CEO & Founder, Top 100 Women of the Future | AI, Web3, Metaverse - Advisor & Deep Tech Investor | Keynote Speaker | Masterclass | Master Human-Centric Tech Transformation

20,000+ leaders trained. 20+ years in the boardroom. One focus: helping leaders make AI decisions they won't regret.

I bridge AI, healthcare, finance & ethics for leaders navigating technology's human impact.

Most innovation conversations focus on what technology can do. The harder work is understanding what it should do — and who bears the consequences when it doesn't.

My work sits at that intersection.

𝗪𝗵𝘆 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝘁𝗿𝘂𝘀𝘁 𝗺𝗲
I've sat where you sit.
→ Board member: Generali Switzerland, Europe Assurance
→ Former boards: UniCredit, BlackRock
→ 20+ years as executive at UBS and AXA
→ Co-author: Fast Future Blurs (Wiley)

From UBS innovation to Generali strategy rooms, I've spent my career inside highly regulated systems where progress, trust, and responsibility must move together.

𝗥𝗲𝗰𝗲𝗻𝘁 𝘄𝗼𝗿𝗸
→ Davos Innovation Week— Moderated for 4 consecutive years (Fintech, Emerging Tech, AI)
→ Forbes Switzerland Award Jury member and Moderator 2025
→ FIBE Berlin 24/25  — Exclusive Behind the scene Influencer, Europe's leading fintech festival
→ Aeon Life collaboration — preventive healthcare, full-body MRI, AI- enabled early detection 
→ Co-Author Foresight Paper Future Beyond Our times (The World in 2125
→ Co-Author White papers EU AI Act 2024 (Germany), 2025 (Switzerland. 
→ Co-founder, Fast Future Executive Faculty — speed-biased learning for C-level leaders
→ Host, Edge of Tomorrow — conversations with technologists, ethicists, and humanists

𝗥𝗲𝗰𝗼𝗴𝗻𝗶𝘁𝗶𝗼𝗻

Peace Ambassador nominee — United Nations Peace Foundation (2024–2025)
Senator for Switzerland — World Business Angels Investment Forum
Board Member of the World Smart Cities Economic Development Commission
Top 5 Women in Tech in Europe
Top 100 Women in Business in Switzerland — twice
World's Top 200 Business & Technology Innovators
LinkedIn Top Voice 24/25 | 143,000+ followers

𝗠𝘆 𝗳𝗼𝗰𝘂𝘀

Not hype. Clarity.

→ Ethical ROI in medtech and fintech
→ Human dignity in AI and scientific breakthroughs
→ Access and equity in healthcare innovation
→ Progress measured by impact, not just scale

𝗠𝘆 𝗯𝗲𝗹𝗶𝗲𝗳
Technology alone won't save us. We will — if we lead wisely.

𝗪𝗼𝗿𝗸 𝘄𝗶𝘁𝗵 𝗺𝗲

🎤 𝗞𝗲𝘆𝗻𝗼𝘁𝗲𝘀 — I speak globally at conferences and universities. DM "KEYNOTE" for speaking enquiries. 

🏛️ 𝗕𝗼𝗮𝗿𝗱 𝗿𝗼𝗹𝗲𝘀 — Open to selective non-executive positions where responsible technology and strong governance are central.

Dr. Martha Boeckenfeld

Glasses for blind babies. "Science doesn't wait for miracles. It creates them."

These babies usually have severe low vision — high refractive error, astigmatism, sometimes albinism. Without correction, everything is fog. 

Faces are shapes. Eyes are blurs.

Then tiny glasses go on.

And suddenly, he sees her mother's face.

Think about that.

The first years of life are when the visual cortex learns to interpret what the eyes send. If the image stays blurry, the brain stops trying. It down-regulates. Vision that could have developed becomes permanently impaired.

Doctors call it amblyopia. Parents call it heartbreak.

Pediatric ophthalmologists don't wait for babies to read eye charts. They use retinoscopy — shining light into the eye and watching how it reflects. No verbal feedback needed. Just physics and training.

The prescription gets calculated. Tiny frames get fitted. And a brain that was about to give up starts learning to see.

Studies show early spectacle intervention improves visual attention and long-term function compared to waiting. Parents report babies tracking faces, reaching for toys, crawling with confidence.

The technology is plastic lenses in a flexible frame.

The innovation is timing.

What looks like a miracle is actually months of screening, measurement, and precise fitting — compressed into one emotional second when the glasses go on.

That's creates more than a second when a whole new life get's created and you can see. 

The Multiplication Effect:

1 baby = a brain that learns to see
10 clinics with trained staff = early detection at scale
100 countries with screening programs = millions of children who never know what they almost lost

We know how to do this.

We just need to make sure that every child who needs early correction actually gets it.

The smile of these babies is just priceless! 

♻️ Repost to other to learn about this option. 

Video: Sassy Media
Source: BMJ Open (2022), PMC studies on infant visual development, pediatric ophthalmology guidelines.

Human-Centric AI & Future Tech | Keynote Speaker & Board Advisor | Healthcare + Fintech | Generali · Ex-UBS · AXA

The internet is educating your kids.

New Zealand decided parents should too.

They released a national ad about what children are being exposed to online.

It’s uncomfortable.

It’s honest.

And it’s surprisingly funny.

That’s why it worked.

Because the real danger isn’t access.

It’s silence.

We are raising a generation fluent in technology…

But not always fluent in judgment.

Kids don’t “go online” anymore.

Digital and physical are fused.

Which means if we don’t explain what they’re seeing.

An algorithm will.

A stranger will.

Or a system designed to capture attention before understanding catches up.

We often think protection means control.

But control without conversation creates secrecy.

And secrecy is where risk compounds.

I’m not a parent.

But I’m an aunt to nine nieces and nephews.

And watching them grow up in this world has made one thing clear:
↳ Start earlier than feels comfortable
 ↳ Ask more than you lecture
 ↳ Use humor before fear
 ↳ Model the behavior you expect

Because kids don’t copy advice.

They copy patterns.

Technology will keep evolving.

AI-enabled manipulation. Deepfakes. Algorithmic influence.

The tools are accelerating.

So we have to get more intentional.

That’s why I respect that Elcin Biren is tackling this directly.


She’s hosting a session with SwissCyberSmart and INTERPOL on building real cyber resilience at home.

Not panic.

Not screen-time policing.

But practical, proactive conversations.

If you’re raising — or influencing — the next generation, this is worth understanding.

📅 March 10 | 13:00 CET
 🔗 Registration link in comments

Safety starts with connection.

Not control.

Millions of people with chronic back pain are stuck in the same cycle.

Physical therapy stops working. Injections wear off. Opioids become a daily habit. And the only surgical option left is fusion — locking two vertebrae together, losing motion forever.

For years, there was nothing in between.

Dr. Tony Lowman spent twenty years trying to change that.

He's a biomedical engineer who kept asking one question: What if we could repair the disc instead of removing it?

Think about that.

The disc isn't broken. It's deflated. The soft, shock-absorbing center has dried out and cracked. So his team built something to restore it.

HYDRAFIL is an injectable hydrogel. It goes in through a needle, fills the fissures, recruits water, and solidifies inside the disc.

No incision. No hospital stay. Patients walk out the same day.

In preclinical studies:
↳ 10% improvement in disc height within two weeks
↳ Inflammatory markers dropped to near-healthy levels
↳ Material held up under repeated spinal loading

It's now in U.S. clinical trials.

The shift this represents:

Traditional approach: Manage pain until fusion is unavoidable.
This approach: Rebuild the disc before it collapses completely.

Fusion works. But it trades motion for stability. Every fused segment puts more stress on the ones above and below.

Hydrogel repair preserves what's there.

The Multiplication Effect:

1 patient who avoids fusion = years of mobility preserved
10 clinics offering outpatient disc repair = fewer people cycling through opioids
100 trials proving long-term durability = a new standard of care
At scale = back pain treated as a structural problem, not just a pain management problem

This is still early. Human data is limited. Long-term outcomes are unknown.

But the principle matters now.

Back pain would stop being treated only as a pain problem.

And start being treated as a structural one.
It is still early.

Human data is still limited and long-term outcomes remain unknown.

But the idea points to something bigger.

For decades, medicine has focused on replacing damaged parts.

What if the next wave focuses on repairing them instead?

Do you think medicine will shift from replacement to regeneration in the next decade?

Source: Data adapted from Zheng et al., Biomaterials Advances 2022 and Dittmann et al., Pain Physician 2024, plus the ongoing HYDRAFIL‑D pivotal trial (NCT06011551).

We spent a century building trillion-dollar systems to move water.

Omar Yaghi built a box that makes it.

Yaghi won the 2025 Nobel Prize for Metal-Organic Frameworks (MOFs): synthetic crystals that act like tiny sponges. AI helped to figure out the shape. A few grams can have the inner surface area of a football stadium.

