Welcome to another episode of the EUVC Podcast! Today, we’re diving into How Corporates Might just be able Beat VCs in the AI Race. Or maybe more importantly, how we can collaborate.
Our guest is Alex Dang, co-author of the bestselling book The Venture Mindset: How to Make Smarter Bets and Achieve Extraordinary Growth.
Alex is a seasoned technology executive and innovation advisor with over two decades of experience. He was a product leader at Amazon, where he launched new businesses across e-commerce, supply chain, and AI; a partner at McKinsey, helping Fortune 500 companies build digital ventures; and today advises corporate leaders and investors on AI strategies, venture building, and applying VC principles to large organizations.
In this conversation, Alex shares provocative insights on why the venture mindset is now non-negotiable for corporates in the AI era, where incumbents hold hidden advantages over VCs, and how to avoid “innovation theater” while turning data, distribution, and scale into real venture wins.
Let’s jump in!
Here’s what’s covered:
01:56 | The Venture Mindset in one frame with nine principles from 20 years of Stanford VC research: uncertainty → portfolios → outliers
03:44 | The post-book update Alex wishes he had added time compression: “days, not weeks,” and the rise of the “one slice team”
05:53 | Venture mindset applied to AI
07:34 | Why “adding AI” is the wrong framing; start customer-backward, not tech-backward
08:43 | “AI theater”, innovation theater and press release strategies vs real product value
11:19 | The European corporate trap: regulation, consensus, and downside protection as the enemy of transformation
11:56 | The right AI rollout sequence with start in back office to learn and protect trust, then go customer-facing at scale
15:21 | Why CVCs die after 3.7 years: incentives, leadership fear, and why corporate venturing fails structurally
17:24 | AI is now the world’s most democratized intelligence: everyone has the same tools; the gap is execution
18:47 | Where corporates fit in venture + startup ecosystems: strengths: data, distribution, enterprise scale
20:38 | When corporates should build in-house, when to partner, and why AI must become an internal muscle
25:24 | Incentives drive behavior: why executives won’t take venture-style risks unless failure is structurally safe
28:18 | AI-native teams and corporate reskilling among smaller, senior teams + digital workers replacing junior tasks
35:24 | What happens to the average corporate employee: tasks disappear, workflows evolve, but people still matter
38:50 | If Alex were CEO: how to move a workforce into an AI-safe future and target 25% profit uplift through AI
44:01 | Most counterintuitive venture principle — “drop bad ideas fast” and why persistence is sometimes the wrong discipline
46:05 | What top CEOs are doing right now: coding with Claude, learning by building, and staying close to users
49:00 | The compounding effect: “what was impossible 6 months ago is normal today” and why constant feedback loops win
✍️ Show Notes
The Venture Mindset: Why VC Logic Matters More in the AI Era
Alex’s starting point is simple:
Venture capital works because uncertainty is high and outcomes are asymmetric.
Most investments fail.
A few become outliers.
Those outliers generate the returns.
That’s not just finance logic.
It’s an operating system for decision-making when you don’t know the future.
And AI is exactly that kind of environment.
“In uncertainty, your MBA playbook breaks. You need venture mindset tools.”
The book (based on 20 years of Stanford research) identifies nine principles that explain how VCs behave differently and why those principles are increasingly relevant for corporate leaders.
What Alex Wishes He Had Added to the Book
Since May 2024, one thing has become undeniable:
Time has compressed.
Amazon’s famous “two pizza team + launch in 90–111 days” model used to feel fast.
Now:
prototypes launch in days
products ship weekly
teams get smaller
and execution speed becomes the ultimate competitive moat
Alex frames it as:
“Apply the 10x rule to everything — including pace.”
He also introduces the concept of the one slice team:
Many initiatives no longer require a full startup team.
With AI tools + digital workers, one person can launch entire products.
AI Adoption vs. AI Investing: Stop Thinking Tech-Backward
Alex draws a critical distinction:
1) AI adoption
Using AI to reinvent workflows, improve products, personalize customer journeys, and automate internal operations.
2) Corporate venture/investing
Using CVC, partnerships, acquisitions, and startup collaboration as tools to access innovation and talent.
The mistake corporates make?
Treating AI as the strategy.
“The question isn’t ‘what do we do with AI?’
That leads to AI theater.”
Instead, the right framing is customer-backward:
what pain exists?
what workflow is broken?
what can be simplified?
what can be automated?
what becomes possible now?
AI is just one of the tools — like One-Click, Dash, Alexa — successive waves serving the same user needs.
