Category Creation: Why ‘AGI’ Failed and ‘Agentic AI’ Won

In technology markets, category creation isn’t just marketing—it’s the difference between a $7 billion market and a $41 billion opportunity. The rapid abandonment of “AGI” (Artificial General Intelligence) in favor of “Agentic AI” represents one of the most significant category pivots in tech history, revealing how narrative shapes market reality.

The Anatomy of Category Creation

Category creation involves three critical elements:

• Problem Framing: Defining what’s broken in the status quo
• Solution Positioning: Articulating a new way forward
• Market Education: Teaching buyers to think differently

When done successfully, category creators capture 76% of the market cap in their space, according to Play Bigger’s research on category design.

The Rise and Fall of AGI

The AGI Promise (2022-2024)

AGI emerged as the ultimate category promise:

• Human-level intelligence across all domains
• Self-directed learning and reasoning
• The final invention humanity would need to make

OpenAI’s charter explicitly aimed for AGI. Anthropic raised billions on AGI safety. Microsoft restructured entire divisions around AGI preparedness.

The Reality Check (2024-2025)

By late 2024, cracks appeared in the AGI narrative:

• GPT-5’s Incremental Reality: Launched with “incremental improvements wrapped in a routing architecture”
• Scaling Law Doubts: Diminishing returns on model size increases
• Investor Fatigue: Valuations disconnected from measurable progress
• Regulatory Scrutiny: Governments questioning AGI timeline claims

The definitive moment came when tech leaders who “happily hyped AGI a year ago” began actively avoiding the term, concerned about “stoking inflated expectations.”

The Agentic AI Ascension

Strategic Reframing

“Agentic AI” succeeded where AGI failed by shifting the narrative:

From: Replacing human intelligence

To: Augmenting human capability

From: Indefinite timeline to consciousness

To: Immediate autonomous task execution

From: Existential risk debates

To: Measurable business outcomes

The Market Validation

The numbers validate the category shift:

• Agentic AI market: $7.28B (2025) → $41B (2030)
• Enterprise adoption: <1% (2024) → 33% (2028)
• Concrete metric: 80% workflow automation by 2030

Unlike AGI’s abstract promises, Agentic AI offers tangible value propositions that CFOs can model and CTOs can implement.

VTDF Analysis: Category Creation Dynamics

Value Architecture

• AGI Value Proposition: Infinite but intangible future value
• Agentic AI Value Proposition: Immediate, measurable workflow improvements
• Market Perception: Shifted from “someday maybe” to “available today”
• Buyer Psychology: From FOMO-driven to ROI-driven purchases

Technology Stack

• AGI Technology: Monolithic models pursuing general intelligence
• Agentic Technology: Modular systems with specialized capabilities
• Integration Reality: AGI required fundamental rewrites; agents plug into existing systems
• Development Path: AGI needed breakthroughs; agents need engineering

Distribution Strategy

• AGI Distribution: Top-down, CEO-level vision selling
• Agentic Distribution: Bottom-up, department-level problem solving
• Sales Cycle: AGI had indefinite evaluation periods; agents show value in weeks
• Champion Profile: AGI needed visionaries; agents need practitioners

Financial Model

• AGI Economics: Massive upfront investment, uncertain returns
• Agentic Economics: Progressive investment, measurable milestones
• Pricing Model: AGI lacked clear pricing; agents have usage-based models
• ROI Timeline: AGI promised eventual returns; agents deliver quarterly improvements

The Category Creation Playbook

1. Problem Redefinition

AGI’s Problem Definition: “Human intelligence is limited”

Agentic AI’s Problem Definition: “Human workflows are inefficient”

The shift from existential to operational problems made the category accessible to every enterprise buyer.

2. Enemy Identification

Every category needs an enemy:

• AGI’s Enemy: Human cognitive limitations
• Agentic AI’s Enemy: Manual, repetitive tasks

By making the enemy concrete tasks rather than abstract limitations, Agentic AI created a winnable war.

3. Magic Moment Creation

• AGI’s Magic Moment: Passing the Turing Test (abstract)
• Agentic AI’s Magic Moment: First autonomous workflow completion (concrete)

The tangibility of the magic moment accelerates adoption and word-of-mouth.

4. Ecosystem Orchestration

AGI struggled to build an ecosystem because:

• Undefined standards and benchmarks
• Winner-take-all dynamics
• Regulatory uncertainty

Agentic AI thrived by:

• Clear integration standards
• Collaborative multi-agent systems
• Established governance frameworks

Market Implications

The Enterprise Pivot

Enterprises have shifted procurement strategies:

• 2023: “We need an AGI strategy” (Board-level discussions)
• 2025: “We need agent deployment” (Department-level execution)

This shift from strategy to tactics accelerated spending and adoption.

The Talent Migration

The category shift triggered talent reallocation:

• AGI researchers → Practical AI engineers
• Safety philosophers → Governance architects
• Model trainers → Agent orchestrators

The Investment Recalibration

VCs recalibrated portfolios:

• AGI plays: High risk, indefinite timeline
• Agent platforms: Clear metrics, faster exits
• Market sizing: From speculative to quantifiable

The Psychology of Category Abandonment

The Anthropic Factor

When Anthropic captured 32% enterprise market share with Claude, they did so without mentioning AGI. Their messaging focused entirely on:

• Practical capabilities
• Safety through helpfulness
• Enterprise integration

This success proved markets reward execution over vision.

The Microsoft Moment

Microsoft’s AI CEO declaring consciousness research “dangerous” signaled a corporate shift from AGI speculation to agent implementation. When the largest tech company abandons a category, the market follows.

Future Category Evolution

The Next Categories Emerging

• “Cognitive Infrastructure”: Positioning AI as utility-layer technology
• “Autonomous Operations”: Focus on self-managing systems
• “Intelligence Augmentation”: Human-AI collaboration frameworks

Category Creation Lessons

• Tangibility Wins: Abstract visions lose to concrete solutions
• Metrics Matter: Measurable categories attract investment
• Timing Is Everything: AGI was too early; Agentic AI is just right
• Narrative Flexibility: Successful categories evolve with market feedback

The Category Creator’s Advantage

Companies that successfully create and own categories:

• Capture 76% of market value
• Define buyer criteria
• Set pricing standards
• Shape regulatory frameworks

The shift from AGI to Agentic AI isn’t just rebranding—it’s a masterclass in category creation that turned an abstract vision into a $41 billion market opportunity.

Conclusion: The Power of the Right Name

The demise of “AGI” and rise of “Agentic AI” demonstrates that in technology markets, the right category name can be worth billions. AGI asked the market to believe in a distant dream. Agentic AI offers a solution they can deploy on Monday.

The lesson for entrepreneurs and enterprises: Don’t just build technology—create the category that makes your technology inevitable.

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Keywords: category creation, AGI, agentic AI, artificial general intelligence, autonomous agents, market positioning, enterprise AI, category design, technology markets

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