Hi! I'm Stephanie! I'm passionate about building impactful partnerships, enabling businesses to grow, and making sure the social impact community thrives. With over a decade of consistently generating seven and eight figure annual revenue for companies, I understand what it takes to drive success.

Over the last 15 years working with non-profit, government and for profit businesses, I've developed a unique process for building community and generating revenue through a partnership growth mindset. I've been fortunate to develop programs and partnerships that have touched lives across the globe, from India to the United States and beyond. I've created thousands of ecosystems and opportunities that unite governments, educators, employers, and donors to make tangible change.

I believe that together we can achieve great things and am committed to paving the way for a more inclusive, impactful future.

Stephanie Wilson

This weekend I’m spending time at the ISET National Gathering, and I want to name how meaningful it is to be here.

Being in this space is a reminder that workforce development is not just about programs, funding, or outcomes on paper. It’s about people, place, and self-determination. Indigenous communities have been doing this work for generations, building pathways rooted in culture, community knowledge, and lived experience.

What stands out most is the care and intentionality behind the conversations. 

Listening comes first. 
Relationships come before solutions. 
Progress is measured not just by numbers, but by trust, relevance, and long-term impact.

I’m grateful for the opportunity to learn, to listen, and to be present in a space led by Indigenous voices and priorities. 

Moments like this quietly reshape how you think about the work and how you show up when you return home.

#ISETNationalGathering #ISETGathering2026 #Indigenous #WorkforceDevelopment #Community

Thanks to Jelly Academy for organizing such a collaborative space and to Digital Moment | Moment numérique for the opportunity.

Cross-Sector Growth Strategist | $100M+ in Government & Partner Funding Secured | Nonprofit • Tech • Education • SaaS | Founder – The Uplift Collective

The last five days have been full.

Full in the sense of listening carefully, asking questions, and sitting in rooms where people are genuinely trying to figure out how we do this work better.

Across different events, sectors, and conversations, the thread has been consistent.

How do we build systems that actually serve people, not just programs?

How do we prepare for the future of work without losing sight of the humans navigating it right now?

How do we move past performative solutions and into ones that are grounded, inclusive, and durable?

There’s also a reality I’m hearing more clearly now than ever.

Funding is tight. Budgets have been cut. Teams that once sent three or four people to conferences are now sending one. Many are attending virtually, not by choice, but by necessity.

I’m genuinely grateful to conferences and organizers who make that possible. Access matters. So does recognizing that for many organizations, showing up at all right now takes intention and sacrifice.

What that’s changed is the weight of being in the room.

More people are carrying insights back to their teams. 

More responsibility to listen well, synthesize, and translate what matters into action. Fewer spectators. More stewards.

The conversations I’ve been part of haven’t been about trends for the sake of trends. They’ve been about tradeoffs. Priorities. What we protect when resources are constrained.

Spending this time with practitioners, funders, educators, Indigenous leaders, and workforce builders has been a reminder of why this work matters to me.

Not because the answers are easy.

But because when conditions are tight, clarity matters even more.

It was so great to reconnect, meet new people and learn from so many amazing individuals! Until next time friends!
Wendy Baker Darian Kovacs ♾️ Allain Lauzon Mary Stack, BA, CPHR Jasmeen Sidhu, Ph.D. Allan Govender Virginia Gluska Ulrike Bahr-Gedalia Eleanor Hawkins Nausheen Ali Fatima Saadeddine, MBA,PMP,CHRP,ESPT  Jade (Jadelyn) Psutka Allison Bear BComm Barbara Wilson,🍁CCDP® Lisa Stephenson-MBA, CRSP Kelly Johnson

It was unfortunate that so many people had travel cancelled so they couldn't attend after all - I see you!

#Cannexus2026 #ISETGathering2026 #Community #NonProfit #EmploymentServices #Indigenous #Learning

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The Uplift Collective

https://www.upliftcollective.ca/the-partnership-blueprint-five-proven-steps-for-forging-successful-partnerships

the-uplift-collective

I grew up in a small town in rural eastern Ontario.

When I finished high school, I had no idea what I wanted to be. I just knew one thing very clearly. I did not like school the way it was structured. Sitting still. Being talked at. Memorizing instead of doing.

So I took a year off after high school to try to find my way.

It felt uncomfortable. Most of my friends knew exactly what they wanted to do. Everyone was heading off to university. I felt behind. A little lost. Like I had missed some memo everyone else received.

After that year, I still did not know what I wanted to be “when I grew up.” But I did know I needed some form of post secondary education. I needed skills. I needed momentum.

I chose college and enrolled in executive administration.

It was hands on. Practical. I learned a lot. I worked three jobs to cover rent and school. I learned how to manage money because I had to. Those years shaped my work ethic and my sense of responsibility in ways I still carry with me.

After graduating, I got a job working for a municipal councillor. What started as a role turned into six formative years. It exposed me to government, policy, community, and how decisions actually get made. That path eventually led me into the nonprofit world, where I found my purpose. That part of the story is for another day.

For a long time, I was embarrassed to say I did not have a university degree.

I was screened out of jobs automatically because it was mandatory. I questioned myself more times than I can count.

Do I regret not going to university?

Yes and no.

No, because I do not think I would have thrived there at that point in my life.

Yes, because there were real opportunities I never got access to because I did not have that piece of paper.

Both things can be true.

I am sharing this because I see so many people feeling pressure to follow a single definition of success. A single path. A single timeline.

Education matters. Credentials matter. But lived experience matters too.

Learning by doing counts. Working your way through school counts. Taking a longer or different route counts.

There is no one right way to build a career.

Chart your own path. Pay attention to what energizes you, not just what looks good on paper. 

Choose the pathway that works for how you learn, how you move, and who you are becoming.

#CareerPath #Employment #FindYourOwnPath #NonProfit #Education

Photo is me from 2008, still trying to figure things out.

We have a beautiful owl that lives in the trees near our driveway. Usually across the way. Easy to admire from a distance.

Last night, I went out to grab wood for the stove before bed and nearly jumped out of my skin. 

He was sitting right on the front porch railing. Completely still. Just watching. Probably hunting. Definitely unbothered by me.

I froze. Slowly backed into the house. Turned off the lights.

Then I stood in the dining room, in the dark, and watched him for a while.
No noise. 

Just this quiet, unexpected moment of sharing space with something wild and calm and entirely unconcerned with my plans for the evening.

It was incredible.

Sometimes the best moments are the ones that do not mean anything more than exactly what they are.

#Wildlife #NotAPhotographer #CountryLife 

Alyx Parks and Stephanie Martin - I thought of both of you immediately after it happened.

Some of the most valuable parts of my work live in the things I no longer consciously think about.

After years of building, reviewing, defending, and negotiating government budgets, so much of what I do has become instinctive. 

