How Explosive Growth of AI Impacts the Need for IPv4

The explosive growth of AI has created a complex “push and pull” relationship with IPv4. While AI doesn’t necessarily require IPv4 internally to function, the massive scale of its deployment and the way it interacts with the current internet are placing significant new pressures on the remaining supply of IPv4 addresses.

Here is how the AI boom is affecting the need for IPv4:

1. The “Front-End” Accessibility Problem

Most AI models (like ChatGPT, Claude, or Gemini) and their associated APIs are accessed by millions of users and businesses over the existing internet, which remains predominantly IPv4-based.

Global Reach: To ensure that an AI service is reachable from any device globally, providers must maintain a “front-facing” IPv4 presence.

Compatibility: While the internal data center infrastructure of a company like Microsoft or Google might use IPv6 for its billions of nodes, the “gateways” that connect to the public must still support IPv4 to avoid locking out users who haven’t transitioned to IPv6.

2. Massive Demand for Web Crawling and Training Data

Training Large Language Models (LLMs) requires scraping billions of web pages.

IP Rotation: To gather this data without being blocked by websites’ anti-bot protections, AI companies often require a large pool of IP addresses to rotate through.

The Leasing Market: This has driven a surge in the IPv4 leasing market. AI companies often lease large blocks of IPv4 addresses temporarily for data harvesting tasks, as it is faster and more flexible than buying them.

3. The Rise of “Agentic AI”

We are moving from “chatbots” to “AI agents” that perform tasks independently (e.g., booking a flight, managing a calendar).

Unique Identifiers: Some industry experts predict that as these agents become more autonomous, they may require their own unique, verifiable digital identities. If every distinct AI agent requires its own public IP or identifier to interact with other systems, the 4.3 billion limit of IPv4 will become a total bottleneck.

Identity Infrastructure: This “identity” requirement is one of the strongest arguments for a faster transition to IPv6, which has enough space for every single AI agent to have its own unique address.

4. AI-Powered Data Center Scaling

AI hardware (GPUs like the H100) requires specialized networking.

Internal Scale: AI clusters are so large that they often exceed the limits of traditional private IPv4 ranges (RFC 1918).

Solution: To manage this, many new AI-ready data centers are being built as IPv6-only internally. They use a technique called “NAT64” to talk to the IPv4 internet, reducing the “need” for public IPv4 within the cluster while still requiring it at the edge.

5. AI as a Tool to Manage Scarcity

Interestingly, AI is also being used to reduce the crisis.

Smart Reclamation: AI algorithms are now being used by ISPs and enterprises to identify “zombie” or underutilized IPv4 addresses. By analyzing traffic patterns, AI can find wasted address space and reclaim it for use elsewhere, effectively stretching the lifespan of the existing IPv4 pool.

AI is likely going to drive up the price and demand for IPv4 because of the need for internet compatibility and data gathering. The AI boom has essentially turned IPv4 into a scarce premium necessity.