Think about that.

More than 2 billion people still don’t have safe drinking water.

His company Atoco wrapped MOFs into a water-from-air machine:
Air flows in.

MOFs grab water molecules.
Sun heats the material.
Water vapor comes off, then condenses into drinkable water.

No grid power. No pipes. No desalination. It works at ~20% humidity.

Why it matters:
 ↳ Fully off-grid, powered by solar heat 
↳ Container-sized 
↳ Deployable to disaster zones, desert villages, islands 

Yaghi tested the prototype in the Mojave Desert. It worked.


Scale looks like this:
1 unit: ~1,000 liters/day for a village
10 units: a hospital through a drought
100 units: steady water for a whole region
Places that never had pipes may not need them.

For decades we chased bigger, centralized systems. This heads the other way: small units you can add, move, and run anywhere.

♻️Share this with someone building in the real world.

Follow me for ideas on living through the AI era—and why human leadership still decides what happens next.

Sources: Economic Times (23 Feb): "Nobel Prize winner built a machine that extracts 1,000 liters of water from air" – Scalability, global relevance.
Atoco Website: atoco.com – Company site detailing MOF tech, 1,000L/day off-grid units, and mission.
AgTech Navigator (20 Jan): "Atoco targets commercial rollout" – Death Valley tests, 1,000-4,000L variants.
Image: @engineeringfacts

Two high schoolers just cut car emissions by 74%.

For $30.

Jack Reichert and Rohan Kapoor are seniors at Unionville High School in Pennsylvania. They built the Go Green Filter — a 3D-printed attachment that clips onto any tailpipe.

Inside: a small chamber filled with microalgae suspended in water.

As exhaust passes through, the algae do what they've done for billions of years. Absorb CO₂. Release oxygen. Photosynthesis, running on fumes.

Think about that.

The stats:
↳ 74% reduction in carbon dioxide emissions in controlled tests
↳ Prototype cost: $30–50 per unit
↳ 500 filters already deployed in Indonesia
↳ Works on cars, motorcycles, any combustion vehicle

No engine swap. No electric conversion. No infrastructure overhaul.

Just algae doing what algae do.

What stopped me:

The filter won the 2023 T-Mobile Changemaker Challenge. Their school district measured 74.25% CO₂ reduction. They've already deployed 500 units in Indonesia.

Not a prototype sitting in a lab. Real filters. On real roads. Right now.

Two teenagers. A 3D printer. A biology textbook.

The Multiplication Effect:

1 filter = 74% less CO₂ from one vehicle
1,000 filters = a fleet breathing cleaner
1 million filters = measurable dent in urban air quality
At scale = a bridge while the world waits for electric

For decades, cutting emissions meant expensive retrofits or waiting for the full transition.

These two didn't wait.

Have you seen student-led innovations making real-world impact? Drop a comment below.

Follow me, Dr. Martha Boeckenfeld for more innovators solving problems the world said were too big. 

♻️ Share with someone who believes the next generation isn't waiting for permission.

Source: Go Green Filter, T-Mobile Changemaker Challenge 2023.

Age is just a number. He proved it at 47.

Dr. Carl Allamby spent 25 years as a master mechanic in Cleveland. Built an automotive business from the ground up. Diagnosed problems by sound, by feel, by instinct.

Then a required biology course changed everything.

He needed it to finish a business degree. His professor noticed something: this mechanic thought like a scientist.

Think about that.

The same pattern recognition that diagnosed a failing transmission could diagnose a failing heart. The same systematic troubleshooting. The same pressure to get it right the first time.

His wife said yes. His family backed him. He sold the business and enrolled in medical school.

At 51, he became a doctor.

Today, at 53, he works as an emergency medicine physician at Cleveland Clinic.

What stopped me cold:

He didn't start over. He carried forward.

The garage taught him to read subtle symptoms in complex systems. To make critical decisions under time pressure. To trust his hands when the diagnosis wasn't obvious.

The ER demands the same skills.

The Multiplication Effect:

1 mechanic who becomes a doctor = proof that expertise transfers
10 career changers who see his story = permission to try
100 people who stop waiting for "the right time" = lives redirected
At scale = we stop treating experience as something to leave behind

We've been taught that changing careers means starting from zero.

Allamby's story says something different: You can live your dream with training.

The skills you built solving one kind of problem can solve another. The question isn't whether you're too old. It's whether you're willing.

What path would you take if you stopped waiting for the "right time"?

Follow me, Dr. Martha Boeckenfeld for stories of people who rewrote their path.

♻️ Share with someone who needs to hear that it's not too late.

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Plants have been making fuel from sunlight for 500 million years.

China just figured out how to copy them.

A team at the Chinese Academy of Sciences built a system that takes CO₂ and water, hits it with sunlight, and produces the building blocks of synthetic gasoline.

No oil wells. No drilling. No fossil carbon.

Think about that.

The secret was a "charge reservoir" — a material made from tungsten trioxide and tiny amounts of silver that traps solar energy like a battery and releases it precisely when needed.

Previous systems failed because electrical charges disappeared instantly. This one stores them.

The result: carbon monoxide — the industrial starting point for synthetic gasoline and jet fuel — at roughly 100 times the efficiency of previous catalysts.

Water is the only ingredient consumed. Zero sacrificial chemicals.

What stopped me:

It works with existing engines. Existing pipelines. Existing infrastructure.

No reinvention needed.

The Multiplication Effect:

1 system proving the concept = validation that photosynthesis can be copied
10 systems producing fuel = regional energy without drilling
100 systems deployed = countries producing synthetic fuel from sunlight
At scale = energy independence from fossil carbon

For a century, we've drilled into the Earth for energy.

This system pulls it directly from the sky.

We've spent decades asking how to extract more efficiently.

Maybe the better question was always: how do we copy what already works?

♻️ Follow me, Dr. Martha Boeckenfeld for innovations that reshape how we power the future.

Share if you believe the next energy revolution will come from biology, not geology.

📚 Source: Chinese Academy of Sciences | Yu Huang et al. | Nature Communications, March 2026 | ECOticias — Adrian Villellas

Human-Centric AI & Future Tech | Keynote Speaker & Board Advisor | Healthcare + Fintech | Generali Ch Board Member · Ex-UBS · AXA

She ran out of options at 12. Then her own cells came back to save her.

A girl in Ho Chi Minh City with high-risk B-cell acute lymphoblastic leukemia. Chemotherapy failed. Then her father gave half his bone marrow. That failed too.

Her doctors faced a choice: accept the prognosis or try something Vietnam had never done.

They chose to try.

Her T cells were collected in Vietnam. Shipped to Taiwan. Genetically modified to recognize and attack leukemia cells. Sent back. Reinfused.

Think about that.

Her own immune cells, engineered to find the cancer that had beaten everything else, then returned to finish the fight.

CAR-T therapy turns the body into its own treatment. The cells learn to identify markers on leukemia cells — like CD19 — and destroy them. Researchers call it a "living drug" because it keeps working after infusion.

More than a year later, she's cancer-free. Back to daily life. No detectable disease.

Vietnam's first successful pediatric CAR-T case.

But here's what stopped me:

The treatment costs tens of billions of Vietnamese dong when done abroad. That's tens to hundreds of thousands of US dollars per patient.

Ho Chi Minh City's Blood Transfusion and Hematology Hospital is now preparing to produce CAR-T cells domestically. The goal: cut costs by up to 20-fold.

The Multiplication Effect:

1 patient = proof that "no options left" isn't always true
10 hospitals with CAR-T capability = transplant candidates instead of death sentences
100 families = access without bankruptcy
At scale = the line between "too expensive to try" and "standard of care" moves

The technology is genetic engineering.

The innovation is making it reachable.

One girl's immune cells crossed borders, got reprogrammed, and came home to save her life. Now the question is whether the next child will have to wait for that same chance — or whether it will already be there.

Follow me, Dr. Martha Boeckenfeld for breakthroughs that prove "no options left" isn't the end of the story.

I'm curious — is CAR-T therapy available where you are? What's standing between patients and treatments like this in your country?

Source: VietnamPlus, Vietnam.vn, Blood Transfusion and Hematology Hospital HCMC (2025).

Everyone is teaching kids how to use AI.

But one mother realised something, which no one is teaching you. 

The real upgrade wasn’t the tool.

It was her son’s brain.

Her 10-year-old had already started using AI for homework.

Every evening looked the same.

He experimented with prompts.

She answered emails.

Both went to bed wired.

Neither felt wiser.

So they tried something small.

Before opening any screens, they spent 90 seconds doing cross-crawls and rhythm claps together.

Left elbow to right knee.
Right elbow to left knee.

Simple movements that force both sides of the brain to work together.

Two weeks later something changed.

He settled into homework faster.

Fewer careless mistakes.

And instead of copy-pasting answers from AI, he started asking better questions.

That shift matters.

