The Curious People Solutions Pte Ltd

08/09/2026

Someone recently asked us: why not just create an AI persona of your target market and run your research on that instead? Faster, cheaper, infinitely patient.

Here's the problem. A weather model doesn't need to get wet to predict rain. A flight simulator doesn't need to leave the ground to model flight. But notice — neither was ever asked to report what an experience felt like. That's the one job a synthetic persona is actually hired for, and the one job it structurally can't do.

Aviation figured this out decades ago — simulator hours are capped by federal law, no matter how advanced the simulator gets. Musicians know it too: you can practice alone at home every day, but that's not the concert.

We wrote up why this matters for anyone doing customer or employee research right now, before the "just wait for the next model" argument talks you out of it. 👇

"AI Can Simulate Your Customers. It Can't Live Their Experience."

07/09/2026

Every human interviewer carries invisible bias into the room. Even the best ones.

Confirmation bias, where the interviewer unconsciously listens for answers that fit what they already believe. Similarity bias, where responses from people "like them" get more weight. Leading questions, phrased just subtly enough to nudge an answer. And plain interviewer fatigue, where interview twenty feels nothing like interview two.

None of this is about bad intent. It's about being human. But it changes what gets collected, before analysis even begins.

HEARyou removes the human interviewer from the equation, without removing the human connection. Our AI-interviewer uses our proprietary Conversational Model consisting of conversational anchors and conversational triggers, letting the respondent's own narrative dictate the flow. Not a fixed script marching forward regardless of what's shared. A fluid structure that follows the shape of their story.

Traditional interviews are interviewer-led. HEARyou is interviewee-led. That single shift removes the biases baked into human-led structure, and opens the door to more open, more candid, more honest sharing.

Here's the part that matters most: if the data collected is contaminated by bias, no amount of clever analysis afterward can fix it. The starting point determines everything downstream.

Garbage in, garbage out has never been more true than in qualitative research. What's one interview bias you've seen quietly shape a "finding" that wasn't really true?

Learn more: https://www.thecuriouspeoplesolutions.com/hearyou-4biz

03/09/2026

2,101 F&B businesses closed in 7 months. 2,594 opened. Same rent, same CPF, same market. So it was never the cost.

Yet 83% of employers just named manpower cost their top challenge for 2026.

Here's the part nobody's saying out loud.

It definitely wasn't rent.

Rent actually fell as a share of F&B business costs — from 26% down to 17% since 2019. Retail rents have risen slower than inflation and slower than the economy. Rent caps have already been ruled out by the government.

That fight is over. In a land-scarce country, rent going up is weather. You don't file a complaint against a typhoon. You prepare for it.

CPF and LQS? Also weather. Announced years ahead, identical for every competitor. Which is exactly why they can't explain why the shop that closed, closed — and the one next door didn't.

So what did the survivors know?

They bet there were still customers worth chasing.

Food caterers grew 13.7% as diners moved to events. Fast food grew 4.8%. Meanwhile six in ten of the F&B businesses that shut in 2025 had been around five years or less — and 82% of those had never recorded a single profitable year. That's DPM Gan Kim Yong's own number, in Parliament.

That is not a cost problem. That is a listening problem.

And here's the painful part.

When you freeze wages and cut the training budget, you're not saving money. You're switching off the only people in your business who know why customers stopped coming.

Your staff know. Your customers know. Nobody ever properly asked them.

MTI said it plainly: cost pressure came "more from non-rental components," and to survive, businesses "must continually innovate their offerings."

Innovate for whom? Based on what? You cannot innovate for a customer you have never truly heard.

This is exactly why we built HEARyou.

Not another AI tool to help your staff type faster. A way for any business — including the SMEs employing nearly 70% of our workforce — to genuinely hear their customers and their people, in their own words. Four weeks. A fraction of what a consultancy charges.

48% of employers say they'll prioritise AI in 2027. Point it at the right thing.

Because manpower is not your cost. Manpower is the only thing you've got that can go find your next customer.

Cost is the weather. Demand fit is the boat.

Stop cursing the sky. Go check the shape of your boat.

—

If your 2027 plan is a wage freeze, ask yourself one question first: when did you last properly hear what your customers actually want to buy?

More Singapore employers plan wage freezes and increased AI focus in 2027 amid rising costs and cautious business outlook, says SNEF survey of 320 firms. Read more at straitstimes.com. Read more at straitstimes.com.

03/09/2026

We stopped guessing what Wang Café's customers wanted. We asked them properly. Here's what happened.

• Sales revenue increased by 20%.
• Compliment-to-complaint ratio improved by 900%.
• Staff attrition decreased by 60%.
• Competency development hours increased by 433%.

No six-week study. No five-figure invoice. No consultant embedded on site for months.

What we did instead was let customers and staff tell their own stories, in their own words, at their own pace — using our 3Ts Empathy Toolkit: Triggers, Tales, Truths. Then AI clustered hundreds of those stories into the recurring needs, gaps, and critical success factors that actually mattered.

The output wasn't a report nobody reads. It was the top three to eight customer experience gaps, actionable recommendations, and expected revenue outcomes with KPIs attached.

Here's the part that matters for anyone reading this: that same method now runs in five business days.

Not five weeks. Not five months. Five business days.

The reason most businesses guess about their customers isn't that they don't care. It's that real customer intelligence has always been too slow and too expensive to justify. That's the constraint we broke.

What would you do differently next quarter if you knew — not assumed — what your customers actually valued?

01/09/2026

Should AI labs be treated like the owners of dangerous animals?

Previous worries around AI and cybersecurity have focused on the harm that malicious humans could do with the technology. Autonomous hacking represents a new kind of risk.

