AI Boosts "Data Center to Data Center" Traffic, Not Home Broadband Needs

Current evidence and expert opinion suggests AI use is unlikely to dramatically increase home broadband data consumption in the near term, while driving new needs for bandwidth between data centers. While that might change in the future if new bandwidth-intensive applications develop, for the moment the impact of AI processing seems focused on "data center to data center" capacity.

For starters, AI query traffic Is comparable to that of search engine use. When consumers interact with AI (asking questions to an AI chatbot), the data exchanged is typically limited to short text queries and responses. That is similar in scale to current web searches, meaning the volume of data transferred to and from homes is not substantially greater than existing activities like Google searches.

In some ways, AI chatbots might also reduce some amount of web browsing,  if users rely on AI to summarize information instead of visiting multiple websites.

To the extent there is more processing, that happens within data centers, not across the access network.

Source/Study	Year	Key Findings on Home Data Consumption	Notes on Scope/Methodology
CircleID / POTs and PANs	2024	AI queries use similar bandwidth to search engines; may even reduce home data use by condensing information	Industry analysis, references Scientific American for energy use, not data volume 12
Dell’Oro Group	2023	AI’s main impact is network optimization, not increased home data use; future metaverse/AI combo could drive growth	Industry report, focuses on network-level effects 4
Fiber Broadband Association / Futurum Group	2024	AI is driving fiber deployment and network investment, but impact on household data volumes not specified	Industry survey, focus on infrastructure 3
BroadbandProviders UK	2024	AI can optimize home network usage and plans, improving efficiency rather than increasing consumption	Consumer-facing analysis, focus on network management 5

On the other hand, AI processing operations are very likely to increase the need for additional bandwidth between data centers. 

AI workloads, especially model training and large-scale inference, require the movement of massive datasets between data centers, cloud regions, and enterprise sites (sources: 1,3,4,6,7), so orders for fiber capacity have increased by an order of magnitude, with standard requests jumping from 8 to 12 fibers to 144 to 432 fibers per route in recent years, some analysts say. .

Traditional static wavelength provisioning also might be inadequate for AI’s dynamic and often bursty traffic patterns. AI training and inference workloads may require large-scale but temporary bandwidth, some argue.

Impact Area	Evidence or Argument	Source(s)
Bandwidth Demand	Orders for fiber have increased 10-50x; AI-driven data centers need petabit-scale data transfer	1,3,4,6,7
Latency & Symmetry	AI requires ultra-low latency, symmetrical speeds for real-time inference and distributed training	1,4,7
Network Agility	Shift from static to dynamic, automated provisioning; need for temporary, large-scale bandwidth	2
Data Center Placement	New builds in power-rich regions, requiring new long-haul and middle-mile routes	4,6,8
Bottleneck Risk	Insufficient fiber could cause congestion, limiting AI growth	4,7

Unlike traditional north-south (server to end user) traffic, AI data centers prioritize server-to-server (east-west) communication for parallel processing, requiring 2–4x more fiber density than traditional hyperscale facilities, observers note.

The bottom line is that additional bandwidth demand will be focused on “data center to data center”` portions of the network, not the access network.

Bye Bye Skype

As Microsoft retires Skype in favor of Teams, it might be useful to recall just how impactful “voice over IP” services such as Skype were in dismantling the telco profit engine.

For example, looking only at revenue, in 2000 global international call revenues were in the range of $80 billion to $100 billion, with very-high profit margins. By 2020, international calling revenues had dropped to about $15 billion to $20 billion, with profit margins compressed. 

 

Decline in International Calling Revenue with VoIP Adoption (2000–2020)
Year	Est. Int'l Calling Revenue (Billion USD)	VoIP Adoption & Skype Milestones	Notes
2000	~80–100	Minimal VoIP presence; traditional PSTN dominates	High tariffs for international calls; telecom monopolies prevalent.
2003	~75–90	Skype launched; 11M users by 2004	Skype introduces free VoIP calls and low-cost PSTN calls, challenging telecom pricing.
2005	~70–85	Skype acquired by eBay ($2.6B); 54M users	VoIP gains traction; telecoms begin lowering rates to compete.
2008	~60–75	Skype grows to 405M users	Economic recession impacts telecom revenue; VoIP alternatives expand (Viber, WhatsApp emerging).
2010	~50–65	Skype disables third-party integrations; 663M users	Telecoms lose market share to VoIP; mobile data plans begin reducing VoIP dependency.
2013	~40–55	Skype-to-Skype int’l traffic up 36% (214B minutes)	TeleGeography notes VoIP capturing significant call volume; traditional revenue continues to decline.
2015	~30–45	WhatsApp, Viber, and others compete with Skype	Mobile apps erode Skype’s dominance; telecoms shift to data-driven models.
2018	~20–35	Skype daily users at 40M (2020 peak)	VoIP services saturate the market; telecom firms  focus on broadband and mobile data revenue.
2020	~15–25	Skype usage spikes 70% during COVID-19	Despite Skype’s decline to 36M daily users by 2023, VoIP remains dominant; traditional int’l calling revenue nears obsolescence.

