Minds

CEO & Founder

Mindvalley

Certified Life Coach

Leathwaite: Executive Search

Asia Strategy & Transformation Practice

True Search

Partner, Greater China Country Lead

H.I. Executive Consulting (HIEC)

Partner, APAC Professional Services Practice

VCube International

Founder and Partner

Alcoa

Director of Strategy and Analysis, Asia-Pacific

Roland Berger

Deputy Project Manager/Senior Consultant, Consumer & Retail and Technology

A.T. Kearney

Business Analyst, Financial Services

Gavin is a transformtional leader in executive search and personal coaching, renowned for his expertise in elevating senior leadership in high-growth start-ups and scale-ups. Collaborating with private equity, venture capital funds, and founders across Asia, Gavin delivers strategic talent insights and pioneering thought leadership.

With an illustrious career that includes conducting over 20,000 executive interviews, Gavin’s mastery in talent identification and influence has driven the success of global companies like McKinsey & Company, L Catterton (LVMH), Accenture and Permira.

Gavin’s passion for connecting with people and unveiling their unique stories led him to establish "Empower Through Stories", an initiative that inspires and motivates the next generation of leaders through powerful narratives. 

An alumnus of Stanford and the University of Chicago, Gavin’s global experience spans the US, Italy, Singapore, China, and Thailand. His leadership continues to set benchmarks in excellence, innovation, and influence in the industry.

Email: gavin@mindssearch.com
IG: gavng89

Gavin Ng

I had an amazing conversation with Creasoft Capital — and it’s one every founder should pay attention to - 

Entrepreneurship and the quiet costs that rarely make it into public conversation.

According to a study by UCSF, entrepreneurs are nearly twice as likely to experience burnout and chronic stress compared to the general working population.

And McKinsey & Company  projects that 30–45% of tasks will be automated by AI, which sounds exciting — until you realise automation doesn’t reduce demands on your mind.
Sometimes it increases them.

Decision fatigue.
Constant adaptation.
Th pressure to lead a team through a landscape that shifts every quarter.

So here’s the real question for founders:

What happens to your energy, clarity, and mental resilience when your business, your people, and the world all fight for your attention at the same time?

That’s what Wajeeh H. and I explored — the true cost of entrepreneurship in an AI-driven decade.

🎧 Podcast is on the way.

Stay tuned.

Gavin

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#entrepreneurship #founders #AIfuture #mentalhealth #leadership #thecostofit

Investor | Founder | Executive Search Leader | Coach

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Meta just quietly signalled what every employee and leader needs to hear:
your future performance won’t just be what you do, but how much AI amplifies it.

From 2026, Meta will tie employee performance to “AI-driven impact.”

Not “Did you use AI?”
But: Did AI materially move your results?

Employees are being told to:

Use AI in day-to-day work.
Capture AI-fuelled wins in self-reviews.
Expect performance systems (and even review-writing) to be AI-assisted.

This isn’t just a Meta story.
It’s a preview of where performance culture is going.

Here’s what stands out to me:

🧠 AI literacy is shifting from “nice to have” to “core expectation.”
The question is no longer “Should I use AI?”
It’s “How irresponsible is it not to?” — especially in knowledge work.

⚡️ Performance is moving from effort-based to leverage-based.
It’s not just: “Did you complete the work?”
It’s: “How much did you use AI to multiply speed, quality, and output?”

🧩 The real differentiator won’t be AI access—it’ll be AI habits.
Everyone will have tools.
Few will build daily workflows: prompts, automation, internal copilots, AI-assisted thinking.

🚀 Companies are formalising an AI-native culture, not just AI tools.
When AI shows up in scorecards, hiring, promotion criteria, and even how reviews are written…
it stops being innovation and becomes muscle memory.

If you’re an employee, manager, or founder, here’s what I’d start doing now:

1️⃣ Rebuild your personal performance philosophy around leverage, not effort

Stop thinking in terms of “tasks completed” or “hours invested.”
Start thinking in terms of:

What did I accelerate?
What did I automate?
What quality did I improve?
What decision became sharper because of AI?