Europe’s Default Reflex Is Wrong for AI
Jeppe raises the European pattern:
AI teams sit close to operations and compliance, not growth.
Alex’s response is blunt:
Europe overemphasizes:
consensus
downside protection
regulation-first execution
Which is the opposite of what you want during a revolutionary shift.
But he adds an important caveat:
trust matters.
That’s why he prefers “minimum lovable product” (MLP) over MVP:
You can move fast, but you cannot break user trust.
The rollout playbook:
start with internal/back-office functions (safe learning environment)
build competence and confidence
move aggressively into customer-facing use cases
Corporates Have a Structural Advantage Startups Don’t
Alex is clear on one massive corporate edge:
“A small win, scaled at enterprise level, can generate 100x impact.”
A startup’s win scales via new customers.
A corporate’s win scales through existing distribution.
That means corporates can:
test small in one region
validate quickly
and roll out globally across millions of customers
Done well, that looks like a VC outlier.
Build vs Buy: The Make Wave Is Real (But Only for the Right Companies)
Andreas brings up the emerging “make wave”:
Why spend millions on generic SaaS when you can build internal tools yourself?
Alex’s take:
If you have the scale and talent to build, build.
Because:
no vendor understands your workflow nuance like you do
many “AI startups” are thin wrappers
and the internal capability becomes a long-term competitive advantage
But he acknowledges not every company is Amazon.
The best approach:
Build core AI muscle internally.
Partner where needed.
Use startups for unique wedge technologies — not generic automation you can do yourself.
Why Corporate Venturing Fails: Incentives
Jeppe drops the stat:
Average CVC lifespan: 3.7 years.
Alex explains why:
Corporate incentives punish failure. VC incentives expect failure. A VC writes off 70–80% of investments.
If a corporate executive fails 70% of the time?
They get fired.
So executives rationally:
make safe bets
stay mediocre
outsource responsibility
hide behind vendor choices (“Microsoft Copilot is approved”)
avoid being the person who tried something risky
Alex’s fix is structural:
change incentives + build culture.
He shares an Amazon moment:
He kept press releases from both successful launches and failures on his wall.
Because the signal matters:
“Failing is fine — and you can still be promoted.”
AI Will Replace Tasks — Not People (Yet)
A key part of the episode is workforce transition.
Alex frames it precisely:
AI doesn’t replace roles.
AI replaces tasks.
Routine, automatable workflows will disappear.
But human work remains essential in:
customer understanding
trust-sensitive interactions
relationship building
decision-making under ambiguity
cross-functional coordination
His advice to employees is practical:
use AI tools daily
build something with them (even a game)
understand the limitations
embed yourself into the workflows
Because the winners will be those who can combine:
domain expertise + AI leverage + human empathy
If Alex Were CEO: The AI-Safe Workforce Plan
Alex outlines a CEO playbook:
set an ambitious goal
e.g., 25% profit uplift via AI initiatives
educate every senior leader
don’t delegate AI literacy to “the AI department”
equip teams with tools + training
AI basics + workflow automation (Zapier, n8n, etc.)
experiment across functions
supply chain, marketing, sales, support
roll out customer-facing AI once trust is protected
He adds a point that’s very EUVC:
The fastest way to shift perspective is to spend time in Silicon Valley, around founders, and see what’s possible.
Not because Europe lacks talent — but because proximity compresses learning curves.
The Most Counterintuitive Venture Insight
Alex’s pick:
“Drop bad ideas fast.”
In high uncertainty, persistence can be a trap.
Letting go early is not weakness — it’s discipline.
And it requires mechanisms to counter human bias:
sunk cost fallacy
ego attachment
internal politics
fear of admitting failure
This principle is one of the hardest for corporate leaders to accept — and one of the most powerful.
The Real Benchmark: Compare Yourself to the Best
Alex ends with a sharp warning:
Don’t compare yourself to the average corporate.
Compare yourself to the best.
The best CEOs are:
building with Claude at night
learning by doing
talking to users constantly
and treating AI not as a technology initiative — but as a reinvention engine
Because the shift is already here.
And the companies who treat AI as a press release strategy will lose to the ones who treat it as an operating system.
💡 Founder & Investor Takeaway
AI is forcing corporates to choose:
stay bureaucratic and slow
or adopt a venture mindset and become an innovation machine
The winners will combine:
VC-style portfolio thinking
customer-backward invention
speed as a competitive moat
and incentive structures that make risk-taking safe
And in the best case, corporates won’t “beat” VCs.
They’ll collaborate with them — and scale innovation together.