You stop noticing the hundreds of small decisions you make because you have internalized how funders think, where flexibility actually lives, and which details quietly matter most.

Recently, I had the chance to sit with that experience and write it all down. 

Not the big frameworks or the obvious rules, but the small things you only learn by doing the work. 

The wording choices that reduce scrutiny. 

The assumptions that do not need to be over engineered. 

The places where people think they are locked in, but are not.

There was something unexpectedly grounding about translating years of lived experience into something clear and usable for a client. 

Not to impress. 
Not to overcomplicate. 
Just to make the work easier and less stressful for the people doing it.

This kind of work reminds me why I enjoy what I do. 

Helping smart teams feel more confident, more capable, and less constrained by rules that often feel heavier than they actually are.

If you have ever felt weighed down by process or rules that seemed immovable, I promise there is often more room to breathe than it appears.

#BudgetDevelopment #ProposalDevelopment #NonProfit #GovernmentFunding

One thing I think everyone should try at least once is learning someone else’s job.

Not the polished version. The real, day to day work. The setup. The decisions no one talks about. The small things that keep everything moving quietly in the background.

When you work in teams, so much of that effort becomes invisible. Systems run. Tools connect. Processes exist. You rarely stop to think about how much experience and judgment it takes to make things feel that seamless.

Until those people are not there.

And you have to do one small piece yourself.

You realize how many choices live inside what once looked simple.

Lately, I am spending an absurd amount of time learning tools.
Not the exciting kind. The tiny, fiddly ones. Payment systems. Tool connections. Settings I did not even know existed.

Learning to do something you have never done before, or something that was always someone else’s role, builds more than skills.

It builds appreciation.

It changes how you show up the next time.

#ProfessionalDevelopment #GrowthMindset #Entrepreneurship

I really hate getting a no.

Not because I expect everything to work out, but because I put a lot into the work. Time. Thought. Energy. And more than that, belief. I care deeply about what I do and about the teams and ideas behind every proposal. That makes the no’s land harder than people realize.

Early on, I took them personally. Every declined submission felt like a judgment, not just of the work, but of the care behind it. And honestly, I still feel that sometimes. Loving the work makes you more exposed, not less.

What changed over time was not the feeling. It was what I did with it.

I started sitting with the no’s longer. Looking for patterns. Paying attention to what funders questioned, what they ignored, and what clarity actually meant in practice. Every no taught me something I could not have learned any other way.

That learning adds up. Today, more than 40 percent of what I work on gets approved. Not because the no’s stopped hurting, but because I stayed curious instead of shutting down.

Lately, there have been a lot of yes’s for clients. And I feel genuinely excited for them every single time. 

I also know the no’s will come again. They always do.

When they do, I will feel them. And then I will learn from them.

Because caring about the work is not a weakness. It is the reason the yes’s mean so much when they arrive.

#GovernmentFunding #BusinessDevelopment #ProposalDevelopment

I’ve learned that authenticity isn’t about having a fixed identity. It’s about staying honest as things shift.

I have spent years being the reliable one. 

The person who could hold a lot, absorb uncertainty, and keep moving anyway.

That works. Until it does not.

Because eventually you realize how much energy it takes to live up to a version of yourself that was built for other people’s expectations.

Letting go of who you think you are supposed to be does not mean losing drive or ambition. It means releasing the pressure to look a certain way while you are building something real.

Authenticity is not a reveal or a brand decision.

It is a daily choice to show up aligned, even when that alignment keeps evolving.

And that choice changes everything.

#BeTrueToYourself #Authenticity #Leadership #NonProfit #StartUp

One of the best parts of a panel on AI and the next generation at the AI Policy Conference yesterday was that it did not try to wrap anything up neatly.
Instead, it named the complexity.

AI is already embedded in education, work, and daily life. Young people are forming relationships with systems that shape how they think, learn, and see themselves. Institutions are trying to respond in real time, often without data, shared frameworks, or room to pause.

At the same time, many of the loudest predictions about jobs and disruption have not fully materialized. Change is happening, but unevenly. Slowly in some places. Abruptly in others.

What emerged was a quieter but more useful set of questions.

How do we equip young people to be creators, not just users?

How do we protect without pretending we can stop what is already here?

How do we build literacy, judgment, and human skills that remain valuable no matter how tools evolve?

There was no single answer, and that felt right.

This is long-term work. It requires humility, collaboration across disciplines, and a willingness to sit with uncertainty without defaulting to fear or hype.

If there was a through-line, it was this: the future will be shaped less by the tools themselves and more by how thoughtfully we choose to integrate them.

Panel participants:
Justin Hendrix, Tech Policy Press
Shingai Manjengwa, Mila - Quebec Artificial Intelligence Institute
Namir Anani, P.Eng., ICTC-CTIC
Laurent Charlin, Mila - Quebec Artificial Intelligence Institute
André Côté, The Dais at Toronto Metropolitan University 

Thankful to Mila - Quebec Artificial Intelligence Institute for access to the AI Policy Conference and for putting together such a great event!

#AIPolicy #YouthAndAI #Talent #GovernmentofCanada

Creativity is my word for 2026.

Creativity in how I approach work, rest, and everything in between.

Creative problem solving.
Creative contracting.
Creative time off.
Creative experiences.

Creativity is what lets you ask better questions instead of accepting the default answer. It is how you find options where others see constraints. It is how you design work and life in ways that actually fit.

In 2026, the only box is that there is no box.

More room to experiment.

More permission to rethink how things are done.

More trust in the idea that there is almost always another way.

Here is to a year of curiosity, flexibility, and building something that feels as good as it works.

#Focus #GrowthMindset #HeresTo2026

I never thought I would be an entrepreneur.

In fact, quite the opposite. I was convinced I did not have the “it” that founders and leaders are supposed to have. 

I wanted stability. The person who imagined working for others my whole life and being perfectly content doing that.

And for a long time, that made sense.

What I did not realize then is that entrepreneurship does not always look like taking big risks. Sometimes it looks like taking responsibility. For your values. For your time. For the kind of work you want to put into the world.

I did not wake up one day wanting to start something of my own. I arrived here slowly, through experience, through necessity, and through a growing understanding of what I needed in order to feel grounded and aligned.

Entrepreneurship was not a goal. It was a response.

And maybe that is the part we do not talk about enough. Not everyone sets out to build something. 

Some of us end up here because staying the same stopped being an option.

Did you ever picture yourself doing what you are doing now?

#Entrepreneuship #CareerFocus

Woke up to a weirdly satisfying thing this morning.

I’ve had a watch since July that tracks something called body battery. 

I’ve seen it end the day at five more times than I’d like to admit.

Today I woke up at one hundred. First time ever.

That’s it. That’s the post.

#WeekendVibes #QuietWins #SlowDown

READ THE QUOTE IN THE IMAGE!

