If the Internet Collapsed "Distance," AI Collapses Time

If the core function of the internet is connectivity and the core value is the collapse of distance, then the core function of artificial intelligence is cognition and the core value is the collapse of time. 

If the internet makes physical location less important, AI makes complexity less important, reducing the time to derive insights. 

But both the internet and AI are going to disintermediate value chains, removing distribution functions and providers. 

Dimension	Internet	AI
Core Function	Connectivity: linking people, machines, data, and services across networks.	Cognition: performing tasks that require perception, reasoning, analysis, prediction, or decision support.
Primary Value Created	Eliminating distance: collapsing geography; enabling instantaneous communication and access.	Saving time: collapsing effort; automating, accelerating, or augmenting cognitive tasks.
Economic Logic	Reduces transaction and coordination costs associated with physical separation.	Reduces cognitive labor costs and enhances productivity by automating thinking tasks.
Primary Constraint	Bandwidth, latency, physical infrastructure (fiber, spectrum).	Quality of data, model capability, alignment with goals, compute.
Main Units of Scarcity	Transport capacity (Mbps/Gbps), access points (ports, routers), spectrum.	Compute, data quality, reasoning ability, task generalization.
User Experience Shift	From location-dependent to location-independent access.	From manual decision-making to automated or assisted decision-making.
Industrial Impact	Creates global digital markets; enables remote work, cloud services, platform economies.	Automates white-collar workflows; reshapes knowledge industries; introduces agentic systems.
Business Models	Subscription access, metered usage, advertising, platform marketplaces.	API usage, per-inference billing, embedded intelligence in existing software, agentic task fees.
Strategic Advantage	Owning the pipes, connectivity footprint, spectrum, and interconnection points.	Owning the models, data, workflows, and user attention for cognitive automation.
Regulatory Focus	Universal access, net neutrality, infrastructure competition.	Bias, transparency, safety, copyright, workforce displacement.
Transformation Pattern	Disintermediation of distance-dependent middlemen (retail → e-commerce; media → streaming).	Disintermediation of cognition-dependent middlemen (analysts, coordinators, support roles via agents).

So one way of understanding AI is to view it as a new form of infrastructure, as is the internet, as was electricity or railroads. In that view, potential over-investment happens because the new infrastructure has to be created, and not because of a mania or bubble over asset values that are illusory. 

That might temper some of the concern over AI asset valuations or investment magnitude, which can appear excessive in the near term, and might well be, in some instances. Such early over-investment tends to happen when a new general-purpose technology emerges, and especially when that GPT involves infrastructure.  

Historically, transformative infrastructure projects such as railroads experienced periods of perceived "over-investment," where excess capacity was common before widespread economic and societal adoption caught up. 

The U.S. railroad boom of the late 19th century and the electricity grid’s rollout involved capital surges, initial overbuilding, and even bankruptcies. However, over time, these investments generated foundational benefits, enabling entirely new industries and reshaping nations.

So although the superficial similarity between an irrational asset bubble and an infrastructure boom can exist, they are quite different. 

While a financial bubble features a disconnect between investment and credible returns, general-purpose infrastructure has long-term value, even if some amount of capital is misallocated. 

But that’s the issue right now: some see the infrastructure for a general-purpose technology being built; others see mostly speculation. It can be hard to tell the difference in the early going. 

Criterion	Productive Infrastructure	Speculative Excess
Cost-Benefit Analysis	Thorough, data-driven	Minimal or absent
Multiplier Effect	High, measurable output/wages	Weak, limited economic return
Demand Alignment	Supported by real user/market needs	Based on future hype, not evidence
Systemic Productivity	Positive spillovers	Neutral or negative impact
Asset Price Relationship	Aligned with long-term value	Driven by short-term speculation
Evaluation Rigor	Institutional, non-partisan reviews	Ad hoc, driven by momentum

Agentic AI Should Change Computing Infrastructure: Issue is How Much

Agentic artificial intelligence, eventually featuring teams of autonomous agents working in concert, should have some obvious impact on computing infrastructure. 

Chips will shift further in the direction of custom silicon. There will be more need for low-latency networking; more local or edge processing in addition to remote processing; more parallel and dynamic context to processing; distributed and fault-tolerant processing; more access to distributed databases. 

Specialized hardware (graphics processing units and field programmable gate arrays); more orchestration and more security also will be needed. Think perhaps of swarms of autonomous drones that have to work together, for example. 

In general, we will need “more:” more energy; more chips; more networking; more processing; more interworking and collaboration between autonomous systems. 

So how does that look for a firm such as Lumen Technologies, as a supplier of networking? Perhaps nobody doubts that “more” capacity will be needed, and might be needed in some different locations. 

The issue might be “how much” AI networking requirements actually change market demand, aside from the obvious “more capacity” that is continually needed. 

For starters, Lumen is doubling its intercity fiber mileage; upgrading bandwidth to 100 Gbps and 400 Gbps, using self-provisioning for enterprise customers, with plans to upgrade to 1.2 Tbps to 1.6 Tbps. 

Lumen also is building private networks that connect data centers owned by hyperscalers. But it might be the change in where capacity is needed that will change most. For some time, networking capacity has been driven both by the need to interconnect data centers and the need to make more bandwidth available in the access network so end users are connected with sufficient bandwidth and low-latency services. 

Agentic AI does not necessarily change that situation. Data center interconnection will drive developments in the network backbone. And AI used by edge devices will continue to rely on “on the device” local processing. But requirements for more edge processing in addition to “on the device” will likely mean more regional data center computing and therefore more bandwidth of a regional nature. 

