I Help Corporate Professionals Gain Career Clarity & Fulfillment | Founder @Amplify Your Home | Global AI Tax Copilot Strategist @EY

Don't be fooled by my appearance. Quiet, Asian, tiny girl.

In the last decade, I've...

Successfully navigated the corporate giants: Goldman Sachs, PwC, Deloitte and EY.

Built communities, tax and financial models, and automations. (Excel wizard here)

Empowered employees to own their damn careers,

Challenge their norms to do something special.

That's when Problems become Opportunities,

Strategies into Actions.

You are not Alone.

Ready to redefine your career? Let's make it happen.

Mary Fung

Accenture and Snowflake just formed a joint business group. 5,000+ certified consultants dedicated to AI and data transformation.

That's not a partnership announcement. That's a statement about where enterprise AI is heading.

Reading between the lines:

- The big consultancies are betting hard on data infrastructure as the AI bottleneck
- 'AI transformation' is becoming 'data transformation with AI capabilities'
- If you don't have your data house in order, no amount of AI magic will save you

What this means for enterprise buyers:

The consulting giants are building massive practices around making AI actually work. They're not selling AI hype anymore - they're selling the boring stuff. Data quality. Governance. Integration. Infrastructure.

They learned something from the last 2 years: Executives buy AI demos. But they pay for data cleanup.

If Accenture is deploying 5,000 people to this, ask yourself: Is your organization investing anywhere close to proportionally?

Own Your Damn Career | Founder @Amplify Your Home | Head of Synthetic Data & Simulations @EY

10 AI Predictions for 2026:

1. Gemini will quietly become the default AI model — not because it's best, but because it's baked into Google Workspace and enterprises buy whatever comes with the contract.

2. AI agents will be the buzzword of 2026, but 90% of enterprise "agents" will just be fancy if-then workflows with a chatbot wrapper.

3. Middle management will shrink faster than anyone expected. If your job is routing information between people, start upskilling now.

4. LinkedIn will be flooded with AI slop, which will make authentic human writing easier to spot and more valuable.

5. The companies that win with AI won't have the best models — they'll have the cleanest data and fastest approval pathways.

6. Most "AI transformations" announced in 2025 will be quietly walked back, rebranded, or buried in footnotes.

7. Copilot will be on every enterprise desktop, but 80% of employees will use it the same way they use Excel — poorly and rarely.

8. The Chief AI Officer title will peak and then quietly disappear because nobody figured out what it was supposed to do.

9. Prompt engineering will stop being a job title and become a baseline skill, like knowing how to Google.

10. The people who actually ship AI in 2026 will be the same ones who shipped software in 2016 — builders who know that technology is 20% of the problem.

Everyone keeps saying, “AI needs better foundations.”

That’s true.
But it’s not the part people think.

KPMG isn’t warning about missing tech.
They’re warning about missing discipline.

Most enterprises want AI to move fast
on top of systems that were never designed to be trusted.

Bad data.
Unclear ownership.
Processes built for humans to patch gaps with judgment.

So when AI breaks, leaders don’t ask:
“Why was this workflow fragile to begin with?”

They say:
“AI isn’t ready.”

AI doesn’t fail in enterprises because it’s too powerful.
It fails because it refuses to hide the mess underneath.

Foundations aren’t glamorous.
They don’t demo well.
They don’t win internal applause.

But without them, AI just scales dysfunction faster.

The companies that actually win with AI won’t be the loudest adopters.
They’ll be the ones willing to do the unsexy work first:
clarify ownership, clean data, redesign workflows, define accountability.

Everyone else will keep running pilots —
and blaming the tech when reality shows up.

Most companies don’t hire talent.
They hire job descriptions.

And then they’re shocked when they end up with average people doing average work.

Cursor does the opposite.
They don’t ask “What role do we need?”
They ask “Is this person undeniable?”

If the answer is yes, they bend the org around them.
They don’t wait for headcount approvals.
They don’t debate leveling.
They don’t hide behind process.

