The AGI Goalpost Keeps Moving

2026-02-06 · Source: AI Advances - Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, AI Industry Economics & Strategy · Depth: Intermediate, medium

Summary

The concept of Artificial General Intelligence (AGI) is consistently presented as "two years away" by major AI companies like Google DeepMind and OpenAI, a trend observed since 2016. This perpetual near-term projection has fueled over $600 billion in AI investments in 2024-2025, with OpenAI alone valued at $500 billion. However, the article highlights a critical issue: there is no agreed-upon definition for AGI. While its original meaning implied human-level performance across all intellectual tasks, the industry has shifted definitions to suit investment narratives, focusing on economic output (OpenAI's "automated researcher") or benchmark scores (Google DeepMind's Gemini 3). This moving goalpost, termed the "AI effect," means that as AI achieves new capabilities, those achievements are reclassified as "narrow AI," perpetually deferring the AGI milestone.

Key takeaway

For investors evaluating AI companies, you must scrutinize the underlying investment thesis. Do not conflate the aspirational "civilization-scale change" narrative with the tangible "enterprise product" reality. Your valuation models should focus on assessable criteria like revenue growth, market adoption, and competitive advantage, rather than an undefined AGI milestone, to avoid making faith-based commitments at unprecedented scales.

Key insights

The lack of a consistent AGI definition creates significant information asymmetry for investors.

Principles

• AGI's definition shifts to justify investment.
• The "AI effect" reclassifies achieved capabilities.
• Two-year horizon optimizes investment momentum.

In practice

• Distinguish between "transformative" and "economic" AGI narratives.
• Assess AI investments based on measurable enterprise value.
• Question AGI timelines that consistently remain two years out.

Topics

• Artificial General Intelligence
• AI Investment
• AI Definitions
• AI Effect
• AI Valuation

Best for: Investor, Executive, AI Product Manager

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• What is going on with AI? — Academic research on rapidly evolving AI often lags industry reality by 2-3 years due to structural publication delays and outdated models.
• Stock markets fall as concerns persist over tech firms at heart of AI boom — Investor sentiment for AI stocks is shifting, demanding clear financial returns and capital discipline.

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Advances - Medium.