My path has moved through startup environments, NGO mission-driven work, Big four rigor, and executive leadership in listed companies. Over two decades and six countries, I kept encountering the same friction: systems promise transformation, yet decisions still lag behind data, leaving finance teams buried in reconciliation, constrained by tools, and unable to fully step into the role of true business partners.

I stopped asking how to make these tools work better for me and my team, and started asking why they were built this way in the first place.

I have stepped away from the corporate world to found a tech startup focused on the core inefficiencies of financial decision-making. I’m trading certainty for conviction, bringing the discipline of a seasoned finance leader into the grit and ambiguity of building something new.

As a proud dad, this shift is personal. It’s about choosing exploration over safety, and modeling the courage it takes to create real-world impact. I’m learning deeply, building quietly, and documenting the journey from executive to founder.

Leaving a well-paid, stable corporate career to start something from scratch often looks irrational from the outside.

The reactions from my network are pretty consistent:
That’s brave. Are you sure this is the right move? You are crazy… but I get it (Not the first time I have taken a non-orthodox path 😉)

And honestly, they are not wrong.

- Early-stage founder life is not glamorous.
- There’s no clear plan or guarantees.
- No safety net hidden behind a job title.

What there is:
- Learning at a speed that no corporate role ever forced on me
- Doubting myself more than I would like.
- Having conversations that stretch how I think
- A strange mix of excitement, fear, energy, and purpose


Stability matters, but so does curiosity and betting on yourself.

No risk, no fun. No discomfort, no growth.

If this resonates and you are open to chatting, exchanging ideas, or simply sharing experiences...feel free to reach out.
Good conversations often lead to interesting things!

Mohamed Ali BELHAJ

Results-driven finance executive with a keen business acumen and a proven track record in providing insights to drive organizational growth and enhance profitability. Specializing in business partnering, strategic planning, financial management, and core process improvement, I am dedicated to catalyzing company development through strategic financial initiatives.

My diverse professional journey includes impactful roles in a dynamic Tech Startup, a Big Four audit firm, a listed Technology Company, and a prominent Global NGO. Presently, I serve as the Head of Commercial Finance at Electrolux North America, a leading global player in the home appliances industry.

With a broad international perspective, I have successfully navigated and contributed across various geographies, including Tunisia, Oman, Egypt, India, Sweden, and the United States. My commitment to excellence, coupled with a comprehensive skill set, positions me as a strategic leader capable of driving financial success in a global business landscape.

VP Finance | Building at the intersection of AI & Finance

At some point, comfort becomes more expensive than risk.

- A steady paycheck can cost you your dreams.
- A predictable title can cost you your potential.
- A “safe” path can cost you your future.

The next chapter won’t be built on certainty. It will be built on belief, discipline, and uncomfortable action. 
Documenting this season of growth here.

Twenty years in finance, across industries and geographies, gives you pattern recognition.
Not just about what works, but about what never really changes.

Over time, I have seen new systems implemented, processes re-engineered, and now AI promise transformation.
Yet the same friction remained.

- Decisions still trail data.
- Judgment still sits outside the tools meant to support it.

That gap has become impossible to ignore.

At some point, experience turns into responsibility.
You either accept the limitations or explore what it would take to move beyond them.

I am choosing exploration.
Learning deeply & Building quietly.

Sharing the thinking as it evolves...

Curious if others have noticed the same gap.

Being an early-stage founder means wearing too many hats. All the time.

One hour I’m thinking about product and architecture. The next I’m pitching and collecting feedback, trying to put a team together, or wrapping my head around legal docs.

Context switching is real and multitasking is exhausting. There is often that feeling that I’m doing everything at once and nothing perfectly.

But there is another side to it.

The pace of progress keeps me going. Watching something move from idea to reality, even in small steps, creates momentum. Small wins compound!

You don’t need to be an expert in everything. You need to learn fast, prioritize hard, and stay comfortable being uncomfortable.

Early-stage building isn’t about balance. It’s about forward motion.

The biggest risk for finance right now isn’t AI adoption. It’s adopting it the wrong way.

AI will probably drive the biggest shift this profession has ever seen.
Not because it’s faster, but because it forces us to rethink how decisions are made.

Even the most capable models won’t be enough on their own.
The real differentiator will be applying a new approach: integrating unstructured data, building context, and continuously factoring in external signals as business conditions evolve.

