LinkedIn Top Voice & digital strategist - helping corporate leaders to become unforgettable via personal branding and storytelling.

Hi, I’m Kinga Bali, Strategic Digital Advisor, Visibility Architect, and LinkedIn Top Voice, working at the intersection of digital transformation, thought leadership, and sustainable innovation.

My work spans corporate ecosystems, personal brands, and digital education, with one throughline: building visibility systems that scale trust, traction, and transformation.

What I Do

🔹 Digital & Brand Transformation
Drive end-to-end marketing strategy, digital innovation, and go-to-market execution across global platforms and purpose-led businesses.

🔹 Thought Leadership & Executive Presence
Shape high-authority positioning for founders, executives, and scaling brands, backed by real traction—not just content noise.

🔹 Lecturing & Strategic Advisory
Teach digital trust and visibility at the university level; advise leadership teams on narrative risk, reputation, and influence.

🔹 Visibility Partnerships & Board Engagements
Collaborate with brands and boards on trust-rich positioning, audience strategy, and digital credibility systems that scale.

Why I’m Called In
✔ 20+ years in digital strategy, innovation & transformation across Nestlé, Reckitt & mission-led orgs
✔ MBA research in executive branding, focused on digital trust & influence
✔ Proven ability to align business, tech & content into scalable visibility frameworks
✔ Operational leadership across functions & C-suite enablement
✔ Led platform rollouts across 100+ markets incl. L&D & CRM
✔ Built content systems & product storytelling for global scale

Recent Milestones

• Rolled out global L&D and CRM platforms across 100+ markets
• Built scalable content architectures supporting multilingual delivery and automation
• Shaped high-conversion narratives for digital platforms and internal adoption campaigns
• Created go-to-market frameworks that bridge product, comms, and leadership strategy

I started posting on LinkedIn in 2023 as an MBA assignment. Eight months later, I earned a Top Voice badge with under 4,000 followers. 

Now? 17,000+ followers. Countless DMs. Deep conversations on tech, leadership, and influence.
I’m also open to a select number of board and advisory roles, especially where digital strategy, product storytelling, and culture design need to scale together.

Next Moves

I’m building a portfolio career, board-ready strategy meets product storytelling, executive visibility, and scalable systems. If you’re building something ambitious, transformative, or even a little messy, I’m all ears.

📌 All views are my own. But I speak for the quiet rebels building loud results.

Why low reach might be the best thing for you?
Yes, really. Hear me out.

LinkedIn reach is down. 
Everyone sees it.
Some blame the algorithm. 
Others blame soft content.
Most panic. Or chase trends. Or disappear.

But what if… it’s a gift?

Fewer impressions = less pressure to perform.
Fewer comments = more room for depth.
Less noise = clearer signal.

You get to post without the crowd.
You get to test ideas that aren’t optimized for hype.
You get to reconnect with why you’re writing.

It opens the door to:

• Sharper signal testing
• Longer-form storytelling
• Moving your IP beyond just posts
• Trying that new format you’ve held back

LinkedIn becomes your public gym.
Not a billboard. A lab.
You don’t need 100k views.
You need one real connection that leads to actual traction.

Daily writing still builds the rep.
Still fuels the assets.
Still creates the edge.

Traction never depended on reach.
It came from trust. 
From signal. From the real work.

The algorithm may recover.
But so can your attention span.

Would you keep writing if the views never came back?

Kinga Bali

LinkedIn changed. So did I.
Reach shifted. Vibes shifted. 
Dynamics shifted. 
So I adjusted.

What started as an MBA experiment
became a public lab.

I still share. I still build.
But here’s what I realised:

You’ve known me for tools, language, frameworks.
Now I’m building the next layer:
systems, toolkits, books,
things you can hold, use, and share.

Things snowballed.
I needed structure.
Infrastructure.

Posts became chapters.
I’m now writing three books in parallel.
Not chaos, design.

↳ Boost Her Voice
Not a feminist cryout. A visibility redesign.
↳ The Brilliant Glitch
Neurodivergence, performance, and voice.
↳ The Job Seeker’s Guide in the Age of AI.
Strategy, prompts, and tactics
 you didn’t know you needed.

Each comes with expenses:
Design. Editing. ISBNs. Tools.

Many pieces come from client work,
lecturing, and deep research.
The quality is levelling up.

But here’s the paradox:
Free = generous. 
But free isn’t taken seriously.
Not always.

So I’m shifting.
Some parts will be gated. Some priced.

Not a pivot. Not a pitch.
Just clarity.

No snake oil.
No fake urgency.
Just public building,
with better boundaries.