Because AI can generate answers instantly.

But it cannot decide what matters.

It cannot connect ideas across contexts.

And it cannot replace a brain trained to think.

Neuroscience calls this neuroplasticity.
Your brain constantly rewires based on what you repeat.
Attention. Memory. Cognitive flexibility.

These are not fixed traits.
They are trainable systems.

Cross-body movement strengthens the networks responsible for focus, filtering distractions, and organising information.

Exactly the skills you need when working with AI.

Human brains and AI systems actually learn in a similar way.

Both strengthen what works.
Both prune what doesn’t.

The difference is this:

Humans can choose what to train.

So the real question isn’t whether children will grow up with AI.

They will.

The real question is whether we train their brains to think while using it.

Because the future won’t belong to the people with the best tools.

It will belong to the people with the best trained minds.

What we repeat, we wire.

In code.

And in cortex.

♻️Share for others to learn, how your kid will learn better when using AI. 

Video: @mr.highlevel_

A full-time cardiologist just beat 13,000 AI builders.

He built his platform between shifts.

Hospital break room. Airport lounge. 30,000 feet over the Atlantic.

7 days. 3rd place. While working full-time saving hearts.

The code was the easy part. The insight took a decade.

Michał Nedoszytko didn't brainstorm a startup idea. He solved something he's watched for over ten years: patients leaving appointments confused.

So he built postvisit.ai.

A reverse AI scribe. Not for documentation. For understanding.

The moment you leave the doctor's office, the platform activates:
↳ Surfaces your medical record back to you
↳ Translates diagnoses into plain language
↳ Turns complex instructions into clear next steps
↳ Connects wearables and evidence-based resources in one place

The shift that made this possible:

Powered by the massive context window of Opus 4.6, it allows patients to explore their full medical history, connected devices, Evidence Based resources and external data sources — all in one place.

What inspires me: 

One domain expert can now ship what used to require a department.

That's the real change.

Building is easier than ever. Deep insight isn't.

The advantage now belongs to people closest to real problems.

Doctors.
Operators.
Engineers inside complex systems.
People who've seen the same friction repeat for years.

The Multiplication Effect:

1 expert building = proof that insight beats code
10 operators shipping = industries transformed from within
100 who lived the problem = solutions that actually last

If you're building something, start here:

What problem do you understand better than almost anyone else?

That's your edge. 

♻️ Repost if you believe domain expertise is a founder's unfair advantage.

Follow me, Dr. Martha Boeckenfeld for stories of builders turning experience into impact.

He couldn't walk. Then his knee started thinking.

Now he steps out of cars without help.

Kai lives with a neurological condition that left him unable to walk independently. Every attempt demanded high energy, led to rapid fatigue, and forced compensations that strain joints over time.

Traditional leg braces lock you in place. Powered exoskeletons cost $40,000-$100,000 and weigh 14kg or more.

Agilik weighs 550 grams.

Think about that.

A powered knee actuator lighter than a water bottle. Mounted on a custom brace. Reading every step in real time.

What makes it work:
↳ Sensors measure knee angle, velocity, initial contact, toe-off
↳ Software adjusts assistance or resistance each gait phase
↳ Tuned specifically for each patient
↳ Provides power when needed, resistance when muscles need to work

Help when you're struggling. Challenge when you're ready.

Getting out of the car, Kai can now bring his trunk forward, push up, and feel the powered knee help him reach upright — instead of collapsing into a crouch.

Walking into a shop, sensors track his knee angle step by step, adjusting support so he spends less energy on every meter.

Over weeks and months, clinicians gradually reduce the assistance as his strength improves. The goal: prevent dependency while preserving the gains.

Kai is an adult. But this same principle matters even more for children.

For kids with CP and spina bifida, strength and endurance often deteriorate as they grow. The more they avoid walking, the weaker they get. The weaker they get, the less they walk.

Agilik breaks that cycle.

The Multiplication Effect:

1 child = steps that seemed impossible
10 families = errands together again
100 clinics = gait training that travels home
At scale = mobility that builds strength instead of replacing it

The technology is sensors and motors.

The innovation is a knee that learns your walk — and teaches you to walk better.

What would it mean for someone you know to step out of a car on their own again?

♻️ Share if you believe mobility should build independence, not dependence.

Source Video: x.carstens@insta

500 million neurons. Each arm thinks independently. They solve puzzles, escape aquariums, and form bonds with humans.

Meet the octopus. The closest thing to an intelligent alien on Earth.

Think about that.

Two-thirds of their neurons aren't in their brain. They're in their arms. Each arm can taste, touch, and make decisions without waiting for permission from headquarters.

They unscrew jars from the inside. Carry coconut shells across the seafloor to build shelters later. Recognize individual humans and squirt water at the ones they don't like.

Scientists call it "unlimited associative learning." The same cognitive milestone that marks consciousness in vertebrates. Evolved completely independently, 600 million years apart from us.

The crisis:
↳ Global octopus catches doubled from 1980-2014
↳ Many fisheries now overfished with no recovery
↳ Proposed octopus farms cause stress and cannibalism
↳ Plastics trap them—they mistake cups for shelters
↳ Warming oceans cut juvenile survival by 30%

We're losing ocean geniuses before we understand them.

The protection wins happening now:
↳ Washington and California pushing farm bans
↳ Bottom trawling banned in protected areas
↳ Octopuses recognized as sentient in EU law
↳ Research programs studying wild populations

The Multiplication Effect:

1 octopus protected = a mind preserved
10 marine reserves = ecosystems stabilized
100 countries banning octopus farming = sentient beings no longer factory-farmed
At scale = we stop treating intelligence as something only humans possess

The technology to protect them exists. The science proving their consciousness exists. The only thing missing is the decision to act.

Every creature that thinks, feels, and solves problems deserves protection. Not because they're like us. Because they're brilliant in ways we're only beginning to understand.

Follow me, Dr. Martha Boeckenfeld for innovations that protect the brilliant minds we're only beginning to understand.

♻️ Share if you believe intelligence deserves protection—regardless of the body it inhabits.

Thanks to Tim Gray who collaborated with me to show the beauty of the oceans and marine life we need to protect (by Breakout Clips).

#OceanConservation #MarineLife #Innovation

Director at Lightbox Studio - Director at Breakout Clips

Breakout Clips

AI fluency demand grew 7x in two years.

Creative thinking is still the #2 skill employers want.

Watch Leng Jun paint a portrait so detailed, people mistake it for a photograph.

Every brushstroke guided by decades of practice. Vision, intuition, and muscle memory working together in ways no algorithm can replicate.

Think about that.

The World Economic Forum's 2025 Future of Jobs report puts analytical thinking first. But creativity dominates the rest — curiosity, design thinking, empathy, flexibility.

McKinsey confirms it: 70% of the skills employers seek are still deeply human.

But most of us were trained to optimise, not originate.

Follow templates. Find the right answer. Stay inside the lines.

AI already does that better than we ever will.

What it can't do is turn a blank canvas into something that stops you mid-scroll. Transform years of practice into a single decisive stroke.

That's divergent thinking — creating from experience, not data.

I was live yesterday with Tom Donaldson, Senior Vice President and Head of Creative Play Lab at the Lego Group on The Edge of Tomorrow.

Tom's angle: How leadership needs to steer creativity without killing it.

We' talked about:

• How to build platforms for ideas to emerge instead of chasing random ideas
• How to design failure into the process so experimentation is safe
• How to scale imagination without turning it into bureaucracy

Companies like LEGO don't stay relevant by accident.

There's structure behind the creativity. The success is driven by culture and people. What drives the major breakthroughs is not the technology, but the experience that it changes. 

"Creating the magic" needs "childlike" leadership. (Tom Donaldson) 

If you're building a team right now, this is the real conversation.

Engage in the conversation and let me know, if you agree that curiosity is your "superpower" in the age of Intelligence. 

View here: https://lnkd.in/e6KeSXNA

Video: Leng Jun @insta

The AI said low risk. 92% accuracy.

She almost signed off.

A senior ICU doctor reviewing a sepsis case. The system flagged the patient for deprioritization — free up the bed, move on.

She paused.

One question stopped her: "Am I over-trusting this because it matches my fatigue-driven optimism?"

She checked the AI's confidence breakdown. Found it had underweighted recent lactate trends due to a data quirk. Ran manual diagnostics. Caught early organ distress the algorithm missed.

That pause saved a life.

Think about that.

92% historical accuracy. And it still almost got it wrong.

I saw the same pattern in a boardroom.

A fintech CEO planning a Middle East market entry. The AI's risk assessment looked solid. Green lights across the board.

Something felt off. But he couldn't see it while he was inside the decision.

He took an afternoon off with his family. Came back with distance. Spotted the flaw the model had missed — overestimated risk tolerance for that market.

Two different worlds. Same skill made the difference.

It's called metacognition.

The ability to notice what your mind is doing — and adjust in real time.

