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Startups in the Era of AI

What Changes & What Stays the Same

Super Return 2025 Conference

Bernard Leong

CEO & Co-Founder, Dorje AI

bernardleong@dorje.ai

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The AI Funding Explosion

2024: The Year AI Ate Venture Capital

$100B

Global AI Investment

80% increase from $55.6B in 2023

42%

US VC Share to AI

Up from 22% in 2022

33%

Global VC Share

AI's dominance of all venture funding

AI Funding

Non-AI Funding

AI captured more venture capital in 2024 than the entire global VC market invested in 2014

Source: Crunchbase

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The Magnificent Few

Foundation Model Wars: The $500B Concentration

Company

Valuation

Recent Round

Key Investor

OpenAI

$300B

$40B (Mar 2025)

SoftBank ($30B)

Anthropic

$183B

$13B (Sep 2025)

Iconiq Capital

xAI

$50-200B

$11B (2024-25)

Valor, a16z

Perplexity

$18B

$100M (Jul 2025)

Extension round

Market Concentration

Top 5 AI companies control 40% of all AI unicorn value, creating unprecedented market concentration in venture capital history.

Capital Intensity

Three companies raised more in 2024-2025 than the entire European startup ecosystem combined.

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Speed Revolution

From Zero to Unicorn in 18 Months

Traditional Path

7-10 years to $1B valuation

AI Acceleration

18 months average timeline

1

User Growth

ChatGPT: 100M users in 2 months vs Instagram's 2.5 years

2

Revenue Scale

Cursor: $1M to $100M ARR in 12 months (fastest SaaS growth ever)

3

Market Expansion

OpenAI: $1B (2023) β†’ $3.7B (2024) β†’ $12.7B (2025)

AI startups are achieving in quarters what took traditional companies years to reach.

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Capital Efficiency Paradox

High Burn, Higher Returns: The AI Equation

Metric

Traditional SaaS

AI Startups

Infrastructure Costs

15-20% of revenue

40-60% of revenue

Gross Margins

70-80%

40-60%

Revenue/Employee

$200K

$2-5M

Time to $100M ARR

7 years

1-2 years

Valuation Multiple

6X revenue

25-30X revenue

The New Investment Logic

Higher operational costs justified by accelerated growth timelines and winner-takes-most market dynamics. Traditional SaaS metrics require fundamental recalibration.

Risk-Adjusted Returns

Despite higher burn rates, successful AI startups deliver superior risk-adjusted returns through compressed value creation cycles.

Higher costs, faster growth, winner-takes-most dynamics = fundamentally different investment calculus for

venture partners

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The Small Team Phenomenon

Doing More with Dramatically Less

Midjourney Success

$300M revenue with just 131 employees equals $2.3M per employee - 10X traditional software companies.

Cursor Efficiency

$100M ARR achieved with only 12-20 people, demonstrating $5M+ revenue per employee.

Metric

Traditional SaaS

AI Startups

Revenue/Employee

$200K

$2-5M

Team at $100M ARR

300-500

20-50

Development Speed

6 months/feature

2 weeks/feature

This productivity revolution enables AI startups to achieve massive scale with minimal headcount, fundamentally changing venture capital unit economics.

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- Bernard Leong

β€œA Players with AI hire A players.

B, C, D & E players will be replaced by AI agents.”

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Business Model Disruption

From Licenses to Tokens: The New Economics

API-First Revenue

Usage-based pricing replacing traditional seat licenses

Token Economics

$0.01-0.17 per interaction creating scalable revenue streams

Community-Driven Growth

Midjourney's $200M revenue achieved with $0 marketing spend

Hybrid Models β†’ Pay as You Go

Subscription + usage combinations optimizing customer lifetime value

Infrastructure costs are 2X traditional SaaS but deliver 10X scalability potential

77%

Actual AI Usage

vs 33% perceived adoption

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Fintech Revolution

When AI Meets Money: 3X ROI Reality

78%

Enterprise Adoption

Organizations using AI in business functions

60%

Fortune 500

Adopted Microsoft Copilot

353%

Maximum ROI

Achieved by top performers

Financial Services Impact

  • Fraud Detection: 49% of institutions deployed AI systems
  • Robo-advisors: $333B assets under management (Vanguard Digital)
  • Customer Service: 90% query automation achieved
  • Process Automation: $31B RPA market projected by 2030

Enterprise AI spending exceeded $100B globally in 2024, with financial services leading adoption due to clear ROI measurement capabilities.

