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 quoSolution Positioning: Articulating a new way forwardMarket 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 AGIThe AGI Promise (2022-2024)

AGI emerged as the ultimate category promise:

Human-level intelligence across all domainsSelf-directed learning and reasoningThe 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 increasesInvestor Fatigue: Valuations disconnected from measurable progressRegulatory 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 AscensionStrategic 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 DynamicsValue ArchitectureAGI Value Proposition: Infinite but intangible future valueAgentic AI Value Proposition: Immediate, measurable workflow improvementsMarket Perception: Shifted from “someday maybe” to “available today”Buyer Psychology: From FOMO-driven to ROI-driven purchasesTechnology StackAGI Technology: Monolithic models pursuing general intelligenceAgentic Technology: Modular systems with specialized capabilitiesIntegration Reality: AGI required fundamental rewrites; agents plug into existing systemsDevelopment Path: AGI needed breakthroughs; agents need engineeringDistribution StrategyAGI Distribution: Top-down, CEO-level vision sellingAgentic Distribution: Bottom-up, department-level problem solvingSales Cycle: AGI had indefinite evaluation periods; agents show value in weeksChampion Profile: AGI needed visionaries; agents need practitionersFinancial ModelAGI Economics: Massive upfront investment, uncertain returnsAgentic Economics: Progressive investment, measurable milestonesPricing Model: AGI lacked clear pricing; agents have usage-based modelsROI Timeline: AGI promised eventual returns; agents deliver quarterly improvementsThe Category Creation Playbook1. 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 limitationsAgentic 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 CreationAGI’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 benchmarksWinner-take-all dynamicsRegulatory uncertainty

Agentic AI thrived by:

Clear integration standardsCollaborative multi-agent systemsEstablished governance frameworksMarket ImplicationsThe 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 engineersSafety philosophers → Governance architectsModel trainers → Agent orchestratorsThe Investment Recalibration

VCs recalibrated portfolios:

AGI plays: High risk, indefinite timelineAgent platforms: Clear metrics, faster exitsMarket sizing: From speculative to quantifiableThe Psychology of Category AbandonmentThe Anthropic Factor

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

Practical capabilitiesSafety through helpfulnessEnterprise 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 EvolutionThe Next Categories Emerging“Cognitive Infrastructure”: Positioning AI as utility-layer technology“Autonomous Operations”: Focus on self-managing systems“Intelligence Augmentation”: Human-AI collaboration frameworksCategory Creation LessonsTangibility Wins: Abstract visions lose to concrete solutionsMetrics Matter: Measurable categories attract investmentTiming Is Everything: AGI was too early; Agentic AI is just rightNarrative Flexibility: Successful categories evolve with market feedbackThe Category Creator’s Advantage

Companies that successfully create and own categories:

Capture 76% of market valueDefine buyer criteriaSet pricing standardsShape 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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