If you’ve used this work, forwarded it,
built on it, thank you.

You’ll start seeing where and how
to support it, too.

What would you actually pay for,
if it solved a real problem, fast?

Penny for your thoughts?
And maybe a glitch worth funding.

My first book, The Unforgettable You,
drops next week.

The next one?
It will be built in public.
With you.
One post. Every week.
For a year.

The Brilliant Glitch
A toolkit. A book. A system.

For people with ADHD, Autism, or Dyslexia.
Or those who lead, love, or raise them.

Why now?
Because masking is killing clarity.
Because misconceptions are harmful.
Because most parents are left guessing.
Because ND adults are burning out quietly.
And because no one gives us the right words.

This project will offer:

↳Real stories, failures, redesigns
↳Tools for ND teams and parenting
↳Language that explains, not excuses
↳Open-source rituals, prompts, and scripts

Most of it will be free.
But systems take time, care, design.

Want to support it?
You can drop some pennies here:
https://lnkd.in/eXdbhv_E

What do you wish someone told you
about leading, working, or parenting with a glitch?
Your answers may shape the next chapter.

The Brilliant Glitch

We believe in luck until we sober up.
(And this is what plays better with the odds.)

I still believe in luck.
Not the lottery kind.
The kind where you toss salt.
Touch the wood. Whisper a wish.
Just in case.

Not because it works.
Because it moves me.
Myth with momentum.
Ritual when routine crumbles.

Because luck fades.
Seasons shift.
Energy dips.
What stays?

The compound interest of motion.

The boring.
The unseen.
The reps no one claps for.

Not every pitch lands.
Not every post performs.
Not every effort echoes back.

But you know what guarantees nothing?

Stalling.
Waiting.
Holding out for January clarity.

Yes, you can get lucky.
Once. Maybe twice.

But the ones who stay?
They were showing up on tired Tuesdays
and flu-season Fridays.
Building while no one watched.

And when the light hits?
People will say, "It’s all happening for you."

You’ll sip something hot
over the ashes of unanswered emails
and smile. Because it wasn’t luck.

It was motion.
Relentless.
Compounding.

So… what will you do this week
that luck can take credit for next year?

You hoped AI would pass. It stayed and hired.
The work is still there. The skills aren’t.

You don’t need to code.
You just need to start.
Here are 6 high-impact, free platforms,
built for people who never thought they'd learn AI.

1️⃣ The Skills Gap Is Real
75% of companies say AI skills are missing.
Only 1 in 5 workers feels ready to use AI at work.
The gap isn’t just technical; it’s confidence, too.

2️⃣ Demand’s Exploding
AI-related roles grew 250% in two years.
Prompt engineers. Trainers. Auditors.
New titles. New rules. No slowing down.

3️⃣ Upskilling Works
Companies that invest see up to 20% productivity gains.
And 70% of leaders now call AI training a must.
It pays off fast—if you start early.

4️⃣ What Skills Actually Matter
It’s not just coding. It’s context.
Data literacy. Critical thinking. Prompting.
Ethics. Change management. Translation over tech.

5️⃣ People Want to Learn
82% want AI in their daily work.
Only 28% say their company helps them.
The curiosity is there. The support isn’t.

6️⃣ No-Code = No Excuse
60% of enterprise AI runs on low-code tools.
That means you don’t need to “be technical.”
Just be open—and willing to try.

7️⃣ AI Literacy Is the New Excel
By 2030, using AI will be basic fluency.
Like spreadsheets were in 2005.
It’s not a specialty. It’s the standard.

8️⃣ Leadership Changes Everything
AI-confident leaders scale AI 2.5x faster.
Culture decides whether learning sticks.
Or gets quietly ignored.

You don’t need to code.
You just need to start.

Here are 6 high-impact, free platforms,
built for people who never thought they'd learn AI.

1️⃣ OpenAI Academy
Step-by-step lessons, practical exercises, real-world use.
Beginner to advanced, no fluff. Surprisingly good.

2️⃣ Elements of AI
Taught by a university. Trusted by over 1 million learners.
No coding. No jargon. Just real understanding.

3️⃣ Google AI Essentials
AI basics, real use cases, and a free Google certificate.
Self-paced. Built for the day-to-day.

4️⃣ Microsoft Learn: AI for Beginners
Structured, bite-sized, and beginner-proof.
Concepts + hands-on tools. Start with zero.

5️⃣ IBM SkillsBuild
Designed for career switchers and non-tech learners.
Learn AI, ethics, and get digital badges to show it.