Now read it again!

Who. You. TRULY. Are

NOT the version that feels easiest to explain.

NOT the version that keeps everyone comfortable.

NOT the version that fits neatly into a role you learned to play well.

Being yourself is not about being loud or visible all the time.
It is about being honest. With your values. With your limits. With what actually matters to you now, not who you were five years ago.

I have learned that the more energy you spend trying to meet expectations that are not yours, the dimmer everything feels. The work. The relationships. Even the wins.

The moments where things start to open up again usually come from a small shift. 

Saying no when you would normally say yes. Choosing alignment over approval. 

Letting yourself evolve without needing to justify it.

Your light is not something you manufacture.
It is something that shows up naturally when you stop hiding parts of yourself to fit the room.

And the right rooms do not require you to dim it in the first place.

#BeYourself #BeAuthentic #ISeeYou #Leadership #Teamwork #BetterTogether

One thing I keep coming back to in conversations lately is timing.

A lot of organizations are doing the right work. Strong ideas. Capable teams. Real demand. And still, things are not moving the way they expected.

Not because they are doing something wrong.

Because the system itself is in motion.

Calls are delayed or quietly reworked.
Programs get folded into other initiatives.
Priorities shift before anything ever reaches a public intake.

From the outside, it can feel confusing. Like you misread the landscape or missed a signal. In reality, the rules are still being rewritten.

This is where patience becomes strategic.

Not passive patience. Active patience. The kind where you keep preparing, strengthening, and paying attention while resisting the urge to force momentum.

A lot of the work right now is helping teams sit with that uncertainty without spiraling. Adjusting plans without abandoning them. Staying ready without trying to rush a system that is not ready yet.

Sometimes the smartest move is not to push harder, but to hold steady until the timing catches up to the work.

#FundingStrategy #GovernmentFunding #NonprofitLeadership
 #StrategicPlanning #SystemsThinking

Join an upcoming FREE workshops to better prepare for what's coming!  https://lnkd.in/e_KQt4jg

Stop beating yourself up!!!

Don’t think you do that?
Here’s what it actually looks like in real life:
- Replaying a conversation on the drive home.
- Second-guessing a decision you already made with the information you had.
 - Assuming a mistake says something about who you are, not just what happened.
 - Feeling like you should have known better, been faster, clearer, stronger.

Sound familiar?

We’ve been taught that self-criticism equals accountability.
That if we’re hard on ourselves, we’ll improve faster.
That pressure produces excellence.

But more often, it just produces exhaustion.

Beating yourself up usually shows up when expectations are high, outcomes are uncertain, and you’re carrying more responsibility than anyone sees.

It’s a signal.
The problem is that self-criticism rarely makes us better.
It just makes us smaller.

So how do you stop when you catch yourself doing it?

1️⃣  Name what’s actually happening.
 Instead of “I screwed this up,” try “This didn’t go the way I hoped.”
 Facts calm the nervous system. Stories inflame it.

2️⃣ Separate intent from outcome.
You can have good intentions and imperfect results at the same time.
Both can be true. Only one needs fixing.

3️⃣  Ask one forward-looking question.
Not “What’s wrong with me?”
But “What’s the next small adjustment I’d make if this came up again?”
That’s it. No spiral required.

If you’re trying to be a good person and you try to do the right thing, that's all that matters.

Growth doesn’t require punishment.

It requires honesty, rest, and the willingness to keep going.

And if you’re reading this thinking, “This sounds like me” then it probably is.
You’re not alone, and you’re not doing it wrong.
Be a little kinder to yourself today.

#BeKind #PersonalGrowth #FallingNotFailing #SelfImprovement #Leadership #Teamwork

You may not control the events that happen to you
 but you can decide not to be reduced by them.

That choice is one I see leaders, founders, and builders struggle with more than almost anything else.

Because a setback can quietly turn into a story about who you are.
A hard moment can shrink your confidence if you let it.
One decision, one missed opportunity, one tough season can start to feel permanent.

But it isn’t.

You’re allowed to be impacted without being defined.

You can acknowledge what hurt without letting it harden you.

You can learn from something without carrying it as proof that you’re not enough.

Resilience isn’t pretending things didn’t affect you.

It’s choosing not to let them take more than they already have.

If you’re in the middle of something heavy right now, this is your reminder

You’re still standing.
You’re still growing.

And YOU get to decide what this chapter means next.

#NonProfit #Leadership #StartUp #GrowthMindset #Resilience #NonProfitLeadership

I watched a video and could not stop thinking about how early we learn to edit ourselves.

Kids start out loud, curious, unapologetic. They ask strange questions. They take up space. They are fully themselves without checking the room first. And then, slowly, they learn when to quiet down. When to blend in. When to stop standing out.

What stayed with me is how familiar that feels in the professional world.

At some point, many of us learn the same lesson.

Tone it down.

Stick to the playbook.

Do not be the odd one out.

Over time, that sparkle does not disappear. It just gets managed. Contained. Brought out only when it feels safe or appropriate.

And yet, the work that actually moves things forward is almost always shaped by people who think differently. 

The ones who question defaults. 

The ones who see patterns others miss. 

The ones willing to sound a little strange before they sound right.

If you have ever felt yourself shrinking to fit a role, a title, or an industry norm, consider this a reminder. 

That part of you is still there. It has just been waiting for space.

BRING BACK THE SPARKLE!!

Step off the well worn path.

Nothing meaningful has ever been built by people who only followed the herd.

https://lnkd.in/emWvkws2 
His Youtube Channel to give him a follow: https://lnkd.in/ehb-AESd [I couldn't find the above video on the channel]

#BringBackTheSparkle #BeYourself #BeAuthentic

If you have ever hit a word limit halfway through answering a funder’s question, this is for you.

One of the hardest parts of writing proposals is answering every part of a funder’s question while staying inside a tight word or character limit.

Especially when appendices or extra attachments are not allowed.

You cannot skip components. You also cannot explain everything.

So when space is tight, here is a rule that helps.

Every sentence must do more than one job. Ideally three.

A strong sentence should:

 1 describe what you are actually going to do

 2 signal eligibility and alignment to the funder’s priorities

 3 imply milestones, outcomes, or credibility

If a sentence only does one of those things, it is a candidate for removal or compression.

This is how you stay compliant and persuasive without running out of room.

It is not about writing less.

It is about making every sentence work harder.

If you have ever hit a word limit and wondered what to cut, start here.

#ProposalDevelopment #GovernmentFunding #NonProfit #Charity

Growth is what you do with what happens.

That is how better decisions get made over time.

#WednesdayWisdom #GrowthMindset

One thing I wish more people understood about funded projects is how messy they usually are behind the scenes.

From the outside, a successful contribution agreement looks clean.

A defined plan. 
A neat timeline. 

It gives the impression that everything is stable and predictable.

