready business models that balance environmental impact with financial viability. The panel ultimately highlighted collaboration among governments, investors, and innovators as key to achieving meaningful and scalable progress in the region’s transition to a low-carbon economy.

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At Echelon Singapore 2025, a panel explored how artificial intelligence is driving scalable growth in complex industries. Speakers discussed both the short- and long-term implications of AI, highlighting how sectors such as law and banking have already undergone transformation, while others like mining are still on the cusp of disruption.

For AI startups to succeed in these industries, founders must understand the current technological landscape, anticipate what’s next in development, and plan for both immediate and future integration. The panel emphasised that complexity within industries—particularly in areas like supply chain—creates rich opportunities for innovation. However, startups must approach these sectors thoughtfully: rather than aiming for disruption, they should focus on enhancement, enabling AI solutions to integrate seamlessly and deliver measurable value.

By prioritising practical adoption over radical change, AI innovators can drive sustainable and scalable impact across traditionally intricate and regulated industries.

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Home security cameras are everywhere. They promise peace of mind, but often deliver the opposite: endless pings, meaningless alerts, and hours of footage that no one has time to sift through.

It’s a paradox of the smart home age: the more devices we add, the less clarity we seem to have. Notifications blur into background noise. Families ignore them. And when something truly urgent happens, it’s often discovered too late.

This is not a failure of hardware. It’s a failure of design.

Noise without context

Take the typical experience: you’re at work and your phone lights up, “motion detected in the living room.” You check, and it’s sunlight moving across the floor. Minutes later, another ping: the dog rolling over. Eventually, you swipe them away without thinking.

The pattern is familiar across smart home products: endless “automation” that still requires constant user intervention. Devices monitor, but they don’t interpret. They record, but they don’t advise. They’re smart in name, not in function.

The real promise of smart

A truly smart device should understand context. It should know the difference between background noise and a genuine event. It should anticipate patterns, act proactively, and communicate in a way that feels natural.

This means shifting from machine-like notifications to human-like conversations. Not “motion detected,” but “Your baby has been crying for ten minutes, do you want me to turn on the nursery camera?” Not a flood of raw data, but a single, timely message that matters.

Designing for real users

The most overlooked truth about smart home technology is that its core users aren’t technophiles, they’re everyday parents, caregivers, and seniors. These are people who don’t want to manage a complex interface. They want reassurance, quickly and simply.

That’s why design matters. Instead of forcing users into yet another app which needs to be learned, imagine if cameras could be managed through chat, a user behaviour that everyone is familiar. . Instead of navigating tabs and toggles, imagine texting a device the same way you text a friend.

This is what the next generation of smart homes should look like: intuitive, contextual, conversational.

Also Read: Smart nation, smart homes: How Singapore’s proptech ecosystem is redefining urban living

Privacy must evolve, too

With smarter systems comes a bigger responsibility: privacy. The EU’s GDPR has already flagged a critical flaw in current cameras: static “masking” that either blocks out too much or too little. A neighbour’s window might be masked to protect privacy, but that means you also can’t see what’s happening at your own front door.

New approaches, such as dynamic unmasking, can solve this. By using AI to identify and reveal only the relevant subject, say, a person lingering outside your door, it balances security with compliance. Privacy and protection don’t have to be at odds.

Toward agent AI

The real frontier is not just better cameras, but better agents. Devices that learn patterns over time and take small, appropriate actions without needing to be told. If every night at two am, you silence a stray motion alert, the system should learn. If you always ask for packages to be left at the door, the system should handle it for you.

This is what makes technology truly smart, not automating tasks after you ask, but anticipating needs before you do.

A call to rethink “smart”

The term “smart device” has been diluted by products that add features without solving problems. What users need now is not more information, but more clarity on the information relayed.

This shift will only happen when design centres on context, conversation, and care. As more innovators adopt this philosophy, we move closer to technology that earns trust — less noise, more clarity, and the quiet confidence that your home is truly looked after.

Designing for peace of mind

The future of smart home technology doesn’t lie in more sensors or sharper cameras. It lies in better judgment, systems that understand context, reduce noise, and communicate in ways that make sense to real people.

To get there, design priorities need to shift. Instead of piling on features, we need to focus on usefulness. Instead of flooding users with data, we need to deliver clarity. And instead of forcing people to adapt to technology, we should build technology that adapts to people.

“Smart” should mean more than being connected. It should mean considered, quiet, and genuinely helpful. Only then can these devices live up to their promise of not just monitoring our homes, but giving us the peace of mind we expected in the first place.

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