And yes, I beleive autonomous finance is coming.
Not “hands-off finance,” but platforms that continuously monitor business health and proactively surface insights and actions with humans firmly in the loop.

Done right, this shift:

- Pulls finance away from PPT decks and Excel maintenance
- Frees teams to focus on trade-offs, foresight, and value creation
- Elevates finance into a true business partner role

If we adopt AI passively, we will just close the books faster and push data to dashboard tools. If we shape it intentionally, we’ll improve the quality of decisions.

The future of finance won’t be manual, and it won’t be mindless automation.

It will be context-aware, autonomous systems guided by human judgment.

Curious how others are thinking about this shift, where do you see the biggest opportunities (or risks)?

After years in FP&A, I noticed a specific pattern that separates the good from the great.
It wasn’t their Excel skills. It wasn’t their speed.
It was something much more valuable. ...

Here are the 5 competencies I consistently see in top-tier FP&A talent:

1️⃣ Business Judgment over Technical Perfection
The best FP&A professionals understand what truly matters to the business.
They know when “directionally right” beats analytically perfect.

2️⃣ Turning Data into Insights & Decisions
Models don’t create value, but decisions do.
Strong FP&A connects financial signals to clear options, trade-offs, and recommendations.

3️⃣ Comfort with Ambiguity
High-impact FP&A doesn’t wait for perfect data.
It challenges assumptions, works with uncertainty, and continuously adapts as reality changes.

4️⃣ Influence Without Authority
FP&A rarely owns decisions, but it often shapes them.
The best teams frame insights in a way that resonates with operators, not just finance peers. That's when you see true business partnering behavior in action. 

5️⃣ A Forward-Looking Mindset
Top FP&A professionals spend less time explaining the past and more time stress-testing the future, through scenarios, sensitivities, and external signals.

Here’s the shift we’re entering:

These competencies are quickly becoming table stakes for FP&A.

What will differentiate finance teams going forward is how these skills are amplified by AI:
• Continuous signal detection beyond structured data
• Faster scenario exploration
• Less manual work, more judgment and foresight

AI doesn’t replace FP&A expertise, it compounds it. I still see hesitation and resistance across part of my network, but I’m convinced that those willing to learn, experiment, and adapt will benefit most over the long run.

The future of FP&A won’t be defined by better spreadsheets, it will be defined by how well humans and AI think together.

(Human Judgement + Business Context) * AI = Future of FP&A

Most companies don’t have an FP&A problem.
They have an FP&A expectation gap.

FP&A (Financial Planning & Analysis) is often described as forecasting, budgeting, and variance analysis.

That’s not wrong. It’s just incomplete.

At its best, FP&A is where strategy meets execution.

- It’s the finance function closest to how the business actually runs.
- The place where ambition turns into real trade-offs.
- Where leaders stop asking “what happened?” and start deciding “what do we do next?”

When FP&A is weak, a few things happen fast:

- Strategy turns into storytelling instead of execution
- Leadership debates whose numbers are right instead of what to do next
- CFOs get pulled back into fire drills instead of forward-looking decisions

You don’t get a truly strategic CFO office without a strong FP&A function underneath.

But FP&A’s impact is not just about talent or experience.
It’s also about capability.

- Give FP&A fragmented systems and manual workflows, and you get hindsight.
- Give it the right tools, trusted data, and the mandate to partner with the business, and you get foresight.

That’s when FP&A stops explaining the business and starts helping build it.

I’m spending a lot of time diving into current AI progress and its impact. And everyone keeps asking the same question:

“Is AI a bubble?”

My humble take is: Yes, and that’s not a bad thing.

Every major shift that truly changed the economy started as a bubble.
Railroads. Electricity. The internet.

Is it overhyped? Absolutely.
Is it transformational? Also yes.

What makes this moment different from bubbles like the 2008 financial crisis is why it exists.

That crisis was driven by leverage, greed, and financial engineering detached from real productivity.
AI is driven by something else entirely: a genuine step-change in how work gets done and problems are solved at scale.

This feels a lot like a gold rush.
Most prospectors won’t strike gold. Many startups won’t survive, especially LLM wrappers chasing fast takeoff and unreasonable valuations.

But the infrastructure will.
The tools. The standards. The platforms and a New generation of entrepreneurs.