That is almost NEVER the case.

Most funded projects are delivered while markets are shifting. 
Project timelines wobble. 
Plans get pulled forward or pushed back. 
Teams make trade offs in real time, often without the luxury of perfect information.

What funders are really assessing in those moments is not whether risk exists. It is how it is understood and managed.

Strong applications and delivery organizations are not the ones pretending everything is fine. 

They are the ones that show judgment.
An ability to adapt without overreacting. 
A plan that can flex while still holding together.

There is a skill in knowing what to surface and what to hold steady. 
In demonstrating resilience without amplifying uncertainty. 
In showing that the work will continue even when conditions are not ideal.

Funding success is rarely about having a flawless story.
It is about proving you can keep moving when the story changes.

#Resilience #NonProfit #GrowthMindset #StartUp #GovernmentFunding

Every conversation about AI sounds exciting -until you try to make it work inside a real business.Most leaders see the potential.What they don’t see is a clear starting point.So they stay stuck - not because they’re doing nothing,but because they’re doing too many things that don’t move the needle.→ Teams wasting hours on repetitive work that should’ve been automated months ago→ Customer support drowning in simple questions while real issues wait in line→ Sales reps managing CRM chaos instead of relationships→ Marketing pushing out content that doesn’t convert→ Projects that “pilot forever” but never scale→ Systems that don’t talk to each other - so people become the integration layer→ Leaders flooded with vendor pitches, buzzwords, and no clear playbookThe result?Rising costs. Missed opportunities.And that quiet, uncomfortable feeling that competitors are moving faster.It doesn’t have to be this way.With the right AI and automation strategy, you can:Pinpoint the highest-impact areas to automateReclaim hundreds of hours across teamsScale without adding headcountThat’s where my work begins - with an AI Automation Audit.A hands-on, practical look at your workflows, tech stack, and decision loops to uncover what’s possible right now.No jargon. No hype. Just a clear starting point and a roadmap that actually works.Because AI only matters if it improves judgment, strengthens teams, and removes friction from work.That’s been my practice for over 25 years - scaling businesses, repairing broken processes, and delivering change that lasts.Here’s what that looks like in real life:👉 Replacing fragile systems that can’t support growth👉 Scaling untapped opportunities hiding in plain sight👉 Applying AI and data to sharpen decisions, not decorate dashboards👉 Leading transformations that make daily work simpler for the people who actually use the systemsI’ve done this across the spectrum - from shoestring budgets to million-dollar programs.What I bring:✅ Calm and clarity when things grow complex✅ A focus on value, not features✅ Data that informs, never dictates✅ Teams that perform - without burning outIf you’re done with the AI noise and ready for results that stick, let’s talk.

Ranjana Sharma

Tech didn’t invent new human behaviors.
It just found a way to scale the old ones… beautifully, efficiently, profitably.

Human drives → Monetized at scale

There are seven drives baked into being human.
Not learned. Not taught. Wired.
Each one of us carries them.

Lust became swipe velocity with Tinder.
Gluttony became frictionless consumption Uber Eats and Door Dash.
Greed got wrapped in “democratization” with Robinhood.
Sloth learned autoplay with YouTube.
Wrath found comment sections in Reddit.
Envy got an algorithm with TikTok.
Pride? Well… we optimized that one for engagement in Linkedin.

Tech didn’t create these behaviors.
It built business models around them.

Apps didn’t just serve our drives.
They packaged them.
Gamified them.
Optimized them.

And the better they got, the more balance we lost.

Endless scrolling.
Frictionless spending.
Outrage on demand.
Comparison as a daily habit.

Not because people are weak.
Because the systems are designed to win.

Now add AI to the mix.

AI doesn’t introduce new incentives.
It removes the last bit of resistance.

What already worked will work faster.
Cheaper.
At scale.
And harder to escape.

We’re already seeing it.
From hyper-personalized manipulation
to tools that normalize deepfake sexualization.

This isn’t a distant future.
It’s a direction we’re already moving in.

And that’s the real risk.

The most dangerous thing about AI isn’t intelligence.
It’s efficiency pointed in the wrong direction.

Which means the real question isn’t
Can we build it?

It’s
What parts of human nature are we choosing to accelerate… and who’s responsible for the brakes?

Because technology reflects us.
AI just removes the delay.


♻️Repost if it sparked a thought.
🔔 Follow Ranjana Sharma for reflections on growth, leadership, and evolving in the age of AI

Image Credit : Michael Lee

Turning AI Hype Into Results That Stick | AI Strategy • Automation Audits • Scaling Smarter, Not Louder

Most of us don’t know what we’re good at
until we notice what comes easier to us than to others.

Everyone has strengths.
Some are obvious.
Others stay hidden because they don’t look like the “standard” version of success.

You can call them natural gifts.
Talent.
A unique kind of intelligence.

I think of it as your inner wiring.

It took me years to recognize mine.

It was always there -
in how I approached work,
how I framed problems,
how I connected ideas.

People often called me “creative.”
I didn’t fully own it.
It felt vague. Almost uncomfortable.

What I didn’t see then was this:
my upbringing, experiences, and life choices had shaped how I think.
They wired me to see patterns others missed.

For a long time, that difference frustrated me.
I felt like I had to work harder -
to bring people along to where my thinking already was.

But that tension changed me.

It sharpened my ability to persuade.
To communicate clearly.
To translate ideas so others could act on them.

Somewhere along the way, I stopped resisting it.
I leaned into it.
And it became a strength I could rely on.

Here’s what I’ve learned:
Every one of us has a uniqueness-
a way of seeing the world,
approaching problems,
and making sense of complexity.

That difference isn’t something to fix.
It’s something to cultivate.

The goal isn’t to blend into the mainstream.
The goal is to grow into the version of yourself
that only you can be.

♻️ Repost if this inspired you today
🔔 Follow Ranjana for practical thinking on leading with clarity, empathy, and impact in an AI-powered world.

Knowing your value changes everything.
But first, you have to know it.

A shoe is just a shoe
until my son steps into it.

Then it becomes confidence.
Posture.
A quiet belief that he belongs wherever he’s about to walk.

That’s how value works.
A role is just a role.
A paycheck is just a number.
A “final offer” is usually just a pause.

Until you know what you bring.

Most people wait for permission that never comes.
They negotiate from fear.
Of being difficult. Of losing the deal. Of asking one question too many.

But no real change happens until you realize
you’re holding more cards than you think.

So how do you actually know your value?

• Track outcomes, not effort
Effort feels noble. Outcomes get paid.
What changed because you showed up?

• Follow the pain
Value lives where problems are expensive, loud, or avoided.

• Replace yourself on paper
If you vanished tomorrow, what would it cost to replace you
in money, time, momentum?