Catching yourself procrastinating because something feels overwhelming.

Pausing before sending a reactive message.

Realizing you've been stuck using the wrong approach.

Brain research shows this skill strengthens both analytical and creative thinking. It's why some people stay steady under pressure while others spiral.

And the key point: it's trainable.

Same intelligence. Very different outcomes.

The difference is noticing the spiral and redirecting early.

AI gives confidence.

Metacognition gives clarity.

The Multiplication Effect:

1 doctor who pauses = 1 patient saved
1 CEO who steps back = a market misstep avoided
10 leaders trained in reflection = better human-AI decisions across industries
At scale = AI becomes a tool, not a crutch

The doctor paused. The CEO stepped away.

Both caught what the algorithm missed.

♻️ Follow me and share if you want other to learn, how make better decisions with AI. 

Reel: @goodneuroscience
Sources: Individuals with High Metacognitive Ability Are Better at Divergent and Convergent Thinking DOl:10.3390/jintelligence11080162
Purucker, L., Hammer, M., & Boehm, F. (2024). Metacognitive AI: Framework and the case for a neurosymbolic approach. arXiv. arXiv:2406.12147

The AI said low risk. 92% accuracy.

The future of mobility has four legs.

Toyota just unveiled Walk Me. A robotic chair that walks instead of rolls.

Each leg bends, lifts, and adjusts on its own. Inspired by how goats balance on slopes and crabs move across rocks.

Around 80 million people worldwide use a wheelchair.

Most of those wheelchairs need flat floors. Ramps. Lifts.

But most of the world isn't flat.

Stairs in old buildings. Gravel paths. Thresholds between rooms.

Walk Me handles all of it.

What makes it work:

LiDAR scans for obstacles.
Sensors check balance before each step.
AI adjusts movement in milliseconds.
Legs fold flat to fit in a car trunk.

But here's what stopped me:

The chair rises on "tiptoes" and tilts forward so the user can step into a car. No transfer board. No caregiver lifting.

A grandmother visiting her daughter's second-floor apartment.

A father getting into his own car for the first time in years.

That's not a feature. That's dignity.

The Multiplication Effect:

1 chair = stairs become passable
10 homes = caregivers rest
100 cities = accessibility without rebuilding
At scale = mobility that meets the world as it is

This is biomimicry at its best. Taking lessons from nature to create mobility that adapts to the world as it is.

We spent decades redesigning buildings for wheelchairs. What if we redesigned the wheelchair for buildings?

Who in your life would this change everything for? 

Video: Toyota Presented at the Japan Mobility Show 2025.

Surgical robots cost $2 million.

Beijing just built one for $200,000.

Watch it peel a quail egg: Shell removed. Inner membrane intact. Submillimeter accuracy that matches da Vinci at 90% less cost.

I posted about this four months ago. 

But that was only half the story.

At Davos, I talked with Ravin Jesuthasan, CFA, FRSA — global futurist, bestselling author on AI and the future of work.

I asked what most people miss about robotics.

His answer reframed how I see it.

"It's not about the robot. It's about redesigning the work."

Think about that.

We celebrate the $200,000 price tag. The precision. 

But a cheaper robot sitting in the same broken system changes nothing.

Ravin explained it simply: What is the work that needs to happen to produce value for the patient? That requires redesigning how humans and machines combine.

The surgeon doesn't disappear. The role transforms.

↳ Robot handles precision cuts
↳ Human handles judgment calls
↳ AI monitors vitals in real-time
↳ Nurse coordinates the handoffs

Every task reassigned to whoever — or whatever — does it best.

Companies racing to buy robots are asking the wrong question.

The right question: How do we redesign work so the robot actually multiplies what humans can do?

The Multiplication Effect:

1 hospital that redesigns workflows = 10x more surgeries with the same staff
10 hospitals sharing protocols = regional healthcare transformed
100 systems rethinking human-machine teaming = surgical access at scale

The robot was never the breakthrough.

The breakthrough is figuring out who does what — and building the system around that answer.

Ravin put it best: "Companies and individuals who figure that out in their unique circumstances will get to the optimal levels of machine-human teaming."

The $200,000 robot is available now.

The harder work is redesigning everything around it.

Where have you seen a new tool fail because the work around it stayed the same?

♻️ Share if you believe the future of work isn't about replacing humans — it's about redesigning how we work together.

Global thought leader, futurist and bestselling author on the future of work, AI and human capital. Executive Fellow and Adjunct Lecturer of Executive Education at the Kellogg Business School

A community health worker in East Africa just changed how I think about AI governance.

She doesn't have a medical degree. She has a smartphone and an open-source AI called Meditron, built at EPFL in Lausanne.

During a household visit, she photographs a medication package. The AI translates the instructions into the local language. Right there. At the point of need.

Professor Annie Hartley, who works on the project, put it simply: the alternative for many patients isn't a doctor. It's nothing.

That same Meditron will be tested in CHUV Lausanne's emergency room starting May 2026. Over 300 Swiss health professionals already evaluated it — with equal parts enthusiasm and scepticism.

Think about that.

The same AI helping a community health worker in a rural household must meet the same standards as a Swiss university hospital.

That's not a compliance exercise. That's a design choice.

Antoine Bosselut, who led Meditron's development at EPFL, said it clearly: "Access to medical knowledge should be a universal right."

That principe shaped my thinking when I co-authored a country profile on Switzerland and the EU AI Act with AI & Partners.

My argument: true progress isn't just regulatory alignment. It's embedding human-centric principles at the core of governance.

The health worker doesn't care about frameworks. She cares whether the AI helps her patient understand their medication.

That's the standard.

Follow me, Dr. Martha Boeckenfeld for Insights on thriving when AI rises, but Leaders stay Human.

♻️ Share if you think the best AI governance starts with the patient, not the paperwork.

Governance for People, Not Paperwork

Helping you make sense of going Cashless | Best-selling author of "Cashless" and "Innovation Lab Excellence" | Consultant | Speaker | Top media source on China's CBDC, the digital yuan | China AI and tech

As a best-selling author and consultant, I combine my passion for fintech, AI, and innovation with my extensive experience in the banking industry and the Asian market. I wrote two No. 1 international bestsellers, "Cashless: China's Digital Currency Revolution" and "Innovation Lab Excellence," that provide insights, strategies, and practical solutions for the digital transformation of the financial sector. I have also been a top media source and speaker on China's digital yuan and mobile payments, sharing my firsthand knowledge and analysis of the world's most advanced cashless society.

With over 25 years of experience in risk management, structured credit, and debt financing, I deeply understand fintech and AI's challenges and opportunities for the banking industry. I have worked with start-ups and established insurance and asset management players, helping them navigate the uncharted waters of the latest cognitive, AI, blockchain, and analytic technologies. I have also led and contributed to multiple innovation labs and projects across Asia, applying the latest IBM technologies to real-world problems our banking clients face. I am a tireless evangelist for using technology to democratize access to financial markets and to enhance customer experience and value.

Richard Turrin

Stablecoins’ $33T transaction volume grabs headlines, but the true battle isn’t volume — it’s who controls institutional flows, which is why banking licenses have become the new battleground in the stablecoin economy.

The new bank rush includes stablecoin issuers, asset managers, and even a Japanese multinational, all of whom are striving to crack the stablecoin economy by providing institutional access through a bank.

Despite the massive volume hype, stablecoins still lack a clear path to broad institutional adoption. 

Becoming a chartered bank offers a practical solution — normalizing their use by providing the oversight, trust, and infrastructure corporations expect. 

Consider how unlikely it is for large companies to run payroll, supplier payments, or treasury operations on tokens issued by lightly regulated entities and third-party exchanges.  

Becoming a regulated bank changes that equation.

👉Key trends:

↳ In the US, at least 15 applications have been submitted for banking charters overseen by the Office of the Comptroller of the Currency (OCC), 

↳ 11 of the 15 are from stablecoin issuers. 

↳ Payment companies like Stripe, Bridge, Ripple, and Connectia Trust NA, backed by Sony Financial Group.  

↳ Crypto native firms like Coinbase Global Inc. and National Digital Trust are both seeking banks.  

↳ Full-service bank Erebor and even the new US neobank, Brazil’s NuBank

↳ Master account access to Fedwire, ACH, and FedNow would transform issuance, redemption, and on-chain settlement

For incumbent banks, which are, for the most part, lagging with stablecoin adoption, the shift presents both a threat and an opportunity: 

↳ Threat: regulated stablecoin issuers could disintermediate thin-margin wholesale and cross-border payments

↳ Opportunity: partner or replicate to embed stablecoins in cash management, custody, and treasury services 

What is key is that the prize is not retail wallets but control over institutional payment flows.

The race is on. Who will win control of the massive flows associated with asset managers, broker-dealers, and market makers? 

♻️Repost to share this great read on the stablecoin bank rush!
#Fintech, #AI, and Tech at the speed of Asia and China.

