Keyboard shortcuts

Press ← or → to navigate between chapters

Press S or / to search in the book

Press ? to show this help

Press Esc to hide this help

Chapter 2: Commodities

Executive Summary

In the digital economy, the concept of commodities—standardized, interchangeable goods and services—has undergone a radical transformation. What once applied primarily to physical raw materials like wheat or oil now encompasses software capabilities, business processes, and even intelligence itself. This chapter establishes the foundational economic principles of commoditization and demonstrates how these dynamics shape modern software businesses, from the infrastructure platform revolution that turned computing into a utility, to the current wave of AI-driven automation that is commoditizing human expertise at unprecedented speed.

Understanding Commodities: An Economics Primer

What is a Commodity?

Definition: Commodity
A commodity is a basic good or service that is interchangeable with other goods or services of the same type. Commodities are characterized by standardization, where the quality and features are uniform across producers, making price the primary basis for competition.

To understand commodities, consider a simple example: wheat. A bushel of wheat from Farm A is essentially identical to a bushel from Farm B. Buyers don't care about the source—they care about meeting a standard specification at the lowest price. This fungibility (interchangeability) is the hallmark of a commodity.

Classical Economic Properties of Commodities

Traditional commodities share several key characteristics:

  1. Standardization: Uniform quality and specifications
  2. Fungibility: Perfect substitutability between suppliers
  3. Price-based competition: With no differentiation, price becomes the primary competitive factor
  4. Low switching costs: Easy to change suppliers
  5. Transparent markets: Clear pricing and availability

The Economic Theory Behind Commoditization

In economic theory, commoditization occurs through a predictable process:

  1. Innovation Phase: New products command premium prices due to scarcity and differentiation
  2. Growth Phase: Competition enters, features standardize, prices begin to fall
  3. Maturity Phase: Products become interchangeable, price competition intensifies
  4. Commodity Phase: Margins compress to near cost of production, volume becomes critical

Example: The Personal Computer

  • 1970s (Innovation): Unique designs, premium pricing ($10,000+)
  • 1980s (Growth): IBM PC standard emerges, clones appear
  • 1990s (Maturity): Features standardize, brands matter less
  • 2000s (Commodity): PCs are interchangeable, sold on price/specs

Digital Commodities: A New Economic Paradigm

Digital goods and services challenge traditional commodity economics in fundamental ways:

Zero Marginal Cost

Definition: Marginal Cost
The cost of producing one additional unit of a good or service.

Unlike physical commodities, digital products have near-zero marginal cost. Producing the millionth copy of software costs essentially nothing, while producing the millionth bushel of wheat requires the same resources as the first.

Economic Implication: This creates potential for extreme price competition, as providers can profitably sell at any price above zero.

Non-Rivalry

Definition: Non-Rival Good
A good whose consumption by one person does not reduce its availability to others.

When you consume a bushel of wheat, it's gone. When you use software, it remains fully available to others. This non-rivalry means digital commodities can achieve infinite scale without depletion.

Example: One million developers can use the same API simultaneously without degrading the experience for any individual user.

Network Effects

Definition: Network Effects
The phenomenon where a product or service becomes more valuable as more people use it.

Digital commodities often exhibit network effects that physical commodities lack. As more developers use AWS, more tools and integrations become available, making it more valuable despite being a commodity.

The Software Commoditization Journey

The Infrastructure Platform Revolution (2000s-2010s)

The early 21st century witnessed a fundamental shift in how computing resources were consumed, transforming IT infrastructure from a capital expense to an operational commodity.

Before: The Era of Owned Infrastructure

In 2005, launching a web application required:

  • Physical servers: $10,000-50,000 upfront investment
  • Data center space: Colocation contracts, cooling, power
  • Network equipment: Routers, switches, load balancers
  • Time to market: 3-6 months for procurement and setup
  • Capacity planning: Guess peak load, usually over-provision

Companies competed on their ability to efficiently manage infrastructure. Having better servers or more reliable data centers provided competitive advantage.

The Transformation: Cloud Computing Emerges

Amazon Web Services (AWS) launched EC2 in 2006 with a radical proposition: computing as a utility.

Case Study: Netflix's Migration (2008-2016)
Netflix moved from owning data centers to AWS, transforming their economics:

  • Before: $50M+ in data center investments, 6-month capacity planning cycles
  • After: Pay-per-hour computing, scale in minutes
  • Result: Could compete with established players without infrastructure investment
  • Impact: Infrastructure became irrelevant to competitive advantage

The Commoditization Pattern

The infrastructure platform revolution followed a clear pattern:

  1. Abstraction: Complex physical infrastructure hidden behind simple APIs
  2. Standardization: Common interfaces (REST APIs, JSON) across providers
  3. Democratization: Enterprise-grade infrastructure available to anyone with a credit card
  4. Price Competition: AWS, Google Cloud, Azure compete primarily on price

Economic Consequences

For Providers:

  • Massive economies of scale (AWS operates 2M+ servers)
  • Winner-take-most dynamics (top 3 providers control 65% of market)
  • Race to zero margins (infrastructure becomes loss leader for higher-value services)

