Value in Technology Value Chains Tends to Migrate to the App Layer

Slow revenue growth and lower average revenue per account are hardly new concerns for suppliers of consumer access services (mobile or fixed). 

But we should not be surprised, either. 

The rule in technology industries is that economic value tends to migrate upward in the technology stack. Network effects are one reason. But opportunities for customer relationships, loyalty and multiple revenue models also make a big difference. 

Asset	Access provider	Application
Customer relationship	Weak	Strong
User data	Limited	Extensive
Workflow integration	None	Deep
Brand loyalty	Moderate	High
Network effects	Small	Often enormous
Pricing flexibility	Low	High

So in the internet value chain, roughly half of ecosystem revenues accrue to app providers, while access providers (internet service providers, mobile service providers) get between 15 percent and 20 percent. 

Value chain layer	Typical participants	Approx. share of ecosystem revenues	Economic characteristics
User applications & digital services	Google, Meta, Microsoft, Netflix, Salesforce	45–55%	Highest margins and strongest network effects
Commerce & digital platforms	Amazon, Uber	20–25%	Transaction-based economics
Cloud & enabling services	Amazon Web Services, Microsoft Azure, Google Cloud, CDNs	10–15%	Infrastructure with higher value-added
Internet access	ISPs, cable, mobile operators	15–20%	Capital intensive, regulated, slower growth
Passive infrastructure	Towers, fiber REITs, colocation	5–10%	Stable but utility-like returns

The economic principle is simple:

• Infrastructure competes on capacity

• applications compete on customer outcomes.

Capacity usually becomes abundant, and abundance reduces pricing power.  Solutions for customer problems remain “scarce,” in the sense that customers gravitate to a relatively few apps and tend to stick with them over time. 

And scarcity supports pricing power. 

Economic force	Internet example	AI analogy
Infrastructure becomes commoditized	Broadband, fiber and mobile access become widely available	GPU clusters eventually become standardized compute utilities
User attention concentrates	Search, social media, streaming dominate consumer engagement	AI assistants and vertical AI agents become primary interfaces
Switching costs increase higher in stack	Users stay with Gmail, Office 365, Salesforce—not because of ISP	Users remain with AI workflow platforms because of memory, integrations and data
Network effects strongest near users	Facebook, YouTube, Amazon Marketplace	OpenAI ecosystem, enterprise agent platforms, developer ecosystems
Pricing power follows differentiation	ISP sells Mbps; applications sell outcomes	GPU provider sells tokens; applications sell productivity or decisions
Marginal cost falls faster below than above	Network capacity continually gets cheaper	Compute cost falls faster than value of specialized applications

In the AI ecosystem, similar value chain effects should happen. Value should accrue heavily at the app layer. 

AI layer	Future revenue share	Why
AI applications and agents	40–50%	Own workflows and customer relationships
Vertical enterprise software	20–25%	Industry-specific solutions
Foundation model providers	10–20%	Models become more competitive over time
AI cloud infrastructure	10–15%	Compute utility with economies of scale
Hardware (GPUs, networking)	5–10%	Hardware normalizes after supply shortages
Power and facilities	3–8%	Necessary but infrastructure economics