Paul’s Perspective:
The speed and scale of AI adoption, paired with enormous infrastructure investments and plummeting costs, are rapidly reshaping the business landscape—making it essential for leaders to understand where real value and risks now reside. As AI matures and B2B opportunities expand, decision-makers need to track not just the technology, but also evolving business models to capitalize on efficiency gains or niche capabilities.
Key Points in Video:
- ChatGPT reached 800 million users and 365 billion searches in two years, outpacing early internet giants by a wide margin.
- GPU computing power has increased 100× since 2019, driving AI’s rapid evolution.
- LLM inference costs have plummeted by 99.7% in just two years, enabling new business models.
- Top AI models from OpenAI, Google, and DeepSeek now show similar benchmark performance, suggesting a multi-player market.
- Model builders have raised approximately $95 billion, yet only generate an estimated $11 billion in annual revenue.
Strategic Actions:
- Monitor AI user growth rates and adoption patterns in your industry.
- Assess your infrastructure strategy as compute and hardware investments accelerate.
- Evaluate cost declines in AI services to explore new use cases and automation opportunities.
- Track performance convergence among leading AI models for solution selection.
- Watch for changes in pricing models or monetization from AI vendors given funding-revenue imbalance.
- Explore specialized B2B AI applications or ‘pick-and-shovel’ infrastructure investments.
- Stay realistic about the current state of AI agent deployment, especially for mid-market firms.
The Bottom Line:
- AI is experiencing historic user growth, rapidly falling costs, and major infrastructure investment, while model performance now converges among top providers.
- However, there’s a massive funding-revenue gap and significant new opportunities emerging in B2B and specialized AI tools.
Dive deeper > Source Video:
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