A new 2026 Enterprise AI Maturity Index from ServiceNow found that the proportion of Singapore enterprises using agentic AI more than doubled in a single year. It rose from 22% in 2025 to 51% in 2026. That’s a substantial change in just twelve months. Agentic AI is different from the more familiar form of generative AI many people have already been using. A typical generative AI tool might help you write an email, summarise a document, brainstorm ideas or create an image. An AI agent can go further. The idea is that it can perform actions and work through multiple steps towards an objective, rather than simply producing an answer to a single prompt. That creates enormous possibilities. Imagine an AI system that doesn’t just draft a customer email, but: • receives the enquiry; • identifies what the customer needs; • checks the relevant information; • prepares a response; • updates the appropriate system; • flags anything that requires human judgement; • and records what happened. That’s a very different proposition from asking ChatGPT to write an email. It’s closer to having a digital worker operating inside a defined workflow. But there’s a catch.
Adoption isn’t the same as transformation
This is where the Singapore figures become particularly interesting. Despite 51% of enterprises using agentic AI, only 10% reported having redesigned processes so AI could complete multi-step business tasks end-to-end. Meanwhile, the largest group — 33% — were using AI primarily to assist individual employees with day-to-day tasks. That distinction is easy to miss. A business can have AI everywhere and still operate fundamentally the same way it did before. Someone might use AI to write reports. Another employee might use it to summarise meetings. Someone else might use it to create spreadsheets. A manager might use it to draft presentations. The marketing department might use it to create social posts. The customer-service team might use it
to draft replies. Every individual becomes slightly faster. But the underlying workflow remains exactly the same. The result can be faster busyness. And faster busyness isn’t necessarily productivity.
The AI productivity trap
There’s a question I think we should be asking more often: Are we using AI to make work better, or simply to help people cope with too much work? Those sound similar. They aren’t. Imagine an employee who spends six hours a day dealing with emails, spreadsheets, meetings, reports and administrative tasks. You give them an AI assistant that makes them 20% faster. That sounds like a win. But what happens next? If the organisation responds by giving that person 20% more work, the benefit hasn’t necessarily gone to the employee. The organisation has simply increased output. The person may still finish the day exhausted. They may still have no time to think. They may still take work home. They may still feel permanently behind. And eventually, the organisation may wonder why the person is burning out despite having better technology. That’s the problem with measuring productivity purely by volume. More output isn’t automatically a better working life. The number that really caught my attention The 51% figure makes a good headline. But for me, the 10% figure is more revealing. Only one in ten Singapore enterprises surveyed had reached the point where AI was being used to complete multi-step business processes end-to-end. That suggests a huge gap between “We have AI” and “We have redesigned the way we work around AI.” Those are completely different stages. And I think this distinction will become increasingly important over the next few years. Because buying another AI tool is relatively easy. Changing a workflow is harder. Changing responsibilities is harder. Changing systems is harder. Deciding which decisions should remain with humans is harder. Working out where AI should have autonomy — and where it shouldn’t — is harder. But that’s where the real gains may eventually come from.
The difference between an AI tool and an AI system Think about a simple example. Suppose you’re running a small business. Every week you need to: check incoming enquiries; respond to customers; follow up unanswered messages; update your spreadsheet; prepare social content; review website analytics; create invoices; organise appointments; and identify outstanding tasks. You could buy eight different AI tools. One for emails. One for social media. One for analytics. One for invoices. One for meetings. One for customer service. One for writing. One for task management. You might become very good at using AI. But you could also end up with eight more things to manage. Alternatively, you could step back and ask: “What does this workflow actually look like from beginning to end?” That question changes everything. Perhaps the real problem isn’t that writing emails takes too long. Perhaps the real problem is that the same customer information is being copied between four different systems. Perhaps the real problem isn’t that social posts take too long. Perhaps nobody has defined the content process clearly enough. Perhaps the real problem isn’t that meetings need better summaries. Perhaps there are too many meetings. This is where calm productivity and AI start to overlap.