Whether peer-to-peer requirements lead to more meshy architectures remains to be seen. But to some extent agentic AI simply continues other trends such as needs for more symmetrical bandwidth in the access network. As upstream bandwidth became more important as users started routinely uploading images and video, so agentic AI will additionally create more need for bidirectional capacity as local processors and actions combine with web services, software as a service platforms and application programming interfaces.

Barring a big change, such as Lumen somehow divesting its entire local telecom business, to become a latter-day Level 3 Communications capacity supplier, AI-driven requirements might be more incremental than disruptive.

As a financial matter, a Lumen that is a pure-play capacity provider might have 70 percent of present revenue, but a higher valuation. Some believe that could result in a Lumen valuation that is up to double what the firm presently commands, assuming "flawless execution" and probably also hinging on how the debt burden gets distributed.

Will AI Really be that Big a Deal for Connectivity Providers?

As a rule, forecasts for markets tend to err on the optimistic side, many of us would note. So it might not come as a surprise that the benefits of artificial intelligence boosting the need for data center connectivity might be too-optimistic as well. 

We already are hearing how important AI will be for suppliers of data center connectivity, for example. Lumen Technologies is a good example of that, though even data centers are both suppliers and customers of connectivity services (often “local” interconnection rather than “wide area.”

The larger point is that interconnecting domains, already important for cloud computing, is likely to generate even more AI connectivity demand. But the issue is how much new revenue-relevant activity will happen for connectivity providers (data centers also earn interconnection revenue)

Provider	AI Connectivity Revenue	Year	Source
Equinix	$1.2 billion	2024	Gartner Research
Zayo Group	$780 million	2024	IDC Insights
Digital Realty	$650 million	2024	S&P Global Market Intelligence
AT&T	$520 million	2024	Forrester Research
Lumen	$410 million	2024	TeleGeography Research
Total Market Estimate	$3.56 billion	2024	Synergy Research Group

One obvious change in the market is that data center interconnection, for example, used to be largely supplied by “connectivity specialists.” These days, much of the connectivity is supplied by enterprises themselves (Google, Meta, AWS, for example), and not “purchased as a service” from other connectivity suppliers. 

Provider	Bandwidth Estimate	Year	Context	Source Title	Date Published	Publisher
Google Cloud	35.2 Tbps	2024	Internal Network Capacity	"Global Cloud Infrastructure Report"	February 2024	Synergy Research Group
Meta (Facebook)	42.6 Tbps	2023	Private Network Bandwidth	"Hyperscaler Network Infrastructure Analysis"	November 2023	Dell'Oro Group
Amazon Web Services (AWS)	46.8 Tbps	2024	Global Network Capacity	"Cloud Networking Trends"	January 2024	IHS Markit
Microsoft Azure	38.5 Tbps	2024	Internal Network Bandwidth	"Cloud Provider Network Capabilities"	March 2024	Gartner Research
Connectivity Specialists (Combined)	92.7 Tbps	2024	Aggregate Bandwidth from Major Providers	"Telecommunications Infrastructure Report"	February 2024	TeleGeography Research
Internet Backbone Providers	127.4 Tbps	2023	Total Commercial Bandwidth	"Global Internet Bandwidth Overview"	December 2023	Cisco Annual Internet Report

Since firms operating their own networks mostly account for such infrastructure as a cost of doing business rather than a revenue item, we might look at reported interconnection revenue for firms that are in the business of generating revenue from data interconnection or transport, to get some idea of the magnitude of such revenue. 

Company	Revenue Estimate	Source Title	Date Published	Publisher
Equinix	$7.2 billion	"Global Interconnection Market Report"	January 2024	Equinix Market Research
Digital Realty	$5.9 billion	"Data Center Connectivity Market Analysis"	February 2024	Gartner Research
Zayo Group	$3.4 billion	"Telecommunications Infrastructure Report"	November 2023	IDC Insights
Lumen	$4.1 billion	"Enterprise Network Services Forecast"	March 2024	Forrester Research
AT&T	$6.5 billion	"Telecommunications Connectivity Market Study"	February 2024	S&P Global Market Intelligence
Cogent Communications	$1.8 billion	"Data Center Interconnection Market Report"	December 2023	TeleGeography Research

The point is that data center interconnection or capacity revenue is smaller than many would think, though a major revenue source for some connectivity providers. Zayo, Lumen and Cogent Communications are heavily involved in the data center interconnection business. AT&T actually earns more money from such activities, but has much larger revenue contributions from mobility and other services. 

Company	Data Center Bandwidth Revenue	Total Annual Revenue	Percentage of Revenue from Data Center Bandwidth	Year	Publisher
Zayo Group	$3.4 billion	$11.2 billion	30.40%	2023	IDC Insights
Lumen	$4.1 billion	$16.5 billion	24.80%	2024	Forrester Research
AT&T	$6.5 billion	$120.7 billion	5.40%	2024	Morgan Stanley Research
Cogent Communications	$1.8 billion	$5.6 billion	32.10%	2023	TeleGeography Research

The point is that new AI revenues might not be so significant as a source of new bandwidth demand that can be monetized by some transport providers, though it might be important for some specialists. 

Source Title	Date Published	Publisher	Revenue Estimate
Data Center Switches Industry Research Report 2024	September 5, 2024	ResearchAndMarkets.com	$16.3 Billion (2023)
Data Center Networking Market Size, Share, and Trends 2024 to 2033	August 2024	Precedence Research	$38.13 Billion (2024)
Edge Data Center Statistics 2024 By Digital Infra Tech	October 17, 2024	market.us	$12.7 Billion (2024)