6️⃣ Khan Academy: AI & Machine Learning
Free. Friendly. Clear.
Explainers for every age and every attention span.

Start small.
One course. One session. 
One concept that clicks.

The goal isn’t to master AI.
It’s to stop feeling behind it.

You don’t need a tech background.
You need momentum.

Now’s a good time to build it.
Who’s catching up while you hesitate to learn?

𝗞𝗶𝗻𝗴𝗮 𝗕𝗮𝗹𝗶

AI upskilling

Lisa B.

After the AI gold rush.
What’s left is the hard part.

We use AI knowingly when we prompt, plan, or code.
We use it unknowingly when we swipe, scroll, or speak.
It's inside your maps, your inbox, your camera roll.
Invisible, silent, woven into everyday habits.
Now leaders must make it reliable, secure, human.
Here’s where the real work begins .

1️⃣ AI gets expensive fast to run
Running it means constant servers, updates, and storage.
The bill grows fast, often faster than expected.

2️⃣ Bad data creates unfair results
AI copies what it learns.
Bad inputs mean biased or broken outputs.

3️⃣ No training means no adoption
New tools confuse teams without support.
People won’t use what they don’t understand.

4️⃣ Weak setups invite security risks
New models open new doors for attacks.
Few firms are ready to defend all of them.

5️⃣ Talent gaps stall AI progress
The tools evolve fast.
Most teams don’t have the people to match.

6️⃣ AI needs fresh data to stay useful
Outdated data leads to wrong advice.
AI must learn constantly to stay sharp.

7️⃣ Old systems struggle with AI tools
Most setups were not built for AI loads.
Connections break. Costs rise. Teams get stuck.

8️⃣ If people don’t get it, they won’t trust it
If you can’t explain it, you can’t sell it.
Trust needs clarity, not just output.

Hype made the headlines.
Care builds the future.

Reliability scales what flash alone can't.
Steady beats shiny.

What seemed easy now gets real.
This is where the work begins.

What breaks first: trust, skill, or systems?

8 AI Growing Pains

The Brilliant Glitch 
Neurodiverse minds.

Some problems? 
Cannot be solved with the old ways. 
Non-linear brains to the rescue. 

📌 Dr. Camilla Pang
The computational biologist reverse-engineering humans.
Diagnosed autistic, with ADHD, as a child.
Treats social interaction like a dataset to decode.
Builds models that translate behavior into algorithms.

📌 Dr. Nancy Doyle
The psychologist designing systems for divergent minds.
Founded Genius Within to rewire workplace inclusion.
Links neurodivergent traits to executive-level strengths.
Builds tools where others build barriers.

📌 Dr. Donna Williams
The theorist who decoded autism from the inside out.
Author of foundational books on neurodivergent perception.
Framed autism as sensory architecture, not defect.
Mapped a new model of cognition, through lived data.

📌 Dr. Sue Black, OBE
The activist who hacked her way into history.
Saved Bletchley Park with sheer grit and code.
Built Techmums to upskill underserved communities.
Hyperfocus turned into her superpower at scale.

📌 Dr. Helen Taylor
The ecologist proving cognitive diversity is survival.
Researches how varied brains boost group resilience.
Links dyslexia to innovation in evolutionary systems.
Turns her own glitch into a scientific hypothesis.

📌 Dr. Mary-Anne Williams
The roboticist solving AI with a restless mind.
Leads research in human-robot collaboration and ethics.
ADHD drives her cross-disciplinary problem solving.
Builds machines that think—and rethink—like humans.

📌 Dr. Marcia Bjornerud
The geologist reading time in tectonic layers.
Dyslexia sharpened her spatial reasoning and pattern vision.
Explores Earth’s memory through rock and rupture.
Sees structure where others see stone.

📌 Prof. Lynn Murray
The mathematician modeling chaos with calm precision.
Solves fluid dynamics problems with applied intuition.
ADHD fuels her nonlinear leaps across equations.
Finds patterns where logic alone falls short.

📌 Dr. Joanne Wood
The neuropsychologist turning data into care systems.
Autistic precision drives her diagnostic expertise.
Translates brain science into real-world interventions.
Sees clarity in cognitive complexity.

📌 Daisy Shearer
The physicist building quantum tech from deep focus.
Autistic, with a special interest in quantum systems.
Works on semiconductors for next-gen computation.
Translates theory into tech, and shares as she builds.

📌 Dr. Maja Matarić
The roboticist designing empathy into machines.
Builds socially assistive robots for therapy and care.
Bridges neuroscience, AI, and behavioral science.
Systems thinking with a human core.