The Race Is On to Build a Stablecoin Bank and Cash-in!

Fintech and AI from a uniquely Asian and China-centric perspective | Best-selling author of “Cashless” and “Innovation Lab Excellence” | Consultant | Speaker | Top media source on China’s digital yuan |

Weekend Read:  Tokenized Money Explained: What You Need to Know in 2026 – Deposit tokens, CBDC, Stablecoins & More

This is a fabulous Weekend Read for fans of tokenized money and tokenization! 

While all of the document is a solid read, here are the chapters you simply can't miss:

🔹 Chapter 1  The Taxonomy
Learn how the different forms of digital money are classified based on: 

• the nature of the claim;
• the backing;
• the form in which it is represented on a ledger;
• and the access conditions guiding who can hold
and transfer it.

🔹Chapter 3  Interoperability and Programmability
Read this to learn why these are so important to EVERY form of digital money, and the 5 key challenges to scalability: 

• Cross-border efficiency
• Cross-platform connectivity
• Cross-asset connectivity
• Regulatory alignment
• Governance coordination

Read this, and you will be ready for the big changes coming to how we pay in 2026! 


♻️Repost to share this fabulous read on Tokenized Money! 
#Fintech, #AI, and Tech at the speed of Asia and China.

Tokenized Money: What you need to know! 

Harvard Business Review drops a bombshell by claiming that AI isn’t reducing anyone’s workload, but is actually intensifying it and increasing burnout.

The results of an eight-month study at a tech company with 200 employees may at first sound like every manager’s dream: 

“We found that employees worked at a faster pace, took on a broader scope of tasks, and extended work into more hours of the day, often without being asked to do so.”  

...and it gets better.... 

“Workers did more because AI made ‘doing more’ feel possible, accessible, and in many cases intrinsically rewarding.”

The problem for workers is burnout:

“Once the excitement of experimenting fades, workers can find that their workload has quietly grown and feel stretched from juggling everything that’s suddenly on their plate."

"That workload creep can in turn lead to cognitive fatigue, burnout, and weakened decision-making.”

The study found that companies will need to adopt an AI practice:

"a set of intentional norms and routines that structure how AI is used, when it is appropriate to stop, and how work should and should not expand in response to newfound capability."

Three creators of AI intensity:

↳ Task Expansion

AI automates routine work, but instead of reducing workload it expands the scope — leaving people to handle more complex, judgment-heavy tasks and exceptions at scale.

↳ Blurred Boundaries

AI enables constant availability and real-time monitoring, blurring the line between work and personal time — making it harder to disconnect and increasing burnout risk.

↳ Multitasking

AI speeds up task-switching and creates more simultaneous workflows, raising cognitive load — leading to fragmented attention, reduced deep focus, and higher error rates.


This isn’t to say that humans and AI won’t reach the critical balance allowing humans to work comfortably with AI.  

They most certainly will, but it will only come if companies have policies that help foster this balance.  

Companies need to be proactive in adopting an AI practice for employee well-being, just as they do with adopting AI  risk management and governance programs.

Expecting this balance to happen magically by itself is a fundamental error. 

Or will companies just accept employee burnout and make humans sacrificial?

♻️Repost to share how AI increases work intensity
#Fintech, #AI, and Tech at the speed of Asia and China.

Bombshell:  AI doesn't reduce work but fosters burnout

Harvard Business Review’s survey of 623 senior execs reveals the surreal state of hype for agentic AI, as a stunning 84% believe Agentic AI will transform their organization’s business.  

Yet backing this belief is the harsh reality that:

↳ Only 26% say that their organization is very effective at leveraging ANY type of AI 

↳ 66% say their organizations aren’t even using agentic AI, as they are in pilot or a lower level of activity. 

So execs are making big predictions on agentic AI’s transformative power with little success using AI and no direct experience. 

But then, as though we are entering a painting by Salvador Dali, most can’t even define what success is for their agentic systems: 

↳ Only 5% of respondents say that their organization has well-defined success metrics for agentic AI implementation

↳ 19% say their organization has some success metrics in place. 

↳ 55% say their organization is defining or planning such metrics 

↳ 17% say their organization has not considered success metrics 

So, exactly what is a successful agentic AI when most have no clue as to the metrics to measure success?! 

But wait, as if this isn’t surreal enough: 

↳ 72% fully expect that agentic AI will deliver a return on investment, but wait for it….

↳ 46% don’t even have an agentic AI roadmap or strategy!

You can’t make this stuff up! 

That execs are positive about agentic AI isn’t bad, and one may argue that they are making predictions about its future use.  

That may be true, but execs should be a bit more skeptical. 

"Transforming a business" is a high bar, and the gap between their reality and aspiration is too great.

If this isn’t a surrealist Salvador Dali painting, what is? 

♻️Repost to share how hyped agentic AI has become!
#Fintech, #AI, and Tech at the speed of Asia and China.

Hopium: The Huge Gap Between AI Hype and Reality 

🔥Weekend Read: McKinsey's "The State of Organizations 2026," should have been titled: "The AI 'Jobpocalypse' Begins and Block Shows Why."

McKinsey's nine strategic "shifts" are a great read, and yes, all will transform organizations. 

The problem is that McKinsey makes them all sound happy, when many will be very hard on employees! 

As Block's layoff of 40% of staff shows, the real "state of organizations in 2026" will not be as employee-friendly as McKinsey suggests.

↳ Where McKinsey happily sees companies "reaching the next productivity frontier," Block's Jack Dorsey confirms that this frontier doesn't need as many humans: 

“We’re already seeing that the intelligence tools we’re creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company.”

↳ While McKinsey sees humans and AI agents working together and collaborating, this isn't what happened at Block. 

40% of staff were let go, and none were deemed worthy of agent collaboration? Nearly half the company won't be happily collaborating with agents. 

↳ McKinsey wants companies to "Aim higher with a new performance edge."

Block's CEO, Jack Dorsey, agrees and says other companies will get the same "edge" soon: 

"I think most companies are late. Within the next year, I believe the majority of companies will reach the same conclusion and make similar structural changes.” 

McKinsey's 9 shifts transforming organizations all sound happy, but read between the lines for the outlook on jobs: 

 1. Unlocking the Al-enabled organization

2. Humans and Al agents: Building a new world of collaboration

3. Leveraging Al to rewrite the future of shared services

4. Finding value in a new geopolitical context

5. From structure to flow: Reaching the next productivity frontier

6. Focusing on the core: Doing the right thing with more intensity

7. Aiming higher with a new performance edge

8. Sharpening the focus on diversity and inclusion

9. Reinventing leadership: Leading from the inside out

The State of Organizations in 2026 may be fine; look how Block's stock went up on Friday. 

The state of employment, however, is very different, and I don't think employees or society is fully prepared. 

♻️Repost this great read that predicts the jobpocalypse.
hashtag#Fintech, hashtag#AI, and Tech at the speed of Asia and China.

The AI ‘Jobpocalypse’ Begins and Block Shows Why.

Neobanks are the new kings of banking. With almost 40% of the new banking relationships worldwide, 52% satisfied with their bank, and 72% of consumers now having two or more banks.

A few years ago, there was a serious debate about whether neobanks were just a passing trend or here to stay.

These numbers don’t lie with big neobank gains worldwide:

↳ 39% of new banking relationships
↳ 19% of all bank accounts
↳ 5% of revenue share

While the 5% revenue share figure above may raise eyebrows, don’t expect this low figure to last. 

There are clear signals of increased profitability, with revenue per customer jumping to USD 100 per account per year, up from USD 75 just 24 months ago.

Critics were correct in that initially, there were far too many neobanks, and the overall number of neobanks has declined.  

But the global leaders that remain are a real threat with rates and low fees that incumbents can’t match.

↳ Nubank + Revolut added 50+ million users in the past two years alone (the world's fastest growing banks)
↳ 20+ neobanks now exceed 10 million customers; ~100 have passed 1 million

The few areas where incumbents still lead are trust, fraud protection, and customer support. 

Trust was always neobank’s “Achilles heel,” but even this gap is shrinking. 

I’ll use myself as an example. I went from four primary incumbent banking relationships to seven, with three neobanks added in recent years. 

Yes, the incumbents have more of my money, but that is changing by the month. 

Can incumbents keep up?  

Don’t count on it.  

Hampered by legacy tech and mentality, they will have a hard time besting fast-moving neobanks with new products, gamification, low-fee monetization, and leveraging AI. 

This doesn’t mean incumbents are doomed, as they have deep societal connections that will keep them afloat for years.  

That said, we can expect them to have dwindling relevance, particularly to clients in their 30’s (or older ones like me!) who are comfortable with digital relationships. 

The new banking king?

Neobanks and their rise is unstoppable.

Who’s winning the banking battle for your money right now?