AI shouldn’t just make you faster
There’s a temptation in the productivity world to celebrate speed. Faster writing. Faster emails. Faster research. Faster content. Faster meetings. Faster decision-making. But faster isn’t always better. Sometimes the smartest productivity improvement is simply: don’t do the thing. That’s particularly important for anyone who has experienced burnout recovery and calmer ways to work. When you’re already overloaded, the answer isn’t necessarily to become more efficient at carrying an impossible workload. Sometimes you need to reduce the workload itself. That might mean: removing unnecessary meetings; automating repetitive administration; creating templates; simplifying approval processes; batching communication; setting clearer boundaries; reducing duplicate work; or deciding that a particular task doesn’t need doing at all. AI can help with some of these things. But only if we first understand the work.
The calm productivity question
I’ve become increasingly interested in a different way of thinking about productivity. Instead of asking “How much more can I get done?” ask “What can I remove without reducing the quality of what matters?”
That’s a very different mindset. It doesn’t mean becoming lazy. It doesn’t mean lowering standards. It doesn’t mean avoiding ambition. It means recognising that human attention is limited. Every unnecessary task consumes some of it. Every notification interrupts it. Every context switch costs something. Every meeting has an opportunity cost. Every piece of duplicated administration takes energy that could have been used elsewhere. And once you start looking at work through that lens, AI becomes much more interesting.
What agentic AI could mean for ordinary workers
The conversation around agentic AI often focuses on large enterprises. But the underlying idea could eventually have a much more practical impact on ordinary workers and small businesses. Consider a freelancer. Instead of spending an hour every Monday checking which clients need follow-up, an AI system could potentially monitor agreed information and flag the exceptions. Consider a therapist. Instead of manually organising repetitive administrative information, appropriately designed systems could potentially prepare structured information for review — while leaving clinical judgement firmly with the professional. Consider a small online business. Instead of checking several platforms every morning, a workflow could potentially bring the relevant information together and highlight what actually needs attention. Consider a content creator. Instead of starting every article from a blank page, a structured system could help move an idea through research, outlining, drafting, editing and distribution. The point isn’t to eliminate the human. It’s to stop making the human repeatedly perform the parts of the process that machines are increasingly capable of handling.
But autonomy needs boundaries
This is where the conversation needs some balance. Agentic AI shouldn’t be treated as magic. Giving an AI system the ability to take actions creates different risks from simply asking it to generate text. The more autonomy a system has, the more important questions around permissions, monitoring, data, security, accuracy and accountability become. ServiceNow’s research highlights this wider issue too. Its global 2026 research found that organisations are rapidly adopting agentic AI, while many are still struggling with fragmented systems, governance and disconnected workflows. So the future isn’t necessarily “Give AI control of everything.” It is more likely to be “Give AI responsibility for clearly defined tasks, within clearly defined boundaries.” Humans remain responsible for judgement, relationships, ethics and decisions where the consequences matter. AI handles the repetitive process around those decisions. That distinction could become one of the most important workplace skills of the next decade.
Singapore has another interesting lesson
The Singapore research isn’t only about adoption. The country’s overall AI maturity score rose to 53 out of 100 in 2026, up from 34 in 2025 and above the global average of 51. The research also found that Singapore was ahead of global averages in several foundational areas, including modernising legacy systems, AI risk processes and integrating AI workflows across business functions. But AI-enabled workflows remained the weaker area. In other words: the foundations are improving. The challenge is turning those foundations into redesigned work. That’s a useful lesson for businesses everywhere. You don’t build a calmer and more productive organisation simply by purchasing better technology. You build it by deciding how work should happen. Then you choose technology that supports that design. Not the other way around.
Don’t automate a broken process
This might be one of the most important rules for anyone experimenting with AI. Don’t automate a process simply because it already exists. Ask why it exists first. A process that requires six approval steps might not need a faster approval system. It might need two approval steps. A weekly report might not need to be generated automatically. It might not need to exist. A meeting might not need better AI notes. It might not need to happen. An inbox might not need an AI assistant capable of drafting hundreds of responses. Perhaps the organisation needs fewer incoming requests. Automation can make bad processes faster. It doesn’t automatically make them good.