• Notice where you’re pulled in
Unplanned meetings. Sticky problems. Decisions waiting on you.
That’s the market voting quietly.

• Separate value from approval
Being liked doesn’t create leverage. Being useful does.

• Name it before someone else does
If you don’t articulate your value, someone else will
and they’ll do it in budget language.

Negotiation isn’t aggression.
It’s awareness.

Sometimes growth doesn’t require a louder voice.
Just a steadier one.

Know your value.
Then step in like the fit was never in doubt.

♻️ Repost it for someone who needs the reminder.
🔔 Follow Ranjana Sharma for more clarity on work, value, and negotiating with confidence.

I stopped hiring for skills long time ago.
Started hiring for character.

Now, when everyone has access to the same AI tools…
when technical work gets automated…
character becomes the only moat.

Here's what I look for:

1️⃣ Curiosity over certainty
They ask "what are we missing?" instead of "I know this."
They wonder about edge cases.
They question assumptions others accept.

2️⃣ Judgment when data isn't enough
AI can process information.
It can't weigh competing values.
They make calls when perfect answers don't exist.

3️⃣ Comfort being wrong publicly
They say "I was wrong" without deflection.
They update their thinking in real time.
They see pivots as progress.

4️⃣ Empathy in system design  
They ask "who gets hurt if this breaks?"
They consider second-order effects.
They design for humans, not just efficiency.

5️⃣ Clarity under complexity
They translate technical depth into business impact.
They find the signal in organizational noise.
They explain "why this matters" to any audience.

6️⃣ Resilience without rigidity
They adapt strategy while keeping principles.
They evolve methods without losing direction.
They stay flexible on tactics, firm on values.

7️⃣ Ownership beyond their code
They care about what happens after deployment.
They follow up on promises made in meetings.
They measure success by outcomes, not output.

Skills → teachable
Tools → learnable  
Character → everything else

♻️ Repost if you're rethinking how you build teams
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Image credit: Mike Leber

Skip the TL;DR trap
Ask what actually matters

Most people aren’t bad at using AI.
They’re just asking it to do the wrong job.

“Summarise this.”
“Give me the key points.”
“TL;DR please.”

That’s not thinking.
That’s outsourcing reading.

AI isn’t valuable because it shortens text.
It’s valuable because it changes how you think about the work.

What actually gets results 👇

Instead of asking AI to summarize, ask it to:

👉 Extract the decisions hiding in the noise
“What are the 5 insights here that would change a real decision?”
“What should we stop doing based on this?”
“If I had to decide today, what would matter most?”

👉 Turn information into action
“Translate this into a 5-step plan with owners and measurable outcomes.”
“What should happen in the next 30, 60, 90 days?”
“What can be done this week vs what needs leadership approval?”

👉 Surface what everyone is assuming
“What must be true for this to work, and what breaks if it’s wrong?”
“Where are we relying on best-case scenarios?”
“What are we assuming about customers, teams, or timelines?”

👉 Compare opposing views
“Where do these perspectives align, conflict, and when is each valid?”
“What would a skeptic say about this plan?”
“How would this look if I were responsible for cost instead of growth?”

👉 Filter through a role lens
“What matters here to a leader vs a marketer vs an engineer?”
“What would success look like to finance vs operations?”
“What would my boss care about that I might be missing?”

👉 Pull out the contrarian take
“What would smart people disagree with, but shouldn’t ignore?”
“What part of this feels uncomfortable but true?”
“If this fails, what will we wish we had questioned earlier?”

👉 Find leverage points
“Where could small actions create outsized impact?”
“What’s the one change that would unblock three others?”
“What’s the lowest-effort move with the highest downstream effect?”

This is the shift most professionals miss.

AI isn’t here to save you time.
It’s here to upgrade the quality of your thinking.

The teams getting real value aren’t faster typists.
They’re better question-askers.

♻️ If this helped, repost it.
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Image Credit : Charlie Hills 🦩

Everyone wants “AI agents.”
What business owners need is confidence.

Confidence that:
decisions are owned
risk is contained
governance isn’t an afterthought

That’s why Agentic AI isn’t about intelligence.
It’s about architecture.

This diagram isn’t showing tools.
It’s showing operating models.

And one pattern consistently reduces risk and builds trust:
Hierarchical agents with explicit Human-in-the-Loop gates.

Why?

Because:
one planner owns the goal
specialists execute
humans decide where it matters

No diffused accountability.
No runaway autonomy.

Most AI projects don’t fail because models aren’t weak.

They fail because no one decided:
who owns decisions
where judgment stays human
what earns autonomy over time
The safest path forward isn’t maximum automation.

It’s earned autonomy.

Start with hierarchy.
Add human gates.
Expand deliberately.

Agentic AI doesn’t remove responsibility.
It forces clarity.

♻️ If this helps you think differently, repost it.
If you’re building AI for the real world, 🔔 follow along.

Most leadership playbooks were built for a world that moved predictably.

Clear hierarchies.
Stable markets.
Enough time to analyze, decide, and correct.

That world rewarded certainty.

This one doesn’t.

Today, leaders are navigating:
• Faster cycles
• Noisier signals
• AI-shaped decisions
• Ambiguity that doesn’t wait for consensus

And experience alone no longer guarantees good judgment.

The shift isn’t about becoming more technical.
Or chasing the latest AI tool.

It’s a mindset shift.

From having the answers
→ to asking better questions

From control
→ to clarity

From authority based on tenure
→ to trust built through judgment

The real work of leadership has moved upstream.

It now lives in:
• Designing decision environments, not just making decisions
• Choosing where speed helps and where it harms
• Creating systems where people can think, not just execute
• Using AI to extend judgment, not outsource it

Tools don’t make leaders faster.
They make judgment visible.

And that visibility is uncomfortable for outdated models of leadership.

But essential for the future.

Yesterday’s leaders were rewarded for certainty.
Today’s leaders are rewarded for sense-making.

Not because leadership got harder.
But because the world got faster, noisier, and less predictable.

Those who adapt don’t just survive change.
They shape it.

If this resonates, Part 2 goes deeper into governing AI without slowing innovation.

Save this if you’re rethinking what leadership actually requires now.

♻️ Repost if you believe leadership needs updating, not defending.
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Your energy is finite.
Your worry is infinite.

Most people spend their days fighting battles they can't win.
Wrestling with forces beyond their control.
Then wonder why they're exhausted before lunch.

The discipline of letting go isn't surrender.
It's strategy.

Every minute you spend obsessing over uncontrollables is energy stolen from what actually moves you forward:

What you can't control:
↳ Politics and regulatory shifts
↳ Market volatility and economic turbulence  
↳ Your competitor's next move
↳ Industry disruption timelines

What you absolutely can:
↳ Your authenticity in every interaction
↳ The quality standards you maintain
↳ How you respond to uncertainty
↳ Where you direct your mental energy
↳ The relationships you choose to build

Energy management is decision management.