They will outlive the hype and quietly power the next decades of economic progress through companies that solve real problems, improve human productivity, and earn trust over time.

Lately, I have been listening to a set of podcasts that i beleive deliver real value. Clear thinking, first-principles, and lived experience.

If you’re a founder, business leader, or AI enthusiast, these 8 are worth your time:

1) a16z Podcast - Andreessen Horowitz
Deep dives into AI, startups, regulation, and future tech, straight from operators and investors actually shaping the ecosystem.

2) The Founder Initiative – Adam O'Donnell
Honest founder conversations about building companies from the ground up, real & practical.

3) EU VC – @Andreas Munk 
A sharp European lens on venture capital, founders, and what it really takes to build global companies from Europe.

4) The Diary of a CEO – Steven Bartlett
Raw conversations on leadership, ambition, failure, and growth, often more reflective than tactical, but powerful.

5) Founders – David Senra
Timeless lessons from history’s greatest founders. Probably the best reminder that fundamentals still matter.

6) In Good Company – Nicolai Tangen
Exceptional long-form conversations on capital allocation, leadership, and long-term thinking.

7) FP&A Unlocked – Paul Barnhurst
Where modern finance, decision-making, and technology actually meet, very relevant in an AI-driven world.

8) The Tim Ferriss Show – Tim Ferriss
Still one of the best formats for unpacking how high performers think, decide, and build leverage.

Andreessen Horowitz

Helping Founders Pitch B2B Buyers

Founder of Steven.com

Founder at Founders Podcast & David Senra

Chief Executive Officer at Norges Bank Investment Management

Helping FP&A Professionals provide value to their businesses | Founder of The FP&A Guy | Host of 3 popular Finance podcasts | Microsoft MVP | Cofounder The FP&A Hub | AFM Certified

Author of 5 #1 NYT/WSJ bestsellers, Creator of COYOTE card game with 300M+ viral video views (coyotegame.com), Tim Ferriss Show podcast with 1B+ downloads

Davos is usually about macro, geopolitics, and polished narratives.

This year felt different.

Very tech-heavy & very CEO-heavy.
And AI was clearly at the center of gravity.

There was political noise (and the Greenland moment), but almost every serious conversation circled back to the same question: what happens next with AI?

Listening to multiple interviews, one thought stuck with me, we are probably closer to AGI-level capabilities than most systems and organizations are ready for.

The real debate was not if, but speed:

- how fast models evolve,
- when models start training the next generation of models,
- and whether anything around us can adapt at the same pace.

Another layer that kept coming up was energy and infrastructure.
Data centers, power constraints, and even building compute in space.

Big Tech seems to be planning for the after. Google hiring economists to think through post-AGI societal and economic impact isn’t theoretical, it’s preparation.

This moment feels critical for Europe and without accelerating on energy, compute, talent, capital, and adoption, Europe risks falling into a de-facto AI duopoly between the US and China, losing not just competitiveness, but long-term digital and economic sovereignty.

World Economic Forum

World Economic Forum

FP&A is not falling behind because it lacks automation.
It’s falling behind because demand has outgrown the model.

AI is raising expectations on the CFO office. Not to report faster, but to decide better, in real time, under volatility.

Here’s the hard truth many teams feel:

- FP&A is overloaded.
- Even after years of automation, FP&A teams are still reactive and stretched thin. As Gartner puts it, the current trajectory is simply not sustainable.
- The classic promise of automate more so FP&A can partner more is starting to break.

In a VUCA world, decision demand is growing faster than FP&A capacity ever will.

The real shift isn’t more automation. It’s how FP&A delivers value.

Leading teams are moving from an “internal consulting” model to capability diffusion:

- Decision support embedded in tools
- Leaders more self-sufficient
- FP&A focused on the hardest, highest-impact decisions

This is where AI actually matters teh most, not as a speed boost, but as part of purpose-built platforms aligned to real FP&A workflows.

The CFO question is not “how do we automate FP&A?”
It’s: how do we scale decision-making without burning out the team?

A few hours ago, Ursula von der Leyen made an announcement at the WEF that could  change the game for Europe’s startup ecosystem.

EU Inc.

A simple idea with massive implications:
- Register a company in any EU member state
- Fully online
- In 48 hours

If you have ever tried to found, fund, or scale a startup across Europe, you know the reality: fragmented rules, slow incorporation, legal complexity, and administrative friction that kills momentum.