They move.

Because:
> Elite talent is rarer than clean org charts.
> Process is cheap. People aren’t.

Most companies optimize for order.
The best ones tolerate chaos to secure leverage.

If you hire roles first, you get replaceable people.
If you hire people first, they create roles you didn’t know you needed.

That’s how you build an org of superstars.
Not by perfect hiring processes but by having the courage to recognize greatness
and act before it’s gone.

Goldman’s CEO said AI can now do 95% of an S-1 in minutes.

Everyone keeps asking what happens to the jobs.

That’s the wrong question.

The real question is:
What is the 5% that still matters?

It’s not formatting.
It’s not drafting.
It’s not models, footnotes, or precedent decks.

The 5% is:
• deciding what risk actually matters
• knowing what to leave out
• framing the story regulators and investors will believe
• understanding where this deal breaks under pressure
• making judgment calls no template can defend

The 95% was always execution theater.
The 5% was always the job - it was just hidden behind process and headcount.

AI didn’t remove human value.
It stripped it down to the part you can’t fake.

If your role was built on producing the 95%,
you weren’t senior...you were insulated.

Now the insulation is gone.

What’s left is judgment, taste, and accountability.
And that’s the part most people were never trained for.

That’s the real disruption.

Users don’t need Copilot to be visionary.
They need it to be boringly correct.

Once it earns trust, then it can become transformative.

But this is exactly why Copilot keeps disappointing:
the people building it aren’t the people living in Word, Excel, Outlook, and PowerPoint all day.

They don’t feel the cost of a small error.
They don’t feel the “I now have to double-check everything” tax.
So the product ships features… before it ships trust.

And Satya stepping in as PM won’t magically fix that.

This isn’t a leadership-attention problem.
It’s a proximity problem.

Until the builders are forced to live in the workflow and be judged on accuracy, not demos
Copilot will keep being impressive… and optional.

Trust first.
Then transformation.

How to Position Yourself for AI-First Roles:

> Stop learning tools. Start solving problems. Anyone can take a ChatGPT course. Few people can articulate how AI solved a specific business problem with measurable results.

> Document everything you build. That workflow you automated? That analysis you accelerated? Screenshot it. Write it up. Your future employer can't see what you don't show them.

> Get uncomfortable with ambiguity. AI roles live in the gray zone between 'definitely possible' and 'completely impossible.' If you need clear requirements to function, this isn't your path.

> Learn to speak two languages. Technical enough to evaluate AI capabilities. Business enough to translate them into ROI. The people who bridge this gap are absurdly valuable.

> Find the AI skeptics. The person in your company who thinks AI is overhyped? Befriend them. They'll show you every gap in your thinking and make your pitches bulletproof.

> Build a public track record. LinkedIn posts about AI projects. GitHub repos with experiments. A portfolio site showing what you've built. Hiring managers are tired of 'AI enthusiasts' with nothing to show.

> Apply before you're ready. The AI field moves so fast that job requirements are wishlists, not checklists. If you meet 60% of the requirements, you're qualified. They'll teach you the rest.

Most “agentic AI” projects fail for the same reason most corporate transformations fail:
people mistake motion for progress.

McKinsey looked at 50 real agentic AI builds.

The failure wasn’t the models.
It wasn’t the prompts.
It wasn’t the talent.

It was ego.

Teams built impressive agents instead of fixing broken workflows.
They layered AI on top of chaos and called it innovation.

AI isn’t limited by capability.
It’s limited by imagination.

We already have models powerful enough to solve problems most companies haven’t even defined yet.

The gap isn’t technical - it’s structural.
It’s the lack of domain context, product packaging, and change management that turns potential into adoption.

Most enterprises don’t need “better AI.”
They need AI that speaks their language - built around real workflows, real UX, and real ownership of change.

That’s why the next wave won’t come from another foundation model.
It’ll come from domain-specific agents - vertical copilots that combine deep expertise with flawless execution.

