The AI Capabilities Overhang: Why You're Not Getting AI's Value
Here's a surprising fact: AI systems can do far more than organizations are actually capturing. This gap has a name: the capabilities overhang.
Here's why it matters.
The Concept
The AI capabilities overhang describes the growing gap between:
- What AI systems can do
- What people, organizations, and governments are actually capturing
The capabilities exist. The value isn't being realized.
Why It Exists
Closing the gap isn't about better models. It's about:
Access. Many potential users don't have access to AI tools.
Incentives. Organizations don't have clear reasons to adopt AI.
Organizational change. Deployment requires more than technology.
The barrier isn't technical. It's organizational.
Recent Examples
Consumer products illustrate the gap:
Claude Code going mainstream. AI coding tools reach more users.
xAI reaching gigawatt-scale compute. Infrastructure advances rapidly.
Divergent global adoption. Different regions adopt at different rates.
These examples show capabilities exist. Capturing value is the challenge.
What This Means
The overhang has implications:
Product opportunity. Solutions that help organizations deploy existing AI have value.
Organizational challenge. Technology alone isn't enough.
Competition. Companies that close the gap outperform those that don't.
The Takeaway
The AI capabilities overhang represents opportunity:
- Existing AI is more capable than most organizations use
- The gap is about adoption, not technology
- Companies that help close the gap have business opportunities
The question isn't what AI can do. It's whether you're capturing what it can already do.
Stay ahead of AI trends. tldl summarizes podcasts from builders and investors in the AI space.