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

Devexperts

1. Service Delivery Management:
Ensure compliance with the procedures, instructions, KPIs, and support contract commitments,
Lead an onboarding process of the client during the production launch,
Communicate with the client via telephone, e-mail, or IM to report the current status of the issues,
Oversee the resolution of major incidents, ensuring timely communication and resolution,
Take responsibility for completing the support contract conditions.

2. Process management:
Organize and supervise giving estimations, planning and executing maintenance routine operations & project development tasks in frames of the support team,
Manage the process of investigation of the technical issues;
Manage tasks related to the bug fix of the product.

3. People management:
Manage a project support group in the Maintenance and Support department,
Organize and manage the workload of the team and their backlog.

4. Service Improvement:
Identify opportunities for process improvements and implement best practices to enhance service delivery,
Identify opportunities to enhance the teams' active monitoring and reporting,
Report on key performance indicators (KPIs) with the required stakeholders.

Service Delivery Manager

Philip Morris International

- Lead the operational support for B2C and global communication areas, managing services across 60+ countries in all continents.

- Act as the primary point of contact (SPOC) for key market stakeholders, handling escalations, delivering periodic reports, and aligning expectations to ensure customer satisfaction.

- Drive continuous service improvement by implementing automation solutions, reducing support costs, and optimizing performance for end users.

- Define and monitor critical KPIs including SLA, SLO, aged incidents, MTTR, and NPS to maintain high service standards.

- Enhance Mean Time to Resolution (MTTR) and boost Net Promoter Score (NPS) by applying customer-centric principles and improving support strategies.

- Oversee support for complex solutions involving multiple systems (Salesforce, AWS, SAP, Adobe, Twilio, azure, ...), ensuring timely responses and resolutions.

- Provide functional advice and training for new market onboarding, ensuring smooth transitions and service continuity.

- Manage vendor service quality, establish effective reporting mechanisms, and maintain clear communication with internal stakeholders.

- Lead production support onboarding for new teams, ensuring operational readiness and process alignment.


Key Achievements:

- Reduced incident resolution time by 30% through proactive issue management and automation.
- Improved NPS in 40 pp by implementing feedback loops and customer-first support practices.

Senior Service Delivery Manager

Retail Consult

- Led the Service Management practice, standardizing the SDM processes by developing a customized way of working based on ITIL 4.

- Established a Shared Services structure to provide centralized support for multiple clients, improving efficiency and cost management.

- Managed B2B customer relationships across EMEA and Asia, overseeing account revenue, margins, and customer satisfaction.

- Lead pre-sales efforts for new support accounts, estimating effort and cost, preparing SOWs, and presenting tailored service solutions to potential clients.

- Supervised end-to-end support operations, ensuring incidents, requests, and problems were effectively handled via ITSM tools like ServiceNow.

- Developed and maintained service reports, monitoring KPIs such as SLAs, MTTR, and NPS, and delivering insights to clients.


Key Achievements:

Increased client satisfaction by 25% through enhanced service procedures and KPI management.
Successfully onboarded multiple large-scale clients, ensuring seamless transitions to support.
Implemented a centralized support model for retail and supply chain clients, optimizing operations and reducing downtime.

Head of Service Delivery Management

- Managed a high-profile support account for a major British e-commerce retailer, ensuring a smooth transition from project to support phases.

 Supported testing and post-go-live stabilization, producing detailed service procedures and runbooks.

- Regularly discussed SLAs and generated periodic reports to monitor and optimize KPIs.

- Played a critical role in establishing a Shared Services structure, centralizing support for retail and supply chain clients.

- Collaborated with client stakeholders to ensure service alignment and continuous improvement.


Key Achievements:

- Reduced post-go-live issues by 30% through effective knowledge transfer and documentation.

- Improved operational efficiency for retail clients through centralized support and proactive problem management.

Logic Information Systems

- Established a Shared Services support structure to manage multiple retail clients, streamlining operations and reducing costs.

- Managed the pre-sales process for B2B support accounts, estimating costs, preparing SOWs, and presenting service proposals.

- Provided Oracle Retail support to a travel retail client across Brazil and Italy, focusing on merchandise, fiscal, and planning modules.

- Led a 14-member support team, across Brazil and Portugal, ensuring high-quality service delivery.

- Played a pivotal role in migrating the ITSM tool from Redmine to ServiceNow, improving incident handling and reporting.

- Presented weekly progress indicators to the account manager, showcasing account evolution and service improvements.


Key Achievements:

- Improved client satisfaction by reducing incidents by 15% through process improvements.
- Migrated ITSM tool to ServiceNow, streamlining incident and knowledge management.
- Implemented a support structure for large retail clients, ensuring scalable and efficient service.

Senior Service Manager

- Managed Oracle Retail support transitions, setting up initial support processes and defining team sizes and scopes.

- Established initial knowledge bases and managed the first six months of support for new accounts.

- Played a key role in establishing centralized support processes for multiple retail clients.



Key Achievements:

- Ensured smooth service transitions for multiple Oracle Retail clients.
- Enhanced support scalability through the implementation of centralized knowledge management.

Service Transition Manager

- Delivery Manager for Oracle Retail support and development for Latin America's largest e-commerce company.

- Supported ORMS and ORFM modules, developing enhancements to meet the growing demand in a dynamic market.

- Contributed to the development of a Shared Services support model to handle multiple retail accounts efficiently.


Key Achievements:

- Successfully developed improvements that absorbed a 40% increase in system usage.
- Streamlined support operations for large retail clients, ensuring continuous service improvement.

Service Manager

Wipro Technologies

Three years of experience in Application Support and Maintenance. Experience with management, support, development, and Maintenance of Oracle Retail. I participated in a project supporting Brazil's most prominent e-commerce retailer.

Oracle Retail Senior Consultant

I Help IT Company Leaders Transform Their LinkedIn Profiles into Client Magnets | 7 x LinkedIn Top Voice

I am an accomplished Senior Service Delivery Manager with a strong track record in IT operations management and vendor management. With years of experience leading large, cross-functional teams in the delivery of high-quality IT services, I specialize in optimizing service operations and enhancing vendor relationships to consistently meet and exceed SLA and KPI targets.

In my career, I’ve successfully overseen global IT operations, managing multi-vendor environments and ensuring seamless integration across multiple platforms such as Oracle, Salesforce, and AWS. My expertise in vendor management has been instrumental in negotiating service contracts, driving performance improvements, and implementing cost-saving initiatives through automation and streamlined processes.

A key focus of my work has been aligning service delivery with customer-centric metrics such as Net Promoter Score (NPS) and Mean Time to Resolution (MTTR), ensuring that both operational efficiency and customer satisfaction are prioritized. I have led the development and implementation of ITIL and ISO 20000 service management practices, driving operational excellence and boosting team productivity.

With extensive experience managing global service operations and large teams across multiple regions, I excel in high-stakes environments that require quick decision-making and a focus on results. My ability to deliver consistent service quality, while maintaining strong vendor partnerships, makes me a valuable asset in any organization looking to optimize its IT service delivery.

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