Every worry you release creates space for focus.
Every uncontrollable variable you stop wrestling with frees up bandwidth for impact.

The noise never stops.
Your participation in it is optional.

What uncontrollable are you ready to stop fighting?

♻️ Repost if this shifted your perspective
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Most AI failures aren’t technical.
They’re conceptual.

This graphic shows the pattern I see over and over again in boardrooms, steering committees, and “AI task forces.”

Leaders aren’t getting AI wrong because they’re careless.
They’re getting it wrong because the language sounds familiar… and behaves very differently.

A few of the most expensive misunderstandings I see 👇

👉 AI Strategy isn’t buying the right tool.
It’s redesigning how decisions get made.
Miss that, and pilots stall quietly after launch.

👉 Automation isn’t replacing people.
It’s removing friction.
Focus on replacement and you miss augmentation. And morale takes the hit.

👉 AI Agents aren’t smarter chatbots.
They’re autonomous digital workers.
Treat them like Q&A tools and you cap their value before they start.

👉 Accuracy isn’t certainty.
It’s probability with confidence.
Expect perfection and you introduce risk where judgment should live.

👉 Data readiness isn’t volume.
It’s cleanliness, access, and trust.
Dirty data doesn’t just slow AI down. It teaches it the wrong lessons.

👉 Adoption isn’t people logging in.
It’s people changing how they work because the tool exists.
Without behavior change, AI is just a shiny new cost center.

👉 ROI isn’t only cost savings.
It’s better decisions, new revenue, and strategic advantage.
Efficiency alone is table stakes.

None of this is academic.
Every one of these misunderstandings shows up later as:
– “Why isn’t this scaling?”
– “Why didn’t this move the needle?”
– “Why are people frustrated?”

AI doesn’t fail because models are dumb.
It fails because expectations are misaligned.

If you’re leading AI right now, the real work isn’t choosing tools.
It’s choosing the right definitions before the organization builds around the wrong ones.
Most AI failures aren’t technical.
They’re conceptual.

♻️ Repost if this helps put words to what you’re seeing inside your organization.
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Most AI strategies don’t fail because the models aren’t powerful enough.
They fail because ownership never shifts.

In most initiatives, we built AI like a factory line.
Input goes in.
A model runs.
An output comes out.

It’s efficient. Predictable. Safe.
And it’s where most businesses still operate.

But Agentic systems change the game.

They don’t just suggest.
They decide.
They act.
They observe outcomes and adjust.

That’s not optimization.
That’s execution.
Ownership changes and trust becomes THE problem.

And execution introduces a question most strategies quietly avoid:
Who owns the decision when AI takes action?

Without clear ownership, autonomy isn’t innovation.
It’s RISK. 

That’s why the conversation can’t stop at agents.
It has to include control, governance, memory, and learning.

Not to slow things down.
But to make autonomy safe.

This is the shift most AI strategies miss.
Not because it’s hard to build.
But because it’s hard to lead.


If this resonates, ♻️ repost it so others can join the conversation.
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Most goals don’t fail because they’re unrealistic.
They fail because the ground underneath them is soft.

We set ambitious targets.
Revenue. Growth. Transformation. Even “do better this year.”

The ladder is strong.
The intent is clear.

But the footing?

Processes are unclear.
Decisions depend on who’s in the room.
Knowledge lives in people’s heads.
Progress requires heroics instead of flow.

So every step up feels unstable.
Not because people aren’t capable -
but because the system underneath them can’t carry the weight.

This isn’t just about AI.
It’s about leadership.

Goals are directional.
Systems are structural.

Goals tell people where to climb.
Systems determine whether the ladder stands or sinks.

If you want progress that doesn’t wobble under pressure,
stop asking people to climb harder.

Build firmer ground:
– Clear ownership
– Repeatable workflows
– Decisions that survive turnover
– Standards that don’t bend with stress

Because when things break,
it’s rarely the ambition that fails.

It’s what it was standing on.

♻️ Repost if this reframed how you think about goals
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Clarity doesn’t slow progress.
It prevents the wrong kind of speed.

Most AI conversations don’t fall apart because people aren’t smart.
They fall apart because people are using the same words to mean different things.

When someone says “we’re using AI,” that could mean:
– a chatbot drafting copy
– a model answering questions on company data
– an agent taking actions across systems
– or a half-built experiment someone tried once and abandoned

Same label. Very different realities.

That’s what this reference is meant to help with.

These 12 essential AI terms aren’t here to impress anyone or turn leaders into technologists.
They’re here to give teams a shared starting point - so discussions about risk, cost, capability, and value don’t drift into assumptions.

This is the kind of material that helps when:
• you’re evaluating vendors and everyone sounds convincing
• a team says “the model can do that” but can’t explain how
• decisions are being made faster than understanding is catching up

It’s not about knowing everything.
It’s about knowing what question you’re actually asking.

If AI is now part of how work gets done - even indirectly - having a common reference like this reduces friction, rework, and misalignment.

📌 Save this so it’s easy to come back to when a term shows up in a meeting or deck.
♻️ Repost if you think shared language is a prerequisite for good decisions, not a nice-to-have.
🔔 Follow me for practical thinking on leading with clarity, empathy, and impact in an AI-powered world.

Most companies don’t fail at AI because of the tech.
They fail because they skip the middle.

They buy tools.
Run a few pilots.
Announce they’re “AI-first.”

And then… nothing really changes.

This infographic from Alex Barády  nails what actually works.
Becoming AI-native isn’t a single leap. It’s a sequence.

Here’s the path most leaders underestimate 👇

Step 1: Understand the new paradigm
AI today isn’t just automation.
It spans:
• Vibe-coding for fast experimentation
• AI-assisted work for productivity gains
• Agentic systems that plan, act, and improve

Different levels. Different risks. Different use cases.
Treating them as “the same thing” is how confusion starts.

Step 2: Train internal AI champions
This is where transformation quietly succeeds - or dies.

Not everyone needs to code.
But everyone needs:
• The right mental model
• Clear KPIs for AI value
• Guidance on when to trust AI vs when to pause

AI maturity is a people problem before it’s a platform problem.

Step 3: Apply AI to every role (not just engineering)
AI belongs across the full product and operations cycle:
• Planning
• Research
• Prototyping
• QA
• Delivery

When AI stays siloed with “the tech team,” scale never happens.

Step 4: Change the way work actually flows
This is the hardest part and the most ignored.

AI doesn’t just speed up tasks.
It changes:
• Who does what
• When humans decide
• Where agents act autonomously

New workflows. New handoffs. New accountability.

That’s what “AI-native” really means.

Not more tools.
Not louder announcements.
A different operating model designed on purpose in 2026.