01/09/2026

Someone who helped build AI just said the quiet part out loud

Fei-Fei Li is often called the "Godmother of AI." She built ImageNet, the project that helped kick off the whole deep learning era. She teaches at Stanford and co-founded its Human-Centered AI Institute.

So when she sat down with Bloomberg recently, it was worth listening.

Here's what she said: "Human capital, at the end of the day, is the most important resource of our world, and we want a thriving society of people, not a thriving society of just machines."

And this line stopped us in our tracks: a lot of people talk about AI making us more productive, but as she put it, that "doesn't automatically translate into shared prosperity."

We've been saying something similar for a while now. One person getting faster at their tasks doesn't automatically make a business better. Those are two different things, and treating them as the same is how organisations end up busy but no wiser and wealthier.

The institute she founded puts it simply. AI should be "designed to augment, not replace, people."

That's exactly how we built HEARyou. Not to replace the researcher. To let one researcher genuinely hear hundreds of people instead of a dozen — employees, leaders, customers. The three groups every business quietly depends on.

Her team also points out something we see constantly: today's AI still "lacks flexibility and contextual understanding." Which is precisely why understanding people properly can't be handed over to a machine and left there. Someone still has to be curious. Someone still has to listen.

Curiosity about people has always been, and will always be, our northstar.

The tools change. That doesn't.

(Full Bloomberg interview linked in the comments 👇)

28/08/2026

HEARyou: There's no cost excuse left not to understand your people!

This widely-shared Telegraph article warned that replacing entire human roles with AI often costs more than it saves, and can damage the social fabric between employer and employee. We agree entirely.

But the more important point buried in that story isn't really about cost. It's about scale of impact. Even where AI does boost personal productivity, there's no precise or reliable way to show that gain actually translates into business growth or organizational effectiveness. Personal efficiency and organizational progress are not the same thing — and treating them as interchangeable is where the "AI craze" leads businesses astray.

The more durable move, especially right now, is to stay focused on the people who actually make a business sustainable: its employees, its leadership, its customers. These three circles are interdependent, and no amount of personal AI productivity substitutes for genuinely understanding them.

For decades, that kind of deep qualitative insight was a luxury only large enterprises could budget for. HEARyou removes that barrier — not by replacing the researcher, but by letting one researcher's expertise reach hundreds of conversations instead of a dozen.

The three circles that hold any business together never stopped being worth understanding properly. Now there's no longer a cost excuse — or a productivity distraction — standing in the way.

Curiosity about People has always been and will always be the northstar guiding what we do as a business and in life!

The AI bubble will burst, and how that will happen is becoming discernible

18/08/2026

Slow isn’t the same as behind.

A recent BBC piece asked why Japanese firms are “so slow” to adopt AI — just 8.4% of workers use it day-to-day, against 50% in the US. The framing treats hesitation as a deficiency.

We’d offer another read.

Look closer at how Japanese companies actually deploy AI where they have adopted it: overwhelmingly for summarization, document creation, and information retrieval — not for wholesale disruption of product development or operations. That’s not timidity. That’s discernment.

And here’s the number that should give every organization pause: despite near-parity in “adoption rate” with the US, only 9% of Japanese firms said AI “greatly exceeded expectations” — versus 38% in the US. Fast adoption doesn’t guarantee value. It just guarantees adoption.

At The Curious People Solutions, this is the tension we sit inside every day as a human-centric innovation agency. New technology should never be embraced for embracing’s sake. It should be embraced with purpose — understood deeply, tested against real human need, and scaled only when it genuinely serves the people who’ll live with it.

Japan’s craftsmanship instinct — take the time, understand it fully, then build it to last — isn’t a barrier to innovation. It is innovation, done sustainably.

Three lessons we take into every engagement:
• Adoption without understanding is just noise dressed up as progress
• The measure of technology isn’t how fast it spreads, but how well it serves the humans behind the workflow
• Sustainability of humanity isn’t a constraint on innovation — it’s the whole point of it

What’s your organization’s relationship with “fast”? Are you adopting with purpose, or adopting to keep up?



Article:

Japanese risk aversion and conservatism blamed for slow AI take-up by the country's business sector.

09/08/2026

The most anxious person in your AI transformation probably isn’t who you think.

McKinsey surveyed 750 employees and leaders on AI readiness. One finding stopped us cold: middle managers report the highest anxiety about AI-related workplace change of any group — roughly one in four, versus one in five individual contributors.

We’d assumed it would be frontline staff, closest to task automation. It isn’t. Middle managers sit squeezed between executive mandates to redesign work and teams expecting stability from them — projecting confidence downward while privately unsure what their own role becomes.

McKinsey draws a sharp line here: reducing anxiety and building trust are not the same thing. Reassuring people that “AI won’t disrupt your job” may quiet the room. It rarely builds trust, especially when people suspect the reassurance can’t hold.

We’d add a harder truth underneath that: you cannot ask a middle manager directly whether they’re anxious and expect an honest answer — not because they’re being dishonest, but because asking inside a system their own boss can read is exactly what suppresses the truth.

This is the blind spot we built HEARyou360 to close. Instead of rating confidence on a form, HEARyou360 gathers stories — from peers, managers, and direct reports — through private voice conversation about specific incidents. The anxiety, or the confidence, surfaces inside the story, not inside a monitored answer to a monitored question.

McKinsey also found organisational readiness explains nearly twice as much of the AI value-capture gap as individual readiness alone. Middle managers are the connective tissue of that readiness. If they’re anxious and unheard, transformation stalls exactly where it matters most.

We don’t think McKinsey set out to describe our work. But the gap they named is the one HEARyou360 was built to close.



Report:

McKinsey research explores the AI readiness gap and why organizational readiness matters for scaling adoption and capturing enterprise value.

08/08/2026