What this means for someone building a calmer business
This is where the idea becomes especially relevant to people who want to build income without recreating the same pressure they were trying to escape. If you’re building a small online business, you don’t need to become an AI expert overnight. You can start much smaller. Look at one repeated process. For example: content creation. Perhaps your current process looks like this: idea → research → outline → draft → edit → image → Pinterest → social media → email → website. Write every step down. Then ask: which steps genuinely require me? Maybe the ideas need to come from you. Maybe the final editorial judgement needs to come from you. Maybe the personal story needs to come from you.
But research organisation, first drafts, repurposing, formatting, metadata and content scheduling might be partially systemised. Suddenly, instead of asking “How can AI create my content?” you’re asking “How can I build a content system where AI handles the repetitive parts while I keep ownership of the thinking?” That’s a much healthier relationship with technology — and it’s the same principle behind building income without sacrificing wellbeing inside The Calm Hustle.
AI should protect attention, not consume it
One of the biggest risks with modern technology is that every efficiency creates an opportunity for more activity. You answer emails faster. So you receive more emails. You create content faster. So you publish more content. You automate customer service. So you take on more customers. You speed up administration. So someone adds another responsibility. There is nothing inherently wrong with growth. But if every productivity gain immediately becomes another demand, people never experience the benefit. That’s where burnout can creep back in. A calmer approach asks: where does the saved time go? If AI saves you five hours a week, those five hours don’t automatically belong to work. Perhaps some should go towards family; exercise; rest; creative thinking; learning; relationships; or simply having an evening where you aren’t rushing. That isn’t wasted productivity. That’s the point of productivity.
The real opportunity isn’t doing everything faster
Imagine two businesses. Business A. The owner uses AI to produce twice as much content, answer twice as many emails and launch twice as many projects. Revenue increases. So does workload. Business B. The owner uses AI to remove repetitive administration, simplify customer journeys and reduce unnecessary tasks. Revenue grows more slowly. But the owner gets evenings back. Which business is more successful? The answer depends on what success means to you. If success is purely revenue, perhaps Business A wins. But if success includes health, relationships, freedom and sustainability, the calculation changes. This is why I think the AI conversation needs another dimension. We need to talk about the quality of the life that increased productivity creates.
A simple framework for using AI without creating more chaos
If you’re experimenting with AI, try this five-step approach.
- Notice. Write down the repetitive tasks you perform every week. Don’t start with technology. Start with reality. What actually takes your time? 2. Question. For each task, ask: does this need to happen? If the answer is no, remove it.
- Simplify. If it does need to happen, ask whether the process can be made simpler before introducing AI.
- Automate. Only then consider whether AI or automation can handle some or all of the process. Start with low-risk, repetitive tasks.
- Protect. Decide what you will do with the time you save. This final step is easy to overlook. But it may be the most important one. If you don’t protect the time, someone — or something — will eventually fill it.
What Singapore’s 51% figure really tells us
The headline is: agentic AI adoption in Singapore doubled to 51%. That’s impressive. But the more useful lesson is hidden behind it. Only 10% had reached end-to-end workflow transformation. So perhaps the next phase of AI isn’t going to be about who owns the most AI tools. It may be about who understands workflows best. The businesses that benefit most may not necessarily be the ones with the biggest AI budgets. They may be the ones willing to ask uncomfortable questions. Why do we do this? Why does this require three people? Why does this need six approvals? Why are we copying this information? Why are we holding this meeting? Why are people working late to complete something that could be redesigned? Those questions aren’t particularly glamorous. But they are where transformation begins.
The future of work shouldn’t mean working constantly
There’s a strange contradiction in the way we talk about technology. For decades, we’ve been promised that better technology would give us more leisure. Instead, many people feel permanently connected. Email followed us home. Smartphones put work in our pockets. Cloud software made it possible to work anywhere. Now AI can help us work faster. So the question is worth asking: are we going to use this technology to create more work — or finally use it to create more room for life? I don’t think there’s a technological answer to that question. It’s a human one. Technology can give us possibilities. We decide what those possibilities are used for.