📌 Michelle Dawson
The researcher who challenged the autism playbook.
Redefined intelligence beyond clinical assumptions.
Co-led studies centering autistic cognitive strengths.
Turned lived experience into scientific disruption.

They don’t follow instructions.
They redesign the assignment.
What if the glitch was the upgrade all along?

Neurodiverse minds. Some problems? Cannot be solved with the old ways. Non-linear brains to the rescue.   📌 Dr. Camilla Pang: The computational biolo

Open article: The Brilliant Glitch  by Kinga Bali • 2 min read

You didn’t see this coming.
Or at least not yet.
APO is at the gates.

While everyone is optimizing for GEO...
APO walks in.
Another acronym? 
Yes. But worth remembering.

Agentic Product Optimization (APO) 
is how your product:

↳ stays visible inside platforms
↳ can be purchased by AI agents
↳ appeals to bots and humans alike

Here are the 7 must-knows for smart APO strategy.

1️⃣ Search terms → solved tasks
SEO brought people to your site.
APO helps agents finish the job.
You optimize for completions now.
Not traffic. Not clicks.
Outcomes.

2️⃣ Structure before style
AI agents need structured:
clean, real-time data.
Fix schema markup.
Check product feeds.
Expose availability and price via API.

3️⃣ Friction kills transactions
Can the agent complete the purchase?
They skip what adds steps.
Use delegated payments.
Remove cart friction.

4️⃣ Write for constraints, not impressions
SEO was keyword-driven.
APO is logic-driven.
Help agents choose.
Highlight budget, size, fit, value.
Stay clear.

5️⃣ Trust earns ranking
Agents reward reliability.
Boost verified reviews.
Speed up delivery.
Simplify returns.
Make trust visible.

6️⃣ SEO feeds APO
One builds on the other.
Strong content still matters.
But agent-friendly data wins the sale.
Prepare for both.

7️⃣ Timing is now
Gemini and ChatGPT support holiday shopping.
This is the first season with real APO impact.
You are either ready, or losing share.

Theory? Not anymore.
This is infrastructure.
Built now.
Paid off in Q4.
Expanded in 2026.

Are your systems agent-ready?

APO explained

7 ways AI quietly rewrites the job market.
The shift is not loud. 
It is silent, systemic, global.

Career mobility, formats, and access, 
redesigned without warning.
This is what changes. 
Whether you adapt or not.

1️⃣ Printed CVs still circulate. Most get ignored.
In South Africa, 25% apply after deadlines.
Printed and static CVs persist in hiring flows.
But ATS cannot scan paper.
No format fit means no shot.

2️⃣ AI-made CVs now flood the system.
61% of UK/US applicants use AI tools.
Many sound identical. Trust drops.
Recruiters push video prompts to cut through.
Originality is now infrastructure.

3️⃣ Video CVs rise. Static text reveals less.
Europe moves toward voice and visuals.
Soft skills beat sentence structures.
No energy, no edge.
Text-only is starting to feel flat.

4️⃣ Entry-level roles are vanishing.
AI erases admin, assistant, junior positions.
First jobs disappear fastest.
This breaks the leadership pipeline.
No start means no scale.

5️⃣ Application norms now split by region.
US resumes avoid age and photos.
Europe wants detail, images, soft skill cues.
Asia mixes old and AI-optimized styles.
Wrong format kills global fit.

6️⃣ ATS filters rewrite visibility.
If it cannot parse, it cannot pass.
Design CVs for the scan first.
Keywords are not enough.
Structure decides if humans ever see you.

7️⃣ AI risk is unequal by economy.
Manual work shields emerging markets, for now.
Digital tools lag behind in access.
White-collar roles vanish in the Global North.
The divide deepens without noise.

What breaks first: the tools, the trust, or the talent?

Job market and ai

You lie to you.
The worst? You don’t even notice.

There are 180 biases.
Most can be hacked.
Some? Trained out.
But deletion?
Takes design.
Meet the designers.

📌 Dr. Jessica Milli
The economist who made bias billable.
Quantified the cost of “prove-it-again” culture.
Drove $1.5M in reform-triggering grant shifts.
Turned gender bias into a budget line item.

📌 Dr. Joan C. Williams
The architect of the bias interrupter.
Decoded five patterns that sabotage women at work.
Built tools now reshaping corporate policy.
Showed how 5% bias breaks the pipeline.

📌 Dr. Sylvia Ann Hewlett
The voice that cracked the maternal wall.
Named the silent exit of women in power.
Exposed “creeping nonchoice” as a career design flaw.
Proved ambition is punished when it’s maternal.