For Consumers:

  • CapEx → OpEx shift (no upfront investment required)
  • Infinite elasticity (scale up/down instantly)
  • Global reach (deploy worldwide in minutes)

For the Market:

  • Barriers to entry collapsed (student in dorm room can build global service)
  • Innovation accelerated (focus on product, not infrastructure)
  • New business models enabled (SaaS, marketplace, platform economies)

Modern Commoditization: Every Layer of the Stack

Today, commoditization has spread throughout the technology stack:

Layer 1: Infrastructure (Fully Commoditized)

  • Compute: EC2, Google Compute Engine, Azure VMs
  • Storage: S3, Google Cloud Storage, Azure Blob
  • Networking: CDNs, load balancers, DNS
  • Pricing: Race to bottom, often loss leaders

Layer 2: Platform Services (Commoditizing)

  • Databases: RDS, DynamoDB, Cosmos DB
  • Authentication: Auth0, Okta, Firebase Auth
  • Payments: Stripe, Square, PayPal
  • Pattern: Best practices encoded in services

Layer 3: Business Logic (Active Commoditization)

  • Email: SendGrid, Mailgun (email delivery as commodity)
  • SMS: Twilio (communications as commodity)
  • Maps: Google Maps, Mapbox (geography as commodity)
  • Search: Algolia, Elasticsearch (search as commodity)

Layer 4: Intelligence (Emerging Commoditization)

  • Language: OpenAI API, Claude API (reasoning as commodity)
  • Vision: Computer vision APIs (perception as commodity)
  • Code: GitHub Copilot (programming as commodity)
  • Analysis: AutoML platforms (data science as commodity)

How Commoditization Occurs in Software

The Mechanisms of Digital Commoditization

Understanding how software becomes commoditized helps businesses anticipate and respond to market changes.

1. Abstraction and Simplification

Complex processes are wrapped in simple interfaces, making them accessible to non-experts.

Example: Payment Processing Evolution

  • 1990s: Implement credit card processing required months of bank negotiations, security audits, custom code
  • 2000s: PayPal provides simple checkout button
  • 2010s: Stripe offers 7 lines of code integration
  • Today: One-click payment setup, AI fraud detection included

Each abstraction layer commoditized the previous complexity.

2. Best Practice Encoding

Industry knowledge becomes embedded in software, eliminating competitive advantages from process expertise.

Example: DevOps Transformation

  • Before CI/CD platforms: Each company developed unique deployment processes
  • GitHub Actions arrives: Best practices for testing, building, deploying become templates
  • Result: Deployment excellence no longer differentiates; it's table stakes

3. Open Standards and Interoperability

Standards enable commoditization by ensuring substitutability between providers.

Key Standards Driving Commoditization:

  • APIs: REST, GraphQL, OpenAPI specifications
  • Data: JSON, Protocol Buffers, Parquet
  • Containers: Docker, Kubernetes, OCI standards
  • Identity: OAuth, SAML, OpenID Connect

4. Venture Capital and Competition

VC funding accelerates commoditization by funding multiple competitors in each category, driving feature convergence and price competition.

Case Study: The CRM Commoditization

  • 2000: Salesforce pioneers cloud CRM at $65/user/month
  • 2010: 50+ funded CRM startups enter market
  • 2020: Basic CRM features available free (HubSpot), $10/month (Pipedrive)
  • Result: CRM features become commodity; competition shifts to ecosystem and integrations

AI as the Ultimate Commoditization Force

How AI Accelerates Commoditization

Artificial Intelligence is not just another technology being commoditized—it's an accelerant that commoditizes everything it touches.

The Commoditization Engine

AI commoditizes through three mechanisms:

  1. Pattern Recognition at Scale

    • AI identifies optimal patterns across millions of examples
    • Best practices emerge automatically, not through human discovery
    • Every company gets access to collective intelligence

  2. Instant Expertise Distribution

    • Knowledge that took years to develop becomes instantly accessible
    • Geographic and language barriers disappear
    • Expertise scales infinitely without degradation

  3. Continuous Improvement Without Human Intervention

    • Models improve through usage across all customers
    • No individual company can match collective training
    • Competitive advantages from proprietary methods evaporate

Business Process Commoditization Through AI

Before AI: Process as Competitive Advantage

Companies historically competed through superior processes:

Example: Amazon's Fulfillment Advantage (2000-2015)

  • Proprietary warehouse management systems
  • Custom algorithms for inventory placement
  • Years of operational refinement
  • Result: 2-day shipping when competitors needed 7-10 days

After AI: Process as Commodity

AI eliminates process advantages by making best practices universally available:

Example: Modern Fulfillment (2020-Present)

  • Off-the-shelf warehouse management AI
  • Standard optimization algorithms available to all
  • Shopify Fulfillment Network offers Amazon-like capabilities to any merchant
  • Result: 2-day shipping is table stakes, not differentiation

Case Studies in AI-Driven Commoditization

The Traditional Model:

  • Law firms competed on expertise and precedent knowledge
  • Document review required trained lawyers
  • $500/hour for contract analysis
  • Competitive advantage through better lawyers