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Creative Disruption

When Everyone Becomes a Creator

ChatGPT Dominance

700-800M weekly active users, doubled in 2025

Midjourney Growth

20.77M users generating $500M revenue run-rate

Character.AI Engagement

20-28M MAU with 2+ hours daily usage

Creator Adoption

84% using AI tools, 70% time reduction achieved

Market Segment

Growth Trajectory

Generative AI Market

$67B (2024) β†’ $967B (2030)

Creator Economy

$152B (2024) β†’ $715B (2032)

Gaming AI Funding

$315M in Q4 2024 alone

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Sector Heatmap

Where AI Wins: Industry Disruption Patterns

Sector

AI Adoption

Funding Share

Disruption Level

Healthcare

62%

$6.4B

πŸ”΄ Extreme

Financial Services

78%

$17B

πŸ”΄ Extreme

Creative/Media

84%

$10B+

πŸ”΄ Extreme

Enterprise Software

52%

$4.6B

🟑 High

Manufacturing

12%

$2B

🟒 Moderate

Legal

35%

$1.5B

🟑 High

Key Pattern: B2B adoption accelerating faster than expected, while B2C shows higher engagement metrics

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The Enterprise Reality Check

Most AI tools are Point Solutions and not End to End Workflows

β€œThe data also reveals a misalignment in resource allocation. More than half of generative AI budgets are devoted to sales and marketing tools, yet MIT found the biggest ROI in back-office automationβ€”eliminating business process outsourcing, cutting external agency costs, and streamlining operations.” – Source: Fortune

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The Failure Reality Check

90% Failure Rate: Why Most AI Startups Won't Survive

90%

First Year Failure

AI startups failing within 12 months

85%

Three Year Outlook

Expected failure rate within 36 months

5%

Production Success

Pilot-to-production conversion rate

1

Product-Market Fit

34% of failures due to poor market alignment

2

Unsustainable Burn

25-50% higher burn rates than traditional SaaS

3

Platform Dependency

"Wrapper syndrome" creating existential risks

4

Talent War Impact

Unable to compete for critical technical talent

5

Infrastructure Costs

Computational expenses spiraling out of control

254 venture-backed bankruptcies in Q1 2024 represented a 60% increase, highlighting the brutal selection pressure in AI markets.

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Winner-Takes-Most Dynamics

The Concentration Game: Power Laws on Steroids

ChatGPT Dominance

83.5% market share in AI chatbots, creating platform

monopoly effects

Market Concentration

Top 3 AI companies control 62% of total market capitalization

Infrastructure Moats

Nvidia's 80%+ share creates natural computational barriers

Network Effects Amplified

  • Data accumulation advantages compound exponentially
  • Talent concentration through strategic acqui-hires
  • Partnership lock-ins (Microsoft-OpenAI model)
  • Computational moats (100k+ GPU clusters)

Top 3 AI Companies

Next 10 Players

All Others

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Timeless Principles Still Apply

What Hasn't Changed in the AI Gold Rush

Eternal Investment Truths

Product-Market Fit

Still causes 34% of startup failures

Team Quality

Technical founders outperform 3:1 ratio

Unit Economics

Path to profitability remains critical

Market Timing

Being too early still kills companies

Customer Retention

NPS and churn metrics remain vital

Evolution, Not Revolution

  • Moats shifting from data to workflows
  • Distribution still beats product excellence
  • B2B remains more capital efficient than B2C
  • Vertical focus continues winning over horizontal

Fundamental investment principles adapt to AI context but remain the foundation of successful venture decisions.