The real unlock isn’t general intelligence.
It’s the ability to pour capital into problems that were never scalable before.

And the only thing left standing in the way isn’t the tech -
it’s the willingness to use it.

5 Things I Learned Implementing AI at Enterprise Scale:

1. Your data problem is bigger than you think. Every executive says 'our data is pretty clean.' It never is. Plan for 60% of your timeline to be data work.

2. The pilot trap is real. Successful POCs die in production because nobody planned for security reviews, compliance checks, and the 47 stakeholders who need to approve everything.

3. Change management eats AI for breakfast. The technology works. The humans resist. Budget 3x more time for training, communication, and handling the 'but we've always done it this way' crowd.

4. Start with the boring use cases. Everyone wants the sexy AI chatbot. The real ROI is in automating the mind-numbing document processing that costs you 200 hours/week.

5. Your AI strategy needs an AI exit strategy. Models change. Vendors pivot. Build for portability or you'll be rewriting everything in 18 months.

i won't be surprised if this number 10x by now

Craig Davis

An award-winning Senior Customer Service Representative with 12+ years of experience. Helping hospitality companies create amazing customer experiences that drive 7-figures in annual growth.

I help content creators on LinkedIn by leaving value-driven comments.

My first job was working as a Janitor at the Greater Allen Cathedral of New York in June 2006. I enjoyed learning how to serve people, do a job, and learn about its mission.

I volunteer to serve Thanksgiving food, Christmas Gifts and attend church conferences.

Those experiences translated to my first full-time job, working at a casino in October 2011.

Out of over 1,000+ employees with no phone experience, I became the first-ever Employee of the Month in the Call Center for Outstanding Customer Service.

My former manager wrote in 2015:

"His dedication to excellence and delivering above and beyond what is required makes him a solid addition to any organization." - Elba Batista, Former Customer Relations Manager at Resorts World Casino New York City.

Working in hospitality taught me how to be patient, empathetic, and caring.

My goal is to become a Customer Success Associate at a hospitality tech startup in New York, NY. Here are three reasons why:

1) To start, I want to make a career change that I will be happy with for a long time.

2) Throughout my career, I’ve become an expert at uncovering people’s desired outcomes to help create amazing customer experiences.

3) You get my skills and relevant customer experience to bring a hospitality tech startup in New York, NY.

Why a hospitality startup? To bring insights from working in hotels.

I create content on LinkedIn that focuses on personal branding, adding value, and sharing webinar takeaways. I like to visit Farmer's Markets in New York.

To see webinar takeaways from May 27th, 2020 to now, click "See all" on the featured tab.

To follow my content, follow my hashtag: #CraigNotes

If you are open to how we can work and help each other, please send an InMail or LinkedIn Message.

Specialties: Customer Experience | Hospitality Expert | Account Management | Communication | Relationship Management | Data Analysis | Project Management | Customer Engagement | Relationship Building | Market Research | Customer Retention | Salesforce.com | Customer Support | Troubleshooting | Data Entry | Technical Support

Technical Skills / Systems: | Trello | OS365 / Microsoft Office - Word, Excel, Sharepoint, Powerpoint | Google Suite - Docs, Sheets, Slides | SQL | Slack | Hubspot | OnQ | Meridian | HotSoS | MARSHA | Guestware | Canva | Zoom

Senior Customer Service Representative

•	Facilitated exceptional customer experiences through utilizing data within the hotel data 
        management system, resulting in $5K of extra daily revenue.

•	Boosted customer testimonials by handling customer inquiries during the nomination which 
        resulted in winning the 2019 Certificate of Excellence award from TripAdvisor for the hotel.

•	Upsell ~$900k on an annual basis for upgrades in service packages and room upgrades 
        consistently by educating customers on incentives and rewards.

7 LinkedIn challenges I’m taking on in 2026

(Here's how to completely transform your networking)

1. I will ask for specific help when I need it

- Start your post with: "I need your advice on this."
- Share what you tried. Be straight to the point.
- Ask why you need help. (Not clear? Rewrite)

2. I will personalize my comments

- When commenting, share your personal experience.
- Write how you felt or what the post reminds you of.
- Even if you think no one will read it, still share.