The Commoditized Present:

  • AI contract review (Kira Systems, LawGeex)
  • 95% accuracy in standard clause identification
  • $50 per contract, 1-hour turnaround
  • Same quality regardless of provider

Economic Impact:

  • Entry-level legal jobs declining 20% annually
  • Legal services pricing compressed 60% in routine work
  • New firms competing purely on price
  • Value migrating to complex advisory and relationships

Software Development: From Craft to Commodity

Historical Differentiation:

Company A: Superior coding practices → Better software → Competitive advantage
Company B: Average developers → Inferior product → Market disadvantage

AI-Enabled Commoditization:

All Companies: GitHub Copilot → Same code quality → Competition shifts to business model

Measurable Effects:

  • 40% productivity improvement across all developers (Microsoft Study, 2024)
  • Code quality variance between companies reduced 50%
  • Junior developer value diminishing (entry salaries down 25%)
  • Differentiation moving to architecture and product vision

Economic Implications and Strategic Responses

Value Migration in Commoditized Markets

As commoditization progresses, value doesn't disappear—it migrates:

The Value Stack Evolution

1990s: Value in Infrastructure
└── Servers, networks, data centers command premiums

2000s: Infrastructure commoditizes → Value moves to Applications  
└── SaaS applications command premiums

2010s: Applications commoditize → Value moves to Data
└── Data and analytics command premiums

2020s: Analytics commoditize → Value moves to Intelligence
└── AI and automation command premiums

Future: Intelligence commoditizes → Value moves to...?
└── Relationships, trust, distribution, regulation

Strategic Responses to Commoditization

For Incumbents: Defensive Strategies

  1. Move Up the Stack

    • Amazon: Infrastructure → Platform → AI Services
    • Microsoft: Software → Cloud → AI Copilots
    • Salesforce: CRM → Platform → Industry Clouds

  2. Create Ecosystem Lock-in

    • Apple: Commodity hardware + locked ecosystem
    • Adobe: Commodity tools + Creative Cloud integration
    • Shopify: Commodity e-commerce + app marketplace

  3. Vertical Integration

    • Control multiple layers to capture value
    • Example: Netflix - streaming (commodity) + content (differentiated)

For Challengers: Offensive Strategies

  1. Hyper-Specialization

    • Focus on niches too small for commodity players
    • Example: Vanta (security compliance for startups)

  2. Superior Integration

    • Better connections between commodity services
    • Example: Zapier (connecting 5,000+ apps)

  3. Community and Brand

    • Build emotional connections beyond features
    • Example: Notion (productivity + community)

The Future of Commoditization

What Cannot Be Commoditized?

While AI accelerates commoditization, some areas resist:

1. Deep Human Relationships

  • Trust built over time
  • Emotional connections
  • Personal understanding
  • Cultural alignment

Example: Executive coaching, therapy, high-touch sales

2. Creative Vision and Taste

  • Aesthetic judgment
  • Cultural relevance
  • Emotional resonance
  • Artistic expression

Example: Film direction, fashion design, brand strategy

3. Regulatory and Compliance Expertise

  • Jurisdiction-specific knowledge
  • Relationship with regulators
  • Compliance track record
  • Legal liability acceptance

Example: FDA approval consulting, financial compliance

The Next Waves of Commoditization

Wave 1: Cognitive Tasks (2024-2027)

  • Research and Analysis: AI agents conduct market research
  • Writing and Communication: Content generation becomes commodity
  • Basic Design: Templates and AI eliminate design differentiation
  • Project Management: AI coordinates tasks and resources

Wave 2: Decision-Making (2027-2030)

  • Strategic Planning: AI generates and evaluates strategies
  • Investment Decisions: Algorithmic capital allocation
  • Hiring Decisions: AI-driven talent matching
  • Product Development: AI designs products based on market data

Conclusion

The commoditization of software and business processes represents a fundamental shift in how value is created and captured in the digital economy. From the infrastructure platform revolution that turned computing into a utility, to the current AI wave that commoditizes human expertise, we are witnessing an acceleration of economic forces that transforms entire industries.

Key Takeaways

  1. Commoditization is Inevitable but Predictable

    • Every technology follows the innovation → commodity pathway
    • The speed is accelerating with each generation
    • Planning for commoditization is essential for strategy

  2. Value Migrates, Not Disappears

    • As lower layers commoditize, value moves up the stack
    • New differentiation opportunities emerge continuously
    • Position for where value will be, not where it is

  3. AI is Both Commodity and Commoditizer

    • AI itself is becoming commoditized (model APIs)
    • AI accelerates commoditization of everything else
    • The companies that control AI infrastructure capture outsize value

  4. Platform Positions Provide Temporary Protection

    • Network effects and ecosystem control resist commoditization
    • But platforms too eventually face commodity pressure
    • Continuous innovation is the only sustainable defense

Understanding these dynamics—how commoditization occurs, why it accelerates, where value migrates, and what resists its effects—provides the economic foundation for navigating the digital economy. The future belongs not to those who resist commoditization but to those who understand its patterns and position themselves to capture value wherever it migrates next.