📌 Save this if you’re building an AI roadmap
♻️ Repost if this helps you explain AI transformation without the hype
🔔 Follow Ranjana Sharma for practical, human-first AI insights that actually stick

It starts innocently.

Someone has a deadline.
A deck which needs to prepared and delivered before weekend.
A doc that won’t write itself.
A spreadsheet that’s staring back… unblinking.

Upstairs, the conversation sounds like this:
“We should pause.
Run surveys. Evaluate.
Make sure everyone feels comfortable with AI.”

Downstairs, someone thinks:
“I just need this done before dinner.”

So they open ChatGPT.
No announcement.
No transformation program.
Just… help.

Ten minutes later, the work is finished.

That’s Shadow AI.

Not secrecy.
Not defiance.
Just humans doing what humans have always done:
finding the fastest way through friction.

While leadership debates readiness, surveys sentiment, and plans “Phase 1”…
the work doesn’t wait.

So teams quietly:
• Write drafts faster
• Analyze data without asking
• Automate the boring parts
• Ship work that would’ve taken days

Not because they’re reckless.
Because friction has a cost.

Here’s the uncomfortable truth:
AI adoption isn’t failing because people resist change.
It’s failing because governance is moving slower than gravity.

And when that happens, AI doesn’t disappear.
It goes underground.

If you want AI to be safe, scalable, and aligned:
Stop treating it like a rollout.
Start treating it like a work behavior that already exists.

The choice isn’t:
Adopt AI vs don’t.

It’s:
Lead it intentionally
or inherit it accidentally.

♻️ Repost if you’ve seen this play out.
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A concept everyone should know about:
The Paradox of Knowledge.

For a long time, I believed knowledge was the barometer for success.
The more I knew,
the better I’d become,
the more valuable I’d be.

That hasn’t quite turned out to be true.

After spending nearly two years going deep into AI, I feel like I have more to learn than ever.
It feels unsettling sometimes. 
And that’s ok. 

When you start, everything feels simple.
Tools look straightforward. Concepts feel manageable.
But the deeper you go, the more you realize how much sits beneath the surface.

That feeling didn’t last.

As I went deeper, AI stopped being about models and tools and started becoming about systems.
Data quality. Trade-offs. Incentives. People. Decisions.

The work didn’t get louder.
It got more thoughtful.

That’s the paradox of knowledge.

Early learning brings confidence.
Deeper learning brings humility.
And somewhere in between, real capability starts to form.

From the outside, expertise looks like clarity.
From the inside, it’s mostly learning how to navigate higher-quality confusion.

Here are a few mindset shifts that changed how I approach gaining new expertise - especially in fast-moving fields like AI:

First: learning isn’t about collecting information.
It’s about repetition, refinement, and reflection.
Understanding fewer things more deeply and applying them in real situations.

Second: expertise looks boring up close.
It’s built by making the same decisions, just a little better each time.
Most people chase variety. The best ones chase precision.

Finally: stay a student, even when you’re teaching.
The moment you think you’ve mastered something, growth slows down.

Mastery, I’ve learned, is a bit of a myth.

You often have to act without full clarity.
That’s just reality.

In fast-moving fields like AI, this matters.

The moment you think you’ve mastered it, you stop seeing what’s changing.

The leaders who do well aren’t the ones with all the answers.
They’re the ones willing to keep learning, even when they’re already teaching.

Just remember: The more you learn, the less certain you may feel but the more capable you become.

Happy learning.


♻️ Repost if this made you uncomfortable (in a good way)
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Credit for original idea and Carousel Chris Donnelly

Mastery is a bit of a myth.

At first glance, this project looked like it failed.

Nothing launched.
Nothing was announced.
Nothing visibly changed.

From the outside, it felt like time was lost.

But below the surface, something very different was happening.

The work that took the longest wasn’t the model.
It wasn’t the tool.
It wasn’t even the use case.
It was the unseen work.

Data issues that would have broken the system later were uncovered early.
Bad automation was avoided before it became expensive.
Teams aligned on what was real, not what was hoped for.
False certainty was challenged.
Rework was never created.
Trust stayed intact.

None of this was in the original project plan.
All of it became the foundation.

This is where many AI projects get mislabeled as “failures.”

Because we measure progress by launches.
And ROI by what’s visible.

But in reality, the most valuable work often happens below the waterline.

The real return wasn’t speed.
It was stability.
It was future scale without fragility.

Instead of asking, “Why do AI projects fail?”
A better question might be:

Are we planning for the foundational work that determines whether they ever succeed?

That’s where the real ROI lives.

♻️Repost if you believe this shift will change how we plan for AI projects

🔔 Follow Ranjana Sharma for reflections on growth, leadership, and evolving in the age of AI

🔹 Leadership didn’t stop evolving.

It got more consequential.

From certainty
→ to sense-making
From control
→ to clarity

But that was only the visible part of the transition.

This is the harder one.

Because once AI enters decision-making, leadership stops being about what you decide
and starts being about what you allow, encourage, and reward.

That’s governance.
Not the bureaucratic kind.
The leadership kind.

Here’s where many organizations stumble.

They set goals.
But forget guardrails.

They optimize outcomes.
But skip the conversation about values.

They move fast.
Without deciding what must never be broken along the way.

So Part 2 zooms in on what leadership actually requires in an AI-augmented world.

1️⃣ Set guardrails, not just goals
Ambition without boundaries doesn’t scale innovation.
It scales risk.

Guardrails clarify what success cannot cost.
Trust. Privacy. Fairness. Human recourse.

2️⃣ Decide justice upfront
What feels “fair” in a meeting room
can feel very different to someone affected by an automated decision.

If AI gets it wrong:
– Who owns the error?
– Who can challenge it?
– Who fixes it?

Those answers shouldn’t come after deployment.

3️⃣ Use AI to extend thinking, not outsource it
The best leaders aren’t faster because of tools.
They’re clearer because judgment becomes visible.

AI exposes assumptions.
It doesn’t replace responsibility.

4️⃣ Lead through systems, incentives, and trust
Culture won’t save you if incentives reward speed over sound decisions.
And policy won’t help if people don’t feel safe raising concerns.

True leadership hears.
But it also steers.

The goal isn’t to control every AI outcome.
That’s impossible.

The goal is to shape the systems and incentives guiding those outcomes.

Yesterday’s leadership experience taught us how to decide.
Today’s leadership requirement is knowing how decisions happen at scale.

And that’s the real transition map.

• If Part 1 (in the link below) was about mindset, Part 2 is about responsibility.
• Save this if AI governance is now on your leadership agenda.
• Repost if leadership needs updating, not defending.



♻️ Repost if you believe leadership needs updating, not defending.
🔔 Follow Ranjana Sharma for practical insights on leading with clarity, empathy, and impact in an AI-powered world.