Your career advantage will come from showing compounding leverage, not incremental output.

2️⃣ Redesign your core workflows so AI becomes infrastructure, not an add-on

Pick 2–3 workflows that define your role: analysis, communication, research, reporting, client prep, project management.
Then ask:

Where can AI remove steps?
Where can it take the first draft?
Where can it pressure-test my assumptions?
Where can it replace low-value cognitive load?

Employees who make AI invisible (because it’s embedded everywhere) will outperform those who treat it as a tool they “use occasionally.”

3️⃣ Build a visible “AI impact narrative” — not a usage narrative

Management doesn’t care that you used AI.
They care what AI changed.

Create a simple track record you can point to:

Faster delivery cycles
Higher accuracy
Reduced manual work
Stronger client-facing outputs
Better decision frameworks
More scenarios explored per unit time

Now - What's the one thing that AI can meaningfully improve your performance?

- Gavin 

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#ai #executivesearch #aitalent

You don’t need the title “Head of AI.”
You just need one AI success metric.

In the past month, 3 mid-career professionals asked me the same quiet question:

“What can I possibly do next?
The job market pivots to AI. 
My skills feel… falling behind.”

They weren’t wrong.
AI has reshaped the talent market.
And many were never trained to use it.

But here’s the part most people misunderstand:
Recruiters aren’t looking for AI titles.
They’re looking for proof that you can deliver impact in an AI-enabled world.

Last week, I coached a senior corporate exec from a logistics company who felt “outdated.”
His CV said “AI Project Lead.”
But zero numbers. Zero proof.

We rewrote one line:

“Reduced onboarding time by 40% through AI automation.”

Within 2 weeks, his response rate tripled.

He didn’t become more “AI.”
He simply showed he could use AI to drive real business results.

That’s what the market rewards.

Because concrete metrics beat shiny titles every time.

More importantly — talent branding has shifted.
Your value is no longer your job title.
Your value is the impact you can prove.

Here’s the paradigm shift:

You don’t need to master AI.
You need to show how AI makes you more valuable.

And you can start small.

Here’s how to build your first AI success metric — even if you’re not technical:

1️⃣ Choose one task where AI can help you work faster.
Pick something you already do — drafting emails, analysing data, summarising meetings.
AI upgrades you.
This is your easiest path to a measurable win.

2️⃣ Use AI to reduce the time by 20–40%.
Ask AI to generate drafts, automate steps, or summarize.
Small wins count — they prove productivity.

3️⃣ Measure what changed.
Track minutes saved, errors reduced, or turnaround speed.
Numbers make your story credible.

4️⃣ Turn it into one CV bullet.
Grade-5 English.
Specific.
Impact-focused.

Like:
“Cut reporting time from 3 hours to 45 minutes using AI-assisted workflows.”

5️⃣ Update your LinkedIn intro with that one metric.
Leaders and investors notice people who can deliver, not just talk about AI.

This is how mid-career professionals stay relevant.
Not by chasing new titles — but by proving real-world value.

What’s one AI result you could show if someone asked you today for proof of impact?

– Gavin

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#CareerGrowth #Executivesearch #AI #mindssearch #ExecutiveCoaching

In Asia, I’ve watched great founders turn defensive, even destructive, when investor alignment broke down.

The first argument between founders and investors rarely happens in the boardroom.

It happens in the spreadsheet.
Revenue forecasts. 
Burn rates. 
Valuation and exit pressures.

The founder sees vision.
The investor sees math.
Both are right — and both are looking for a common ground.

Here’s the deeper truth:
Most founder–investor conflicts aren’t just about results.
They’re about rhythm.

The founder is playing the long game — obsessed with legacy, momentum, and the next horizon.
The investor is reporting quarterly — focused on discipline, clarity, and protecting capital.

One’s driven by conviction.
The other by validation.

The best founders learn to measure progress without shrinking their dream.
The best investors I’ve seen translate ambition into accountability — without killing belief.