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The Consolidation Wave Ahead

2025-2026: The Great Reckoning

1

M&A Surge

Incumbents acquiring AI capabilities at premium valuations

2

Foundation Model Shakeout

5 survivors emerging from 100+ attempts

3

Vertical Roll-ups

Industry-specific consolidation accelerating

4

Infrastructure Rationalization

Compute cost optimization driving mergers

Likely Acquirers

Target Categories

Big Tech (FAANG)

AI Infrastructure & Platform Companies

SaaS Giants

Vertical AI Applications

Pharmaceutical

AI Drug Discovery Platforms

Traditional Media

Creative AI Tools & Content Generation

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12-Month Investment Playbook

Where to Deploy Capital in 2025-2026

Vertical AI

Healthcare, Legal, Finance sectors showing higher success rates and defensible moats

AI Infrastructure

Evaluation, Memory, Orchestration - picks & shovels strategy

Enterprise Transformation

AI-native replacements for legacy systems

Geographic Arbitrage

Non-US opportunities at better valuations

Stage Allocation Strategy

Seed/Early

Growth

Late/Pre-IPO

Investment Criteria

  • Seed/Early: Technical moats, domain expertise
  • Growth: Proven PMF, scaling efficiency
  • Late/Pre-IPO: Market leaders, consolidators

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Red Flags & Green Lights

Pattern Recognition for AI Investments

🚩 Red Flags

"Wrapper" Products

No defensibility beyond API integration

Unsustainable Burn

No path to profitability visibility

Platform Dependence

Over-reliance on single foundation model

Commodity Risk

No differentiation from Big Tech roadmap

Domain Inexperience

Founding team lacks vertical expertise

βœ… Green Lights

Vertical Focus

Deep domain knowledge and specialization

Network Effects

Beyond data accumulation advantages

Multiple Moats

Workflow, integration, community locks

Capital Efficiency

Improving unit economics with scale

Proven ROI

Enterprise customers with measurable value

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The $10 Trillion Question

Implications for Global Asset Allocation

15-25%

AI Exposure Target

Optimal allocation of venture portfolio

$4.4T

Economic Impact

Annual potential value creation

3.4%

Productivity Growth

Maximum potential annual increase

Portfolio Construction Recommendations

  • Geographic Mix: 60% US, 40% rest of world
  • Stage Diversification: Earlier stage for pure-play AI
  • Direct vs Fund: Consider dedicated AI funds vs generalist
  • Risk Management: Correlation with tech concentration

Macro Considerations

AI driving unprecedented productivity potential while intensifying sovereign competition. Infrastructure investment becoming national priority across developed economies.

$2.6-4.4 trillion annual economic impact represents largest wealth creation opportunity since the internet

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The AI Imperative

Why This Time Really Is Different(And Why It Isn't)

⚑ What's Changed

Timeline Compression

Development cycles accelerated by 10X

Productivity Revolution

Team output increased 10-25X

Market Concentration

Winner-takes-most dynamics intensified

Infrastructure Barriers

Computational requirements create new moats

🎯 What Hasn't

Fundamentals Matter

Eventually, unit economics still count

Failure Rates

Most startups still don't survive

Timing Critical

Market timing remains decisive factor

Competitive Advantage

Sustainable moats still required for success

"AI represents the greatest wealth creation opportunity since the internet, but with compressed timelines and amplified risks. Success requires new frameworks while respecting timeless principles. The next 18 months will separate the transformative from the transitory."

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Dorje AI – The Different Path

Building the Next Generation Business Operating System

Our thesis: While others chase funding, we chase profitability and build out an ERP-less world.

Our Customers: Medium Size Enterprises with Finance Teams of 4-5 people

Our GTM: Deploying our financial automation solution with agentic AI and proprietary ledger through the hyper-scalers and work with rollup financing firms owned by PE or search funds

Our Counter-Positioning: Pay as You Go replacing Licensing Subscriptions as business model and reducing our customers TCO.

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β€œThey can live in my new world, or they can die in their old one”

- Daenerys Targaryen from Game of Thrones

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How can we help?

Bernard Leong

CEO & Co-Founder, Dorje AI

bernardleong@dorje.ai