♻️Repost to share this great read on neobanks! 
#Fintech, #AI, and Tech at the speed of Asia and China

Neobanks the new kings of banking

Stanford’s Emerging Technology Review is out — and it’s a must-read “Top 10 List” for anyone tracking the tech reshaping our world.

For fintech followers: dive into the AI, Quantum, and Cryptography sections — these directly impact payments, security, and the future of digital finance.

For those wanting a break from fintech, the Neuroscience and Materials Science chapters offer a refreshing, eye-opening shift to completely different frontiers.

The report aims to secure US tech leadership, but don't let that scare you away.

It is a clear, insightful guide to tomorrow's breakthroughs, and is relevant no matter what country you live in or your focus.

Download it here and see what’s coming next. 

What section caught your eye?

👉The Ten Technologies:

01. Artificial Intelligence
02. Biotechnology and Synthetic Biology
03. Cryptography and Computer Security
04. Energy Technologies 
05. Materials Science
06. Neuroscience
07. Quantum Technologies
08. Robotics
09. Semiconductors
10. Space

Thank you to Walter Sepp Aigner for sharing this PDF with me!  

Got a fresh PDF report that you think our community would like?   
Send it over, I'm always on the lookout for good reads to share! 

⛷️Holiday post!  Back next week with longer reads. 
♻️Repost and share these future tech advances. 
#Fintech, #AI, and Tech at the speed of Asia and China.

uninterrupted innovation is key - even if too many hope to ignore innovation - I facilitate hands-on innovativeness with leading-edge champions in Europe as innovation facilitator and curator of (non-)knowledge inflows

The Top 10 Tech Emerging Technologies

The IMF has a MUST-READ report covering Southeast Asia’s (SEA’s) QR-based digital payment revolution that is transforming cross-border payments, promoting local currency usage, and boosting trade and inclusion.  

Humble QR payments, born in China back in 2014, are now changing all of SEA and especially Thailand, a local leader in digital payments, including CBDC.  

The IMF reports domestic QR payments are exploding throughout the region: 

↳ +300% growth in Thailand, 
↳ +550% in Malaysia, 
↳ +467% in the Philippines, all for 2023-24.

But what is happening now is even bolder as QR payments have just begun to go cross-border to reduce cost and time.

To do this, Asia is connecting QR payment systems to allow bilateral real-time transfers in a collaborative effort between governments and local private payment providers.  

The drive for these connections comes from tourism, with intra-ASEAN tourism accounting for 42% of all visits, and the region’s financial backbone, SME businesses.

SMEs benefit from cross-border QR payments in two ways: 

↳ Expansion of their market reach into new countries. 

↳ Establishment of a digital payment footprint that can be used to assess creditworthiness and bring greater inclusion.

Another key point is that these cross-border transactions use local currency and avoid the risk of using US dollars and currency shocks. 

A fact that USD stablecoin fans would do well to take note of. 

The IMF shows QR payments increase with: 

↳ Higher volatility of the local currency against the US dollar. 

↳ Substitution for traditional banking and credit card payments when they are difficult to access. 

↳ Increased tourism receipts.

↳ High cost and slow speed of traditional cross-border bank transfers. 

↳ The number of banks participating in the linkages.

Given the fame of SEA scam centers, it's no surprise that QR cross-border payments are not immune. 

Still, what we are seeing throughout the region is, as the IMF says, a real revolution!  

Now, without being too smug, aren’t you all impressed that I talked about this in my book Cashless 4 years ago?! 

♻️Repost to share SE Asias QR revolution! 
#Fintech, #AI, and Tech at the speed of Asia and China.

SE Asia's QR Digital Payment Revolution

Banks are stuck in AI “pilot purgatory,” and to escape, the author Oscilar proposes an “imitation is flattery” strategy that copies AI use cases that work elsewhere and runs them in parallel with legacy systems.

Copying the success of others isn’t a novel strategy, but in this case, it is very practical because banks don’t have time to waste.

It also saves banks from ripping and replacing legacy systems. 

Some see this as the best solution to AI pilot purgatory, but it will only make banks fall even further behind. 

Systems replacement also doesn’t solve other problems that cause the gap between AI enthusiasm and action:

↳ Long procurement procedures, 

↳ Lack of real-time continuous AI governance, 

↳ The inability to surrender control of their business to AI vendors/providers.   

The strategy is for banks to simply “wedge” AI infrastructure alongside legacy systems without requiring wholesale replacement.

The authors, of course, give this a fancy name.

They call it a “tractable wedge,” which is an “execution pattern observed in live deployments that allows banks to progress toward the AI Bank of the Future incrementally.”

Sounds like copying to me.  

Proposed Wedges:

↳ Shadow mode:  Run a new AI decisioning engine in parallel with legacy

↳ Analyst-assist agents: agents to perform the data gathering and preliminary analysis.

↳ Greenfield products: Build an AI-native risk stack specifically for new product lines. 

↳ Natural language to rule generation: Allow non-technical users to create and test rules. 

↳ AML False Positive Reduction: Deploy an AI “overlay” that performs secondary scoring

Some may critique this strategy as not using AI to its fullest as with a system rip and replace. 

They are correct, but Oscilar estimates that these installations can capture 70-80% of AI’s potential value.

That is more than good enough if copying can actually deliver AI into actual production!  

The problem isn't optimizing AI, but not falling behind.

Banks should jump on this paper.

This is a down-and-dirty AI strategy for laggard banks that makes perfect sense.

(Even if it's just copying with a new name.)  


♻️Repost to share this practical AI strategy: copy others!
#Fintech, #AI, and Tech at the speed of Asia and China.

Banks Need To Get Out of "Pilot Pugatory!"

The AI commoditization crisis is here — this powerful new read explains why, with almost every company using the same AI tools, true differentiation is slipping away unless they build in "intelligence capital."

The author Simon Torrance is on the front lines implementing AI Agents with his company AI Risk, and I received his permission to reprint this article.

How many customer chatbots have you used lately? 

They felt novel a few years ago. Now they’re table stakes — no real edge, no differentiation.

Why? 

Banks and finserv firms rely on the same three or four LLMs, the same consultants with McKinsey and Accenture, and have the same use cases. 

The outcome: AI that automates, but is dull and can’t create a competitive edge.

Enterprise leaders should be asking: 

“Is my AI investment building something a competitor cannot replicate by simply buying the same tech six months later?”

Simon answers that the answer is: No, unless they shift from AI that doesn’t just automate but accumulates. 

The goal of AI isn’t just faster processes; it’s "Intelligence Capital." 

↳ Intelligence Capital: institutional knowledge that compounds with every decision, persists beyond individuals, and can’t be copied by purchasing the next vendor release.

↳ AI agents that provide intelligence capital provide true differentiation as “your competitors can’t build them.”

↳ To generate intelligence capital with AI, we need to use agentic teams that deliberate over data to turn it into a decision.  

Make no mistake, this is advanced agentic use at a time when many think chatbots are cool.  

It is intelligence capital that will differentiate companies' AI usage and provide real value. 

The interesting part is that this use of agents mirrors a human committee rather than an assembly line.  

It also opens the door to using AI digital twins of employees to access their decision-making abilities.

In a world where AI assistants are already a commodity, the winners won’t be the ones who automate fastest.

They’ll be the ones who accumulate Intelligence Capital that no one else can replicate.

Thanks again to Simon Torrance for sharing this article!

♻️Repost to share how Agents can provide a real edge!
#Fintech, #AI, and Tech at the speed of Asia and China.

Expert on Strategy & Innovation | Agentic AI | CEO, AI Risk | Founder, Embedded Finance & Insurance Strategies | Guest lecturer, Singularity University | Keynote speaker

AI Risk

AI is Now a Commodity:  Build a Real Edge

Weekend Read: AI’s Impact on Jobs: What the Data Actually Shows (Spoiler Alert: It’s Not What You Think)

A fresh study cuts through the AI job-loss panic fueled by headlines like Block’s 40% staff cuts.

The real numbers paint a more nuanced picture.

AI disruption is coming, but it’s not hitting hard yet, at least not as fast as the fear-mongering suggests.

Key takeaways:

↳ Limited evidence so far that AI is driving broader unemployment — top 25% most exposed workers show similar unemployment trends to those with zero exposure

↳ Limited evidence that AI is playing a role in the broader labor market today.

↳ Limited evidence that AI has increased unemployment to date.

↳ Hiring of younger workers (22–25) in high-exposure roles is down 14% — they may be staying in existing jobs, shifting roles, or returning to school.  25+ shows no impact.

↳ Actual AI usage is far below theoretical capability. The “observed exposure” (what people really do with tools like Claude) is much lower than models can handle

↳ Top-exposed workers earn 47% more on average, have higher education, and skew white-collar

↳ Demographics of the most exposed: Female (+16%), White (+11%), Married (+10%), Asian (+4%)

↳ Highest exposure roles: Programmers (75%, observed exposure), Customer Service Reps (70%), Data Entry Keyers (67%)

↳ Lowest exposure: Physical/manual jobs like Cooks, Mechanics, Lifeguards, Bartenders, Dishwashers (~30% of workers have zero observed exposure)

There is no doubt that AI is reshaping work, but it’s not the mass job-killer just yet.