5 practical moves to achieve this goal:
1. Translate Vision into Metrics
Sit down quarterly. Founder leads the “why.” Both define the “how to measure.”
Walk out with one shared story, two columns: vision + KPIs.

2. Build Dual Dashboards
Run two scoreboards side-by-side:
• Growth (users, brand, expansion)
• Governance (burn, margin, cash)
Review both monthly — no decision if one goes dark.

3. Agree on Non-Negotiables
Founders list 3 red lines (e.g. no mission dilution).
Investors list 3 (e.g. no governance blind spots).
Put it in writing — revisit every 6 months.

4. Hold Pulse Checks
15-minute sync mid-quarter.
No slides. One question:
“Are we still aligned on rhythm?”
Prevents big misalignment later.

5. Co-Author the Narrative
After each board, founder writes vision, investor writes evidence.
One internal memo — one message.
Story + numbers = trust.

But rhythm is a choice.
You can always choose to tune before the music stops.

- Gavin

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#asialeadership #executivesearchforfounders

This chart puts a visual to the quiet anxiety a lot of us are feeling right now.

For decades, the formula was simple: Corporate growth equals hiring. 

When the S&P 500 went up, job openings followed. They synchronized.

We are witnessing the "Great Decoupling." in real time. 

The S&P 500 is roaring to new heights, driven by efficiency and AI optimism, while total job openings are freefalling back to pre-pandemic levels.

What does this mean for us as professionals?

It means the future isn’t just unequal; it’s sharply "K-Shaped." he "K" represents a split in how we work and how our value is measured.

🔹 The upward arm of the 'K': Professionals and companies using AI to decouple their output from their headcount. They are achieving exponential efficiency. Growth is no longer labor-dependent; it's capital and compute-dependent.
🔹 The downward arm of the 'K': Roles defined by repetitive cognitive tasks, or professionals waiting for the "hype to blow over." The chart shows the market no longer values this labor at the same rate.

The debate isn't "Will AI create more jobs than it destroys in 20 years?" The reality is today. Today, companies are realizing they can grow massive value without massive hiring.

If you are reading this as a knowledge worker, this may be a wake-up call. The middle ground is vanishing.

Actionable Insights for the K-Shaped Future:
🚀 Stop being a "user" and become a "leverager." 
Don't just ask ChatGPT to summarize an email. Use AI to redesign your entire workflow to be 10x faster. If your output is tethered to your hours worked, you are vulnerable.

🔍Audit your role for automation risk. 
Be honest. What percentage of your week could a sophisticated agent handle in 2 years? If it’s over 50%, pivot immediately to strategy, complex human relationship management, or high-level creative synthesis.

🤝 Become the "Human-in-the-Loop" expert. 
The upward arm of the K belongs to those who can orchestrate AI systems, audit their outputs for hallucinations, and apply high-judgment ethics to machine decisions.

The link between growth and jobs starts to break. Which side of the break are you standing on?

- Gavin

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#ArtificialIntelligence #executivesearch

When humanoid robots clean skyscrapers and load aircraft, what happens to the ‘entry-level job’?

Three headlines this week hit me harder than usual:
✈️ Amsterdam is testing robots for aircraft ground operations.
🏙️High-rise façade-cleaning robots are now commercially deployed in Asia.
⚙️Yamaha expanded its industrial robot line — longer reach, faster cycles, more flexible form factors.

Individually, these are cool engineering stories.
Together, they signal something larger:

The ‘first job’ in many industries is quietly disappearing.
Not in a dramatic Hollywood way.
But in the slow, economic way that reshapes a labour market before people realise what happened.

Because here’s the uncomfortable truth:
Technology doesn’t remove jobs — it removes the starting point of a career ladder.

And when the bottom rung disappears, the entire pathway above it must be rebuilt.

And the deeper truth emerging from these signals is this:

🤖Automation enters through the work humans avoid… but exits through the work humans thought they owned.
Cleaning buildings wasn’t a “career destination,” but it was a pathway upward.
When the pathway automates, the middle weakens next.

⚠️We’re not moving into a labour shortage—we’re moving into a skills misalignment crisis.
Japan needs robots because workers are disappearing.
ASEAN will have workers—but not enough robot-literate ones.

