The Future of AI: From Scarcity to Abundance
In 2026, AI’s promise feels constrained by a scarcity problem, evident in usage limits and costly models. This evolving landscape reveals a significant tension:
- Experience vs. Economics: Despite AI’s transformative power, current pricing models feel like metered utilities.
- Cost Stack Inversion: Major profits rest with GPU vendors like NVIDIA, leaving developers facing thin margins and users rationed access.
- Historical Patterns: AI mirrors past tech trends where dominant platforms limited innovation until competition arose.
Key Insights:
- Two Scenarios Ahead:
- Optimistic: Emerging alternatives to NVIDIA disrupt the cost stack, enhancing accessibility by 2029–2032.
- Pessimistic: Prolonged NVIDIA dominance delays economic normalization until 2033–2037.
The Bottom Line:
AI is in a transitional phase, poised for a future where it becomes integral, predictable, and affordable—similar to electricity.
🔗 Join the conversation! What do you think the future holds for AI? Share your thoughts and insights!