From hustle to leverage
This is also why I’m interested in the difference between hustle and leverage. Hustle says: do more. Leverage says: build something that keeps working without requiring all of your attention.
Hustle says: work harder. Leverage says: improve the system. Hustle says: fill every hour. Leverage says: protect the hours that matter. AI can become leverage. But it can also become another form of hustle if we’re not intentional about how we use it. The technology isn’t automatically calm. The system around the technology determines that.
Five questions to ask before adding another AI tool
Before signing up for another AI platform, ask yourself: 1. What specific problem am I solving? If you can’t answer this clearly, you probably don’t need the tool yet. 2. Will this remove work or create another thing to manage? More software isn’t automatically more productivity. 3. Can I simplify the process first? Sometimes the best automation is deleting a step. 4. What still needs human judgement? Make that boundary clear. 5. What will I do with the time I save? This is the question most productivity systems forget.
AI and burnout: the conversation we need to have
Burnout isn’t caused by a lack of productivity apps. And AI isn’t going to solve burnout on its own. But thoughtfully designed systems can potentially reduce some of the repetitive work that contributes to overload. That’s an important distinction. We shouldn’t sell people the idea that an AI assistant will magically make them calm. It won’t. If your workload is fundamentally unreasonable, an AI tool might simply help you complete an unreasonable workload faster. The deeper solution is to look at the entire system: workload; expectations; boundaries; processes; staffing; communication; recovery; autonomy. And then ask where technology genuinely helps. That is a much more useful conversation than simply asking which AI tool is trending this week.
A calmer AI future is possible
The 51% figure from Singapore shows how quickly AI adoption can change. But the 10% figure reminds us that adoption isn’t the destination. The real challenge is transforming how work happens. And perhaps that’s good news. It means we don’t have to chase every new AI development. We can step back. We can look at our own work. We can identify what drains attention. We can remove what doesn’t matter. We can simplify what does. And then we can use technology where it genuinely helps. That’s a much calmer way to approach the AI revolution.
Not “How can I use AI to do more?” But “How can I use AI to spend more of my limited attention on the things that actually matter?” Because ultimately, productivity isn’t about filling every available minute. It’s about making room for the life you’re trying to build. And if AI is going to transform the way we work, perhaps that’s the transformation we should be aiming for.
Frequently Asked Questions
What is agentic AI? Agentic AI refers to AI systems designed to take actions and work through tasks with less human input at each individual step. Unlike a simple chatbot that responds to a prompt, an agentic system can potentially plan and execute multiple steps towards a defined objective. How much has agentic AI adoption increased in Singapore? According to ServiceNow’s 2026 Enterprise AI Maturity Index, adoption among Singapore enterprises increased from 22% in 2025 to 51% in 2026. How many Singapore companies are using AI autonomously? The same research found that 10% of Singapore enterprises had redesigned processes so AI could complete multi-step business tasks end-to-end. Does AI automatically make people more productive? No. AI can make individual tasks faster, but genuine productivity improvements depend on how work is organised. Using AI to accelerate unnecessary or poorly designed processes can simply create more activity rather than better outcomes. Can AI help reduce workplace burnout? AI may help reduce some repetitive administrative work, but it isn’t a treatment for burnout. If someone’s workload, expectations or working environment are unsustainable, adding technology alone may not solve the underlying problem. What is the best way to start using AI at work? Start with one repetitive, low-risk process. Understand the workflow first, remove unnecessary steps, then identify where AI or automation could help. Keep human oversight where judgement, privacy, safety or important decisions are involved.
The Calm Hustle takeaway
AI is changing quickly. But you don’t have to chase every new tool. Start with your work. Find what repeatedly drains your attention. Ask whether it needs to happen. Simplify it. Then automate what makes sense. And when you save time, don’t automatically give that time back to work. That may be one of the most important productivity habits of the AI era.
The goal isn’t to become a machine that can work faster. The goal is to use machines intelligently enough that you can spend more of your life being human.
Want a calmer approach to work?
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