With low "observed exposures," however, we're just at the start of the disruption. 

It’s hitting higher-paid, white-collar roles first, while physical jobs remain largely untouched.

-Are you seeing AI change roles around you? 

-Are the claims of AI job loss, like Block's, a way of claiming dubious AI advances rather than admitting poor performance?

♻️Repost to share the latest on AI's impact on employment
#Fintech, #AI, and Tech at the speed of Asia and China.

AI job losses aren't hitting just yet....but they will

McKinsey highlights Southeast Asia (SEA) as a global AI leader where 46% of companies have AI at scale compared to 35% globally, fueled by billions from Chinese and US tech giants. 

What McKinsey dares not address is that SEA is profiting from its position as an AI battleground between the US and China. 

With Chinese and American tech companies locked in cut-throat competition, SEA is able to play the providers off of one another. 

↳ Indonesia and Malaysia are great examples of nations where Alibaba, Tencent, Microsoft, and Google are investing billion-dollar sums in data centers in a fierce competition.

↳ McKinsey misses that the region’s young connected population largely takes China’s tech for its inspiration.

↳ With ubiquitous QR payments and superapps, what is successful in China will likely work in SEA. 

This doesn’t ensure Chinese AI and cloud providers will come out on top.  SEA also loves YouTube and Facebook.

Yet China’s open-source AI ecosystem (free AI) gives its cloud providers an edge that most in the West underestimate.

Kudos to SEA for turning the superpower competition into a massive local advantage! 

♻️Repost to share this great read on SE Asia's AI
#Fintech, #AI, and Tech at the speed of Asia and China.

SE Asia Turns US-China Competition Into Advantage

Money20/20 Asia’s annual survey confirms what I’ve been saying for years: Asia is the world’s leading fintech capital, driving global innovation with unmatched momentum.

Key highlights from the report:

↳ 90.6% of executives say financial inclusion and social good are now embedded in core business strategy — not vague CSR, but a commercial imperative for long-term success

↳ 22.9% identify SEA as their primary growth target, solidifying its role as the global growth engine, beating all other global regions.

↳ 61.2% of organizations have already adopted AI or machine learning at scale

↳ 63.5% rank fraud prevention as their top operational priority

↳ 72.9% see SME-tailored fintech solutions as critical to regional economic growth

↳ 66% see hyperlocalisation as key for launching across new Asian markets.   APAC is definitely not homogeneous! 

The region is shifting from experimentation to full-scale deployment across AI, digital assets, QR payments, superapps, cross-border linkages, tokenization, and stablecoins.

And unlike the West, regulators are actively backing disruption, not protecting incumbents.

No technology is off-limits in the pursuit of inclusion and real GDP growth.

Asia isn’t copying the West, it’s redefining the future of finance.

♻️Repost this important read on fintech in APAC! 
#Fintech, #AI, and Tech at the speed of Asia and China.

SEA Fintech: "A Primary Driver of Global Innovation"

Identity fraud is a global $58B problem, and this year’s top trend is that it is changing from “low-effort” high-volume schemes to “sophisticated fraud” using deepfakes and social engineering, up 180% YoY.  

The days of an email asking you to unlock your account sent from a hopelessly wrong email address are gone, and for that, we owe thanks to AI.  

But the AI knife cuts both ways. 

“Sophisticated fraud” is an attack that combines multiple coordinated techniques such as AI-generated identities, social engineering, device or telemetry tampering, and cross-channel manipulation. 

Unlike phishing or other more simple attempts, these multi-step schemes require AI, planning, automation, and adaptability, making them far harder to detect and contain.

They are also larger, with a longer-term impact for victims and institutions, as they require greater preparation and higher costs.

The top trends for this year:

↳ The Sophistication Shift: Less sloppy and low effort fraud, but more advanced attempts.

↳ AI industrializes Fraud: AI is evolving into a sophisticated fraud production ecosystem.

↳ AI Fraud Agents: Autonomous systems that combine generative content, scripting, and behavioral mimicry to execute full verification attempts end-to-end.

↳ Telemetry tampering becomes the new evasion: fraudsters are increasingly targeting the data pipelines themselves rather than the identity artifacts alone.  API attacks!

In banking and finserv synthetic identities are hot, making static online onboarding problematic and increasing the need for behavioral biometrics. 

Synthetic identities can slowly build credibility before executing large cash-outs and chargeback abuse. 

And since regular readers might ask: What about APAC? 

APAC has the dubious distinction of leading, as it is one of the most active fraud environments in the world. 

AI is at the core of both committing and defending against fraud; which do you think will prevail in the end?

👉How to read:  Don't be afraid of the long length.  Read the first 30 pages 

♻️Repost to share this great read on Identity Fraud
#Fintech, #AI, and Tech at the speed of Asia and China.

Identity Fraud's $58B Nightmare Continues as AI fights AI!

Plaid's fintech trends for 2026 are a great read, and wake up call as four out of ten are fraud-related.

This shouldn't come as a surprise when the US alone lost $12.3 billion to fraud in 2023, with GenAI potentially pushing losses up to $40 billion by 2027. 

Unless the industry gets better control of fraud, which is exploding due to GenAI, the losses will be simply unsustainable. 

The irony, of course, is that GenAI is used by both fraudsters and financial services, with fraudsters having the edge on innovation.  

Of course, AI ranks the No 1 in the list due to its use in fintech apps, where chat will become the "default front door for consumer finance."

Still, the sad reality is that while everyone is excited about AI's impact on the front door, the back door is wide open. 

Meanwhile, concrete anti-fraud measures like digital ID don't get a reference in the paper.   

We are left hoping that finserv can use GenAI to control fraud at least as well as fraudsters.     

Now that should be a wake-up call. 

👉Plaid's Top 10 for 2026

Trend #1: Fintech apps are becoming a financial co-pilot 
Trend #2: Fraudsters are getting smarter 
Trend #3: Fraud prevention has become a team sport 
Trend #4: Alternative payment types reaching mainstream acceptance 
Trend #5: Lenders are moving beyond all-purpose credit scores 
Trend #6: Open banking is a baseline expectation 
Trend #7: Al shifts from novelty to consumer necessity 
Trend #8: Neobanks are launching on stablecoin rails 
Trend #9: Al is the front line in the fight against fraud 
Trend #10: Fraud moves upstream in the transaction process

⛷️Short holiday post!  
♻️Repost to share this honest read with others
#Fintech, #AI, and Tech at the speed of Asia and China.

Fintech Predications 2026:  Fraud Dominates the List

Citi's "Ten Global Insights for Leaders" Is Required Reading for Everyone — Not Just Leaders

Citi’s latest report is a must-read for anyone trying to navigate our chaotic world, not just the C-suite. 

Calling it “for leaders” feels a bit tone-deaf — these insights matter to all of us.

While AI and stablecoins unsurprisingly top the list, Citi also spotlights a rising Asia as a defining force:

Asia Pacific Economic Cooperation (APEC) countries now account for 61% of global GDP and 60%+ of FDI (up from 55% and 40% two decades ago)

Chapter 5 on geopolitics is essential — and not just because bombs and missiles are now sadly flying. 

Every major tech and fintech trend, stablecoins, payments, and AI now carries a geopolitical layer we can’t ignore.  

AI above all is full of geopolitical landmines: chips, data sovereignty, open-source LLMs, and more.

This is a great macro overview that isn't just for "leaders" but for everyone trying to make sense of a chaotic world.  

The four interconnected themes:

1️⃣  AI transformation:  
While Al is starting to drive productivity gains, it is also creating new fraud risks, as deepfake incidents surged 47x since 2022.

2️⃣  Geopolitical realignment: 
Rising geopolitical tensions are redirecting capital flows, with family offices citing trade disputes as their top concern, and defense spending now exceeding development aid by 2:1.

3️⃣  The evolution of financial markets: 
Financial infrastructure is undergoing radical change through private market democratization, 24/7 settlement cycles and European market harmonization.

4️⃣  The impact of digital assets: 
Stablecoins and bank tokens are transitioning from
crypto novelty to core financial infrastructure, with the
market projected to reach $1.9 trillion by 2030.


👉The Ten Themes/Chapters:
1.  Al: The Information Era's Apex Technology
2. Al in Investment Management: Beyond Efficiency Gains
3. Al Deepfakes: When Seeing and Hearing Can't Be Trusted
4. Private Markets: Access, Innovation and New Pathways to Progress
5. Global Family Offices Navigate a Changing World Order
6. Public Sector Perspectives: Financing National Security Priorities
7. APEC: The New Connections Driving Trade
8. The Future of Post-Trade: Custody and Settlement in an Always-On World
9. Reimagining European Capital Markets: From Fragmentation to Harmonization
10. Stablecoins 2030: Web3 to Wall Street


⛷️ This is a short holiday post!
♻️Repost to these Ten Insights everyone needs now! 
#Fintech, #AI, and Tech at the speed of Asia and China.