This is transformative.

EU Inc. directly tackles one of Europe’s biggest structural disadvantages: the administrative nightmare of operating across multiple member states with different frameworks.

Done right, this can:
- Lower the barrier to Entrepreneurship
- Accelerate cross-border scaling
- Make Europe more attractive for founders and investors
- Help build a strong tech hubs that can compete with Silicon Valley and China

For founders at the very beginning of the journey (myself included), this is incredibly energizing. Speed matters. 

If EU Inc. delivers on its promise, it won’t just reduce paperwork. It will unlock ambition.

Excited to be building in #Silicon_Valhalla, #Stockholm

President of the European Commission

Last week, a friend asked me a question every AI founder eventually wrestles with:

“If GPT-5 is even better… why won’t OpenAI just replace your product?”

Fair question.

Here’s what building in finance is teaching me.

The dirty secret of corporate finance:
90% of a finance team’s time isn’t spent on strategic analysis.
It’s spent reconciling data across fragmented systems, each with its own logic, timestamps, and exceptions.

A general-purpose LLM can write beautiful SQL.

But it can’t tell you that:

- “final numbers” aren’t actually final until the Controller signs off on the 8th business day
- there’s always a manual adjustment for that one legacy contract
- Q4 budgets include a placeholder everyone knows will change

That context doesn’t live in a prompt. It lives in the scar tissue from a hundred broken month-end closes.

This is where the real moat sits:

-> Deep domain architecture, not the model itself.

Adoption will not be driven by “using AI for finance.” But by understanding finance deeply enough to know:

- which integrations actually matter (not all of them)
- where manual judgment will always exist (and should)
- what “good” looks like before AI ever touches the workflow

Big model companies will focus on big-ticket breakthroughs:
cancer research, energy optimization, genomics, space.

AI-native platforms win by going maniacally vertical,
solving the chronic, unsexy problems that quietly compound inside specific domains.

The companies that break through won’t be the ones with the best model.

They will be the ones that understood the problem deeply enough to know exactly where AI should touch the workflow and where it shouldn’t.

Domain expertise isn’t the moat. Domain architecture is.

Where do you see this playing out in your industry?

Andreessen Horowitz raising $15B for AI last week, is not about technology.
It’s about return velocity and new expectations.

That level of capital only works if value is created faster than before. Not marginally faster, but structurally faster.

Which means this is a bet on a different economy:

- AI is no longer confined to software
- It is moving into the physical economy: manufacturing, logistics, energy, healthcare, infrastructure and defense.

Once that happens, disruption stops being optional.
Traditional industries don’t just digitize, they will have to rethink risk taking, speed, and scale at the same time.

In that environment:

- Speed becomes a competitive advantage 
- Delay becomes a cost
- Effective capital allocation is a strategy

This is where finance quietly becomes critical.
Not as a control function, but as the system that ensures:

- Capital moves with ROI clarity
- Scenarios are easy to build and materially more sophisticated
- Accountability, transparency, and speed form the foundation of high-performing finance teams.


You don’t deploy $15B expecting old operating models to hold.
You deploy it expecting the rules to change.

This feels less like AI news or a fund announcement and more like a leading indicator of how value creation itself is being re-engineered.

Curious how others read this signal: another tech cycle, the early shape of a faster and more unforgiving economy, or a defensive move in a shifting global balance?

I came across a research study from Superintelligent covering 2,000+ companies, and a few data points really stood out:

- Only ~10% of companies have successfully scaled AI agents in any single function.

- The real breakthroughs are happening in large organizations, not mid-sized ones. That’s counterintuitive given their complexity and change management requirements.

- Cost savings are not the primary driver of AI adoption. They actually sit near the bottom.

What companies are looking for: 
1- Time savings
2- Higher output
3- Better quality

One of the key questions to answer in 2026 is : How do we scale AI in the real world and actually capture ROI?

This World Economic Forum discussion does a great job grounding the conversation in practical examples of what it really takes to move AI from experiments & pilots to enterprise-wide impact.

This next phase is critical.
We are talking about trillions of dollars already invested across research, infrastructure, and applications. Without scaling plans, the ROI will never materialize.

Tip: scroll to minute ~15 to skip the intro music and jump straight into the substance.

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