🔀 The divide won’t be humans vs robots—it will be humans who can work with robots vs those who can’t.
A cognitive divide.
A workflow divide.
A judgement divide.

🧩 The real competitive advantage won’t be robot hardware—it will be the ecosystem around it.
Robot OS, predictive maintenance, safety layers, orchestration software, industry-specific modules—
this is the “AWS of robotics,” and someone will own it.

In your industry, which entry-level role in your industry will automation quietly absorb first — and what new pathway replaces it?

- Gavin
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The Hidden Role of Executive Search in Scale-ups

Executive search in a scale-up isn’t about recruitment.
It’s about risk management.

When a company hits Series B or C, every new leader either protects enterprise value — or destroys it.

I’ve sat on both sides:
The founder wants someone who “gets it.”
The investor wants someone who can run it.
And somewhere between those two worlds is the person who can actually scale it.

In one Series C search, the brief wasn’t “Find me a CEO.”
It was “Find me someone the founder can trust — and the board can believe in.”

Skills were easy to check.
But the real test was chemistry, emotional maturity, and timing.
Because you’re not just hiring for execution —
you’re designing the next phase of governance.

What Smart Founders and Investors Do Differently ⚙️

1️⃣ Define the next chapter, not just the role.
Clarity on where the company is going shapes who you need — not the other way around.

2️⃣ Hire one phase ahead.
The best leaders can handle the next 18 months, not just the current quarter.

3️⃣ Run the founder–fit test early.
Don’t wait for chemistry issues post-hire — build trust during the search.

4️⃣ Split ownership clearly.
Founders lead vision, new hires lead systems — and both report truth to the board.

5️⃣ Onboard with alignment, not paperwork.
Use the first 60 days to sync culture and expectations — not just sign contracts.

The best searches don’t replace founders — they protect what made them and the company successful.
Hire for continuity.

- Gavin

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#executivesearch #scaleupleadership

If AI is part of your fund raising pitch, investors only want to know one thing:
“Does this make your business more repeatable, or more replaceable?”

I sit with a lot of early-stage founders across Asia, and there’s a pattern I’m seeing more often now.
They come in with ambitious ideas, clean slides, early success and a long list of AI features.
But when we move into the business model, very few can explain how AI might actually strengthen the engine of the company.

Not the vision.
Not the narrative.
The engine.

Last week, a founder walked me through a pitch that looked great on the surface.
But as we discussed their operations, it became clear that the AI was more decoration than discipline.
It didn’t deepen their defensibility.
It didn’t increase output consistency.
It didn’t reduce dependence on human judgment.
It was simply there, like a new coat of paint over the same old wall.

And that’s the skepticism many investors feel today.

We’re no longer asking whether AI is there.
We’re asking whether your business can survive when AI becomes a commodity — because in many categories, it already is.

A single engineer with vibe coding can now rebuild half of what used to be considered a SaaS product.
Features are less important.
Repeatability is key.

The founders who get investor trust are the one who can walk investors through a workflow and point to the exact place where AI improves speed, accuracy, or consistency — and then tie that directly to cost, margin, or scale.

When AI reduces variance, that’s repeatability.
When AI removes friction, that’s repeatability.
When AI shifts work from intuition to process, that’s repeatability.
And repeatability is what investors underwrite at early stage — because it’s the only signal that the business can grow without collapsing under its own weight.

How to make your investor deck “AI-repeatability ready”

1️⃣ Add a “Before vs After AI” slide

Show the exact process today vs. the AI-enhanced version.
Use simple numbers.
People understand contrast more than concepts.

2️⃣ Quantify one metric that moves

It can be delivery time, onboarding hours, churn, accuracy, or CAC.
One number is better than ten assumptions.
Keep it real, even if it’s early.

3️⃣ Explain why AI makes the process repeatable (solving a pain point)

Say it plainly:
“What used to depend on human judgment now depends on a system.”
Repeatability reduces risk — and investors invest to reduce risk.

