The Uneven Rise of AI: From Silicon Valley Illusions to Global Divisions and Human-AI Struggles

Source: Dev.to

During my time in San Francisco, the AI buzz seemed universal—from startup cafés to tech conferences. Returning to Asia, I found a stark contrast: many people still view AI as a hot stock tip rather than a tool embedded in daily work. This regional gap raises questions about who the real users of platforms like ChatGPT Enterprise and OpenRouter are and how they actually use them.

Regional Distribution of Enterprise AI Users

• ChatGPT Enterprise (OpenAI, The State of Enterprise AI 2025 Report)

  • Predominantly North American users, with rapid growth in Asia‑Pacific (Japan, Australia).
  • Primary industries: technology, finance, professional services, healthcare.
  • Typical roles:
    • Engineers (73% report faster code delivery)
    • Marketers / product teams (85% see improved execution efficiency)
    • IT professionals (87% solve problems quicker)
  • Reported time savings: 40–60 minutes per day on tasks such as data analysis and content creation.

• OpenRouter (OpenRouter, Inc., State of AI 2025)

  • Users: 47% North America, 29% Asia (mainly China and India).
  • Main use cases: programming (over 50% of token volume) and role‑playing.
  • Preference for mid‑sized models for reasoning tasks.

These figures illustrate a global unevenness in AI adoption rather than random variation.

Global Adoption Gaps

• United States and China: Rapid AI integration and high usage rates.
• Other regions: General awareness of AI exists, but detailed understanding and practical use lag behind.

Anthropic Economic Index September 2025 Report – AI adoption correlates strongly with per‑capita GDP.

• High‑income leaders: Israel (7 × global average), Singapore (4.57 ×).
• Emerging economies: India (0.27 ×), Nigeria (0.2 ×).

Industry‑Specific Growth

• Fast‑growing sectors (OpenAI data):

  • Technology, internet, healthcare, manufacturing – >140 % YoY growth in markets such as Australia and Brazil.
  • Engineers report saving over 10 hours per week.

• Lagging sectors: Agriculture, retail, low‑end manufacturing lack “AI DNA,” creating high entry barriers.

Capital‑Driven “AI Rollups”

Wealthy AI players are acquiring traditional businesses and retrofitting them with AI. OpenRouter notes that capital inflows have lifted open‑source model market share from near‑zero to 30 %, but this “capital frenzy” often overlooks the challenges workers face in adapting to new tools.

Societal Fractures

• Adopter vs. non‑adopter camps:

  • 75 % of users report efficiency gains (OpenAI).
  • Many employees resist AI, leading to clear divisions within organizations.

• Well‑being concerns: High‑AI environments see rising demand for therapy and burnout support, echoing past tech booms (e.g., the 1990s internet surge).

• Economic impact:

  • Anthropic warns that AI‑driven productivity could double U.S. growth to 1.8 % annually, but also risk widening inequality and displacing “non‑adaptive” workers.
  • AI initially targets lucrative fields (finance, programming), squeezing human labor and sparking a “survival race” narrative.

Future Outlook and Governance

AI’s trajectory suggests the emergence of “superhumans” – individuals combining extraordinary intellect, strength, and judgment to steer civilization forward. However, governance remains urgent:

• Focus on AI agent control, explainability, monitorability, and controllability to ensure systems truly serve human needs.
• Coexistence strategies must balance AI’s capabilities with human wisdom, experience, and courage against the brute force of big data.