Forget the $5,000 AI strategy bootcamps.
Forget the exclusive executive roundtables.
Forget waiting for your board to approve consultants.

The frameworks that matter most are already public.
Most leaders just don't know where to look.

Save this for the future reference.

Strategy isn't about having insider access.
It's about knowing which questions to ask.

Here are 9 resources that will sharpen how you think about AI leadership:

1. Stanford's AI Index Report → the data that shapes Silicon Valley's long-term bets
Link: https://lnkd.in/e9SjAx5y

2. MIT's AI Readiness Assessment → diagnostic questions most organizations skip
Link: https://lnkd.in/ecTJDtuY

3. BCG's AI Governance Templates → what board oversight actually looks like in practice
Link: https://lnkd.in/eDPcNfmq

4. McKinsey's AI Transformation Cases → pattern recognition across failed and successful deployments
Link: https://lnkd.in/e3iEU2qd

5. Harvard Business Review's Change Management Series → why 70% of AI initiatives stall at adoption
Link: https://lnkd.in/edW_FxHb

6. World Economic Forum's Responsibility Frameworks → the compliance landscape before it becomes regulation
Link: https://lnkd.in/ePVBrcCK

7. Brookings Institution's Policy Research → early indicators of what's coming for your industry
Link: https://lnkd.in/ep9dSDsW

8. IEEE's Ethical AI Standards → technical guardrails translated for business decisions
Link: https://lnkd.in/eYYGvDrg

9. Partnership on AI's Enterprise Library → candid post-mortems from companies that got it wrong first
Link: https://lnkd.in/efVrWskc

These aren't just reports.
They're intelligence that shapes decisions at the highest levels.

___

If I had 30 minutes to prepare for an AI strategy discussion:

• Stanford's executive summary → understand the competitive landscape
• MIT's readiness questions → audit where you actually stand today
• BCG's governance checklist → know what sophisticated oversight requires
• McKinsey's failure patterns → anticipate where resistance will emerge
• HBR's adoption research → plan for the human side of transformation

The difference between AI leaders and followers?
Leaders know what questions to ask before problems become crises.

___

♻️ Repost if this changes how you think about AI strategy.

🔔 Follow Ranjana for practical thinking on leading with clarity, empathy, and impact in an AI-powered world.

🚨 Breaking: Salesforce just stepped inside ChatGPT.

Pause on that for a second.
Not connected to.
Not integrated with.

Inside.

This isn’t a shiny feature drop.
It’s a line in the sand for where enterprise AI is actually going.

Now picture a day in the life.

8:37 AM.
A seller opens ChatGPT. Not Salesforce.

They ask:
“What needs my attention today?”

The answer isn’t generic advice or motivational fluff.
It’s grounded in live Salesforce data.

Deals slipping.
An account heating up.
A renewal quietly at risk.

ChatGPT isn’t guessing.
It knows the business.

10:12 AM.
Before a customer call, the seller asks for a quick account brief.

Not a template.
Not best practices.

Actual context:
• Past conversations
• Pipeline history
• Open risks
• Next-best actions

They walk into the call prepared without touching five different tools.

11:04 AM.
The call ends.

“Update the opportunity.
Log notes.
Adjust the forecast.”

Done.
Inside the conversation.

No tab switching.
No CRM clean-up guilt at 6 PM.

This is the breakthrough.

Not because ChatGPT got smarter.
But because it finally knows where work lives.

Enterprise leaders have said:
“AI is impressive… but it doesn’t understand our data, our rules, our reality.”

That was the blocker.

Large language models are great at language.
They are terrible at governance, workflows, and accountability.

Salesforce stepping inside ChatGPT collapses that gap.

It turns a consumer assistant into an enterprise-grade, action-taking agent.

From a bigger lens, this is the real signal:
Salesforce is positioning itself as the last mile of enterprise AI.

As models become interchangeable, value shifts to the layer that connects AI to:
• Trusted data
• Business logic
• Real outcomes

That’s the layer that wins.

This also tells us something important about the agentic era.

It’s not about picking the “best” model.
It’s about how fast insight turns into action, safely.

And distribution matters.

Agentforce doesn’t force teams into new tools.
It shows up where work already happens.
Slack. Apps. Voice. And now ChatGPT.

That’s how adoption actually scales.

Net-net?

This is how AI stops being a demo.
And starts being how revenue teams actually work.

Quietly seismic.
And we’re going to feel the aftershocks.

♻️ Repost if this feels like a turning point for enterprise AI.
🔔 Follow Ranjana Sharma for reflections on growth, leadership in the age of AI

Claude can now read your entire Excel file formulas, tabs, dependencies and answer questions about it.

This changes who can do serious spreadsheet work.

Most of the world still runs on spreadsheets.
Budgets. Forecasts. Pricing. Headcount. Planning your kid's soccer fundraiser.

Excel isn't glamorous but it's where decisions actually happen.

Now Claude (Anthropic's AI) works 𝘪𝘯𝘴𝘪𝘥𝘦 Excel.
Not next to it.
Not pasted in from a chat window.
Inside the file you're already using.

That changes how people can use AI, especially non-technical folks.

What this means in real life

Claude can now:
• Understand how tabs relate to each other
• Follow formulas across cells
• Help build or explain models without breaking them
• Spot issues when numbers don't add up

Translation:
You don't need to be an Excel wizard to do serious work anymore.

You can ask things like:
• "Explain what this sheet is actually doing"
• "Build a version of this model with different assumptions"
• "Where could this logic break?"
• "Turn this mess into something clean and readable"

And it answers 𝘸𝘪𝘵𝘩 𝘢𝘸𝘢𝘳𝘦𝘯𝘦𝘴𝘴 𝘰𝘧 𝘵𝘩𝘦 𝘴𝘱𝘳𝘦𝘢𝘥𝘴𝘩𝘦𝘦𝘵, not generic advice.

Why this matters (beyond productivity hype)

The real shift isn't speed.
It's that AI is moving into 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀, not just conversations.

When AI lives where work happens in Excel, email, docs, tools. It becomes useful, not distracting.

One important reality check

Claude is powerful.
It's not magic.

You still need humans to:
• Decide what assumptions matter
• Check logic before trusting outputs
• Apply judgment at the "last mile"

AI accelerates thinking.
It doesn't replace responsibility.

Who should pay attention

If you:
• Work in business, ops, finance, marketing, or planning
• Spend time cleaning spreadsheets instead of thinking
• Feel like Excel runs your life (because it does)

This is worth learning.

Not to become "AI-driven."
But to spend less time wrestling cells and more time making better decisions.

If you want, I can break down simple ways to start using Claude in Excel no finance degree required. Drop a comment - EXCEL or DM me.

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The Battle

Stephanie Wilson

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Stephanie Wilson's LinkedIn Performance

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Performance ScoreStephanie Wilson's LinkedIn Performance