4️⃣ Pressure-test the idea with a non-technical audience

If they can’t explain back how AI helps, you’re still speaking jargon.
Clear storytelling beats technical depth.

Your next investor meeting will go very differently depending on that answer.

– Gavin

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#StartupPitch #InvestorDeck #AIValue #StartupInvestment #GrowthStrategy

The Fragile Middle (0→1 vs. 1→10 vs. 10→100)

Most startups don’t die at zero.
They die in the middle.

At 0→1, everyone’s a builder.
Speed matters more than structure.
You hire missionaries, not mercenaries.
Every win feels like a miracle.

At 1→10, momentum arrives.
You start hiring specialists, building functions, tightening focus.
Meetings appear. Processes emerge.
Chaos slowly gets organized.

At 10→100, the business demands systems.
Governance, predictability, structure — everything investors love.
But that’s when something else breaks.

I’ve helped companies move from startup to scale-up, then to growth, and eventually pre-IPO.

And the most fragile stage isn’t the start —
it’s that messy, awkward scale-up → pre-IPO transition (10→100).

Because that’s when:

The company outgrows its early heroes but hasn’t yet attracted institutional leaders.
Every process feels half-built.
Everyone’s learning on the job — under investor pressure.

It’s long, scrappy, and brutally exposed.
Because for the first time, you’re building the plane while flying toward the runway.

That’s why this stage kills momentum more often than the early chaos.
The skill set that got you here — creativity, speed, hustle — now needs to evolve into discipline, clarity, and governance.
And most teams underestimate that evolution.

Here are 5 ways to navigate the messy middle 🚀
🔥 1. Build your bridge team.
Hire a few people who’ve scaled before — they’ll turn chaos into order without killing speed.

🧭 2. Write things down early.
Don’t wait to “get organized later.”
Document what works now so new hires don’t start from zero.

⚙️ 3. Balance growth and control.
Keep chasing growth, but make sure someone’s watching burn, cash, and compliance.

🧩 4. Make board talks useful.
Stop reciting updates — talk about what’s changing, what’s breaking, and what help you need.

💬 5. Communicate more than feels necessary.
The moment you think “everyone knows,” they don’t.
Keep repeating direction until it sticks.

What stage are you really leading right now: 0→1, 1→10, or 10→100? What's that one small win you can get this month. Small wins compound faster than perfect plans. 

- Gavin

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#scaleupgrowth #executivesearchforfounders

I love the positivity in this.

A young engineer getting recognised because her actions mattered more than her volume.

If AI can help leaders spot quiet, consistent, high-integrity contributors… that’s a future I’m excited about. 😊

No.1 Tech Voice to Follow & Influencer on LinkedIn|Award Winning Author|AI-IoT-Blockchain-Cybersecurity|Speaker|61k+

Google co-founder Sergey Brin ran an unusual experiment inside an internal company chat by asking #Gemini which participant deserved a promotion.
Instead of selecting senior or outspoken employees, the AI highlighted a young woman engineer who was rarely vocal but consistently contributed.
After reviewing Gemini’s suggestion, leadership approved her promotion.
The incident underscores how AI systems may surface overlooked talent that traditional performance reviews often miss.

We have 2 years before everything changes.

Not 10.
Not 5.
But 2.

I watched Steven Bartlett's new hashtag
#doac episode today, and it hit me harder than I expected.

Because the truth is — many people think AI is a “future nice problem" to have, which we would enjoy the increased productivity, accessibility to better and cheaper services and goods. 

And here’s the part people don’t want to hear:
What's the "trade" when we are opt in to this future?

Love the the balanced, real perspectives on our near future discussed in this episode. 

If you watch one thing this week, watch this:
https://lnkd.in/gfRwuiDA

This will shift how you think about the next two years — and why the real disruption is happening sooner than we think.

- Gavin

https://lnkd.in/gWDXuzqj

Open video: AI Expert: We Have 2 Years Before Everything Changes! We Need To Start Protesting! - Tristan Harris on youtu.be

AI Expert: We Have 2 Years Before Everything Changes! We Need To Start Protesting! - Tristan Harris

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