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 Will Cause Additional Disintermediation in Value Chains

Agentic artificial intelligence, which as software agents acting on behalf of human users, will threaten some participants in existing value chains, in the same way that internet platforms and apps disrupted commerce and content value chains. 

“Disintermediation” is the removal or reduction of intermediaries in any value chain. Disintermediation allows buyers, producers, and consumers to bypass traditional middlemen such as brokers, consultants, customer service agents or logistics coordinators. 

Consider any procurement operation. 

AI agents can gather and compare data across sources in real time, reducing reliance on human experts or intermediaries for information gathering or product curation. That might threaten some parts of Amazon and other e-commerce platforms, for example. 

As was the case with internet retailing, this is going to create new pressures for “price-based” comparisons and some potential diminution of “brand value.” 

AI agents then will negotiate price, delivery, and quality parameters autonomously, replicating the human “buy this” operation, and also circumventing many of the marketing practices that assume a human is persuadable during the buying process. 

As was the case for internet retailing, agentic AI should create more direct producer–consumer ability to transact directly, without distributors.

Process orchestration also should happen, where the AI unifies and handles procurement, contracting and payment operations that previously might have required multiple apps or systems. In a growing number of cases, this will involve the buyer’s agent negotiating with the seller’s agent, without distributors, advisors, consultants or specialists in between them. 

And where internet commerce featured lots of “personalization,” so agentic AI will replace “trusted advisor” or “expert advice supplier” functions and suppliers of those values. “Personalization” and “AI customization” will be analogous outcomes. 

Industry / Value Chain Stage	Traditional Intermediary Role	How Agentic AI Enables Disintermediation	Agentic AI Scenario
Retail and E-commerce	Online marketplaces (Amazon) aggregate sellers and handle logistics	AI shopping agents directly compare sellers, place orders, and track delivery	Consumers’ personal AI negotiates bulk discounts from multiple retailers and arranges delivery without using a central platform
Financial Services	Brokers, financial advisors, loan officers	AI evaluates options, performs due diligence, and executes trades or loans	A consumer’s AI portfolio manager automatically reallocates investments across platforms using live market data
Real Estate	Real estate agents and mortgage brokers	AI agents handle property search, valuation, negotiation, and contract execution	Buyers use AI that identifies undervalued homes, negotiates price, and manages closing paperwork
Supply Chain & Procurement	Procurement agents, sourcing platforms	AI autonomously sources suppliers, evaluates risk, and executes contracts	A manufacturer’s AI identifies suppliers worldwide and directly contracts best-value inputs without human brokers
Healthcare	Primary care gatekeepers, medical schedulers, or insurers as coordination intermediaries	AI triages symptoms, recommends providers, and books care directly	AI health assistant evaluates symptoms, finds available doctors, and schedules an appointment — skipping insurer’s pre-authorization layers
Entertainment / Media Distribution	Streaming platforms, music labels	AI agents match creators directly with audiences and handle rights/licensing smart contracts	Artists’ AIs distribute content directly to audience AIs, who pay micro-royalties automatically
Travel & Hospitality	Travel agents, comparison websites	AI directly plans and books multi-leg trips, comparing prices and reliability	A traveler’s AI negotiates with airlines and hotels’ AIs to assemble the best route and price
Legal & Professional Services	Lawyers, notaries, consultants	AI creates, reviews, and files contracts autonomously	SMEs use AI to draft and file incorporation paperwork directly with government APIs
Education / Training	Universities, training marketplaces	AI tutors create personalized curricula and credentialing directly	Learners use AI tutors that build custom programs, verify mastery, and issue credentials via blockchain
Advertising & Marketing	Agencies, ad brokers	AI agents buy media and tailor campaigns autonomously	A small business’s AI negotiates ad buys with media outlet AIs in real time, eliminating agency fees

So among the “dangers” or challenges for e-tailers are new value compression issues, with the correlating danger of profit margin compression. 

The danger for e-commerce platforms is a loss of gatekeeper power as more peer-to-peer or agent-to-agent interactions develop. 

Brands might also find they face some diminution of “brand value,” just as price comparison sites will shift buyer evaluations in the direction of “lower price.”

How Will Agentic E-Commerce Reshape Value Chains?

Amazon "Buy for Me" provides an example of the way agentic artificial intelligence is going to reshape consumer retail. “Buy for Me,” a new program in beta testing stage, helps customers discover and seamlessly purchase select products from other brands’ sites if those items are not currently sold in Amazon’s store. 

Depending on the product, customers using the Amazon shopping app and "Buy for Me" can either shop brand sites with the help of AI, or visit the brand’s site directly. Shipping, delivery, returns, exchanges, and customer service are managed directly by the brand.

As seems to be the case for earlier e-commerce aggregators including Expedia and delivery services such as DoorDash, the impact on retailers might be both positive and negative. 

On one hand, brands can experience expanded customer access, but also lower profit margins. Smaller brands might benefit in terms of awareness and sales, but at the risk of some brand dilution and loss of control. 

And, as has been the case for virtually every e-commerce advance, price competition will grow. In some cases, the danger of disintermediation (replacing distributors from the value chain and allowing manufacturers to sell directly to customers) is possible. 

New questions will emerge around the issue of whether customer loyalty is affected as well. Will customers be more loyal to the platform or to the brands?