📌 Dr. Erica L. Kirby
The analyst who turned microaggressions into macro data.
Mapped isolation bias for women of color in tech.
Proved race reshapes how bias shows up, and stacks.
Forced intersectionality into the metrics column.

📌 Dr. Dawn R. Post
The data scientist who exposed sponsorship gaps.
Measured a 78% promotion bias in STEM sectors.
Revealed equal performance, unequal reward structures.
Tracked where merit ends and exclusion begins.

📌 Dr. Kimberlé Crenshaw
The theorist who named the glitch in the system.
Coined “intersectionality” and rewrote equity’s playbook.
Proved one-axis solutions fail overlapping realities.
Brought nuance into legal code and hiring reform.

📌 Dr. Leticia Márquez-Magaña
The disruptor who rigged the system in reverse.
Exposed how undervaluation blocks Black and Latina hires.
Advanced co-hire models to shift the gate.
Engineered policy from pressure and proof.

📌 Dr. Mary Murphy
The psychologist who mapped bias to brain chemistry.
Showed subtle signals trigger dropout behavior.
Designed fixes that cut threat response by 30%.
Built belonging into the architecture of ambition.

📌 Dr. Corinne Moss-Racusin
The researcher who ran the résumé trap.
Proved identical CVs sink when labeled female.
Sparked hiring reform across academic institutions.
Exposed bias before the interview even starts.

📌 Dr. Molly Carnes
The strategist who turned exit data into retention.
Created Sea Change to counter STEM attrition.
Bias training boosted lab retention by 25%.
Proved opt-outs are systemic, not personal.

📌 Dr. Virginia Valian
The mathematician who modeled bias to extinction.
Simulated 5% skew erasing women from leadership.
Exposed the “potential vs. proof” promotion gap.
Showed merit works, if you're already in.

📌 Dr. Nilanjana Dasgupta
The experimentalist who rewired bias with visibility.
Proved role models reduce implicit bias by 30%.
Built the evidence base for exposure theory.
Shifted outcomes by changing who’s in the room.

Are you fixing the system or formatting the bias?
Who broke bias for you?

The worst? You don’t even notice. There are 180 biases. Most can be hacked. Some? Trained out. But deletion? Takes design. Meet the designers. 📌 Dr. 

Open article: You lie to you. by Kinga Bali • 2 min read

Game on.
The hidden rules you already play.

Careers aren’t fair. They’re games.
Some rigged. Some strategic.
And most people?
Don’t even know the rules.
Game theory offers a map.
Not wishful thinking, real strategy.

Here are the rules not always see:

1️⃣ Asymmetric information:

Others know more. Or think they do.
In salary talks, this kills your leverage.
Reveal just enough to keep control.

2️⃣ Prisoner's dilemma

Defecting seems smart short term.
But trust beats ego over time.
High-trust teams out-earn lone wolves.

3️⃣ Nash equilibrium

Everyone acts based on others' moves.
You play safe, so do they.
Someone must break the pattern.

4️⃣ Repeated games

One-off wins don’t build careers.
Consistency builds your rep.
They watch how you play, not once, always.

5️⃣  Signaling

Your actions speak louder than words.
Credentials, posture, response time, all signals.
Make them count. Or others will.

Game theory runs the office.
Which rule are you breaking?

Game theory

7 Mistakes in building AI agents.
What slows teams down before they start.

Internal AI tools sound complex.
They don’t need to be.

Anyone can build an agent 
that finds, explains, and answers.
No PhD. No full-time prompt whisperer.

But a few common choices kill momentum fast.

1️⃣ Dumping files, calling it knowledge

Raw content lacks structure or signal.
Fix: Write with headers. Use plain formats. Stay clean.

2️⃣ Skipping use case mapping

Tools fail when shaped around files, not tasks.
Fix: Start with questions users ask often.

3️⃣ Relying on “close enough” answers

“Almost right” feels wrong in most real work.
Fix: Control what counts as a match.

4️⃣ Trusting messy inputs

Outdated, scattered data breaks answers fast.
Fix: Clean before connect. Curate what matters.

5️⃣ Leaving users alone

No guidance leads to silence or mistakes.
Fix: Teach by example. Repeat often.

6️⃣  Ignoring who sees what

Access without rules creates quiet risk.
Fix: Limit inputs. Tag clearly. Audit visibility.

7️⃣ Flying blind after launch

No feedback means no direction.
Fix: Track patterns. Tune inputs. Tighten scope.

Final thought
AI agents don’t need perfect data or expert builders.
They need clean inputs and clear intent.

Most teams stall from clutter, not complexity.
What could change if finding answers felt obvious?

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