3. I will go on a call with 1 connection monthly

- Check connections you haven't spoken to.
- In your DM, mention a recent post you loved.
- Finally, ask to speak for 15 minutes. Follow up.

4. I will write at least 1 LI Recommendation per quarter.

- Reach out to your 1st degree connections.
- Think of how they added value to you and thank them.
- Send a draft. Talk about the situation, with results.

5. I will reflect on my comments to improve them

- Look at the last 10 comments you wrote.
- Think of how you can make your comments better.
- Ask yourself: "Does my comment expand on the post?"

6. I will connect with at least 1 new person per day

- Check posts from 2nd and 3rd-degree connections.
- Check their content and send a personalized request.
- Offer to support their posts. Check their posting time.

7. I will write 7 thank you cards to send in person
- Find a store or shop online to buy blank cards.
- Let your connections know you are sending a card.
- Ask where to mail it to and thank them for their help.

This list is important to help you build real relationships.

Let's make 2026 the year of quality networking!

(Save and Repost this ♻️ to help someone start 2026 strong.)

P.S. Which of these (1-7) will you start first in 2026? Happy New Year!

👉 Click my hashtag #CraigNotes for more of my posts.

Helping beginners navigate LinkedIn and stand out with proven tips and strategies | 10+ years on LinkedIn, known for writing "really good comments" that convert

This is easily overlooked in LinkedIn comments:

Making the author of the post look "great".

Often times, we fall into this trap of trying to say the best thing. Something that'll attract likes and replies.

But we forget about the author of the post.

My simple formula is:

1. Always tag + acknowledge the author of a post
2. Compliment them.

Why should you do this? Because...

1. You're valuing the author's work
2. You're not making it all about yourself
3. It shows "authenticity" to your audience

In a nutshell...

Don't make your comment look good.
Make the author look great too!
It's an excellent combination!

Sounds "good"? :)

(Save and repost this to help others make authors of posts look great.♻️)

P.S. Do you compliment a post's author in your comments? Or do you just leave your thoughts?

👉 Click my hashtag #CraigNotes for more of my posts.

Working hard towards your New Year’s resolution?

Or is momentum starting to fade?

Here's the truth:

Most people have resolutions that fade before the month ends.

In my opinion, the best way to stay the course and to accomplish your goals is to start smart. To do this you:

Take a goal.
Break it down.
Make it realistic.

For example: my goal is to comment on at least 20 new people's posts. Daily.

So I:

-Set aside time to comment daily
-Ensure my commenting time is uninterrupted
-Have a list of 20 accounts that I want to comment on

This means I have to step out of my comment zone, too.

And I have to build a habit. One that I can handle.

But the good thing is the more you do it, the better you get.

Carry this momentum forward and make each day count so you can ensure that you meet your goal.

Let's make 2026 a great year for stretching ourselves!

(Save and repost this so someone can start 2026 well.♻️)

P.S. What new habits are you starting to build this year?

👉 Click my hashtag #CraigNotes for more of my posts.

The best thing about the new year?

You get a chance to work on you.

Wrote LinkedIn Articles for 5 years since December 2020.

The theme for 2026 is in the article.

(Save and repost this.♻️)

P.S. Do you make New Year's Resolutions?

👉 Click my hashtag #CraigNotes for more of my posts.

Tuesday, 8:05am January 6th, 2026 Mom is resting. She made breakfast for the family. Baby bro is in his room. Right now, it's partly cloudy. It's 35 d

Open article: My theme for 2026 by Craig Davis • 2 min read

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The Battle

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Craig Davis

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The Battle

Mary Fung

Craig Davis

Followers

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Engagements

Likes

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);}Mary Fung's LinkedIn Performance

Performance ScoreCraig Davis's LinkedIn Performance

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Performance ScoreMary Fung's LinkedIn Performance