10 Global insights NOT just for "leaders" but EVERYONE

With the NYSE and the NASDAQ creating new markets for tokenized stocks, we'll all soon be deciding whether we want to buy our shares "on-chain" or through traditional methods. 

But buyer beware, not all tokenized stocks are created equal.

Tokenization promises direct, verifiable ownership, faster settlement, lower reconciliation risk, and 24/7 asset movement.  

These are compelling and very real efficiency gains that we should all look forward to!

Still, to profit from tokenization, we all need to understand the three types of tokenized stocks in the market:

• Direct Tokenization: A method that directly tokenizes stock ownership (e.g., Securitize, Superstate). This corresponds to Issuer - Sponsored Tokenized Securities in the SEC’s classification framework.

• Entitlement Tokenization: A method that tokenizes stock-related rights within existing infrastructure (e.g., DTCC). This corresponds to Tokenized Security Entitlement in the
SEC’s classification framework.

• Indirect Tokenization: A method where a company buys and holds stocks on behalf of users and tokenizes the beneficial interest in them (e.g., Robinhood, Backed, Ondo, Dinari). This corresponds to Security - Based Swap in the SEC’s classification framework.

Synthetic/indirect models offer exposure but often strip shareholder rights, introduce counterparty risk, and create fragmented liquidity (platform-dependent, not interoperable).

Are synthetic or "indirect tokenizations" bad?  

NO!  

They can be a great way for investors to gain access to stocks, but know before you buy what form you're getting. 

Remember, liquidity is everything when you want to sell, and it is not interoperable across different indirect tokenization platforms!

How to read: Go to page 18 and read the three mechanisms currently available, and then page 30 for an analysis of the major tokenization platforms!  

Are you excited about tokenized stocks and looking forward to your first purchase or sticking with traditional shares for now?

♻️Repost this as a public service to help others understand the "buyer beware" nature of tokenized stocks.
#Fintech, #AI, and Tech at the speed of Asia and China.

Tokenized Stocks Are Here – But Not All Are Created Equal

The most comprehensive survey yet of AI use reveals the disparity between expectations and reality, with 70% using AI and 80% report no impact on company productivity or employment.

AI is everywhere, with billions invested in implementing it with the goal of increasing worker productivity and cutting employment costs. 

The National Bureau of Economic Research (NBER) surveyed 6000 executives in the US, UK, Germany, and Australia to show that while AI benefits may be coming soon, for now, they are still nowhere to be seen.

The survey found:

↳ “First, around 70% of firms actively use AI, particularly younger, more productive firms.

↳ “Second, while over two-thirds of top executives regularly use AI, their average use is only 1.5 hours a week, with one-quarter reporting no AI use.

↳ 🔥“Third, firms report little impact of AI over the last three years, with over 80% of firms reporting no impact on either employment or productivity.

↳ “Fourth, firms predict sizable impacts over the next three years, forecasting [that] AI will boost productivity by 1.4%, increase output by 0.8% and cut employment by 0.7%.”

↳ This contrasts with individual employees, who predicted “a 0.5% increase in employment in the next three years as a result of AI.” ‼️

There remains a huge gap between executive use in AI, with 25% of executives not using AI at all!

A third of executives surveyed reported using AI in the workplace, but the usage amounted to only 1.5 hours per week on average. 

So we have a system where executives who have little direct experience using AI are being asked to manage AI rollouts. 

If that isn’t a recipe for failure, what is? 

Another factor is also at play, and that is Solow’s productivity paradox. 

Economist Robert Solow famously observed in 1987: “You can see the computer age everywhere but in the productivity statistics.” 

He was highlighting how massive investments in IT failed to deliver measurable economic gains despite widespread adoption due to "information overload." 

It is likely we are facing a similar delay in realizing AI productivity gains. 

What the survey shows is that AI is now the “new normal” in business and that while productivity gains may be delayed, they are likely coming. 

The big question is, will they result in the predicted 1.75 million fewer jobs by 2028 at these firms?


♻️Repost to share this important survey on AI productivity
#Fintech, #AI, and Tech at the speed of Asia and China.

80% of Companies Report No Productivity Gain from AI

Kudos to the DTCC, Clearstream, Euroclear, and BCG for working on bringing DLT interoperability to securities because, until they, or the NYSE, set the standards, market fragmentation is a real risk.

My first article on DLT securities interoperability dates back to April 2024, and I’m frustrated because we still haven’t tackled DLT interoperability. 

All the hype around tokenized/digital securities — 24/7 trading, lower costs, instant settlement — remains just that: hype.

This is so basic it’s shocking that no one has tackled interoperability at scale. 

Interoperability in capital markets can be defined as “the ability to exchange assets across ledgers – DLT and traditional – while preserving the asset’s integrity, ownership rights and lifecycle, with full legal and regulatory compliance.”

In other words: “same asset, same rights, same outcome” across both rails. 

One possibility, and I don’t think this is far-fetched, is that the NYSE and NASDAQ tokenization programs will end up defining/driving interoperability based on their standards. 

But here is the real problem: as ad-hoc DLT adoption surges in capital markets, NYSE and NASDAQ efforts included, there is a real risk of market fragmentation. 

Fragmentation traps assets in silos, inflating operational costs, fragmenting liquidity, and may lead to inefficiencies that are worse than traditional markets. 

So, how to move the market forward?  Brace for it, it's not rocket science:

1. Data standardization – creating common identifiers, taxonomies, and message standards, as financial markets did in the past with ISIN.

2. Process harmonization – ensuring minimum definition of core processes such as settlement, reconciliation, and corporate actions, replicating the efficiency gains achieved in traditional finance through SWIFT standardized protocols.

3. Consistent roles assignment – clearly defining responsibilities for critical functions (for example, custody, validation, oversight), as traditional finance achieved with custodians, CSDs, and clearing houses, to preserve accountability and trust.

Three years on from my first piece, we’re still at square one on scaling this.

Does this latest white paper give you confidence that DLT securities/tokenization are truly around the corner... or is it still mostly talk?

♻️Repost if you want interoperable securities tokens not hype.
#Fintech, #AI, and Tech at the speed of Asia and China.

Lack of DLT Interoperability Threatens Tokenization

FATF’s latest report lays it bare: P2P stablecoin transactions on unhosted wallets are now the go-to method for illicit finance.

↳ Criminal use of stablecoins now represent 84% of the USD $154B illicit virtual asset transaction volume in 2025.

↳ Stablecoins now beat Bitcoin as the dominant crypto asset for crooks.

↳ P2P stablecoins transactions on unhosted wallets are a feature, not a bug 

When the US decided to use stablecoins to digitize the dollar, it left a major loophole that criminals just love: P2P transactions. 

P2P stablecoin transactions through "unhosted wallets" are no different than passing a suitcase full of cash, as they occur directly between individuals or entities.

They are untraceable as they don't pass through a regulated intermediary Virtual Asset Service Provider (VASP) or financial institution. 

P2P transfers put AML responsibility on those ill-equipped to do it:
 
-Stablecoin issuers, who can't be bothered by small amounts.
-Intermediary VASPs, often in foreign domiciles, who don't care.
-Financial institutions, which are challenged to find the origin of the funds or don't want to know.

That AML is hard on stablecoins is a given, but it becomes nearly impossible with P2P where:  

-Stablecoins are used cross-chain to hide the transaction trail.
-Money mule networks are pressed into service. 

Now, if you think the FATF has a solution to this problem, you're dead wrong. 

↳ The FATF recommends only that nations put AML/CFT obligations on issuers, VASPS and banks.   

As we see above, that is simply not practical, but a scant few countries are making limited progress:

-Denying licenses to VASPs that allow self-hosted wallet transfers. (FATF doesn't say which country)
- Limiting customer transfer to first parties (Singapore)
- Enhanced due diligence. (Germany, Switzerland)
- Blockchain forensics (Germany, France, and Singapore)
 

↳ Next, the FATF recommends that nations require stablecoin issuers to be able to burn, freeze or withdraw stablecoins from secondary markets.

Stablecoin Tether is issued in El Salvador. How often will El Salvador request that it burn or freeze a coin, or how would they know how it is being used?  (Note: Tether complies when the US Treasury asks.) 

Stablecoins are incredibly convenient… and criminals know it.

Are we building the next-gen payment rail — or the next-gen laundering tool?

How to read:   Go to pages 11-18 for a good overview. 

♻️Repost to share the downside of stablecoins 
#Fintech, #AI, and Tech at the speed of Asia and China.

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