Profit margins were an important part of the early, pre-VoIP story. Net profit margins on international voice were as high as 25 percent back in 2000. Current net margins are in the range of three percent to possibly five percent. 

In a real sense, VoIP services including Skype disrupted the telecom industry profit driver. 

Year	Domestic Long-Distance Margin (%)	International Long-Distance Margin (%)	Discussion
2000	~12–18%	~15–25%	High margins due to limited competition and high per-minute rates. Domestic margins are slightly lower than international due to local competition. Estimated from telecom sector data and peak long-distance revenue.
2001	~12–17%	~15–24%	Stable margins but early pressure from mobile and VoIP adoption. International margins are higher due to termination fees. Estimated from sector trends.
2002	~11–16%	~14–23%	Decline in domestic voice revenue began as mobile plans offered "bucket" minutes. International margins remained higher but faced VoIP competition. Estimated from sector data.
2003	~10–15%	~13–22%	Continued erosion from mobile and VoIP (e.g., Skype). International margins supported by high termination rates. Estimated from sector trends.
2004	~9–14%	~12–20%	VoIP and internet-based calling reduced costs and rates, squeezing margins. Domestic margins lower due to flat-rate plans. Estimated from sector data.
2005	~8–13%	~11–18%	Long-distance business peaked in 2000; by 2005, revenues were declining rapidly. International margins are higher due to mobile international calling demand. Estimated from sector data.
2006	~7–12%	~10–17%	Domestic margins hit by unlimited calling plans and VoIP. International margins supported by slower price erosion in mobile long-distance. Estimated from sector trends.
2007	~6–11%	~9–16%	Domestic long-distance became commoditized; international margins pressured by OTT apps (e.g., WhatsApp). Estimated from sector data.
2008	~5–10%	~8–15%	Long-distance revenues halved from 2000 peak. Economic recession and VoIP adoption further reduced margins. Estimated from sector data.
2009	~5–9%	~8–14%	Smartphone adoption and VoIP apps (e.g., Skype) eroded margins. International mobile long-distance retained higher margins. Estimated from sector trends.
2010	~4–8%	~7–13%	Domestic long-distance margins near sector average (~4.82%). International margins are higher due to termination fees and mobile demand. Estimated from sector data.
2011	~4–7%	~7–12%	Domestic margins low as carriers bundled unlimited long-distance. International margins declined due to VoIP growth. Estimated from sector trends.
2012	~3–7%	~6–11%	Domestic long-distance fully commoditized; international margins affected by outsourcing and fraud. Estimated from sector data.
2013	~3–6%	~6–10%	Mobile data surpassed voice revenue; domestic long-distance margins were minimal. International margins supported by the wholesale voice market. Estimated from sector trends.
2014	~3–6%	~5–10%	Voice over LTE and VoIP reduced standalone voice profitability. International margins pressured by low-cost VoIP providers. Estimated from sector data.
2015	~3–5%	~5–9%	Domestic long-distance margins were negligible as unlimited plans dominated. International margins declined due to OTT apps. Estimated from sector trends.
2016	~3–5%	~4–8%	Voice services bundled with data; domestic margins near zero. International margins are low but supported by wholesale carriers.
2017	~2–5%	~4–8%	Domestic long-distance margins minimal; international margins affected by grey routes and fraud. Estimated from sector trends.
2018	~2–4%	~4–7%	Domestic margins near zero as voice bundled with data plans. International margins low due to VoIP and 5G adoption. Estimated from sector data.
2019	~2–4%	~3–7%	Voice commoditization is complete; international margins slightly higher due to wholesale voice demand. Estimated from sector trends.
2020	~2–4%	~3–6%	COVID-19 increased communication demand, but voice margins remained low due to free VoIP apps. Estimated from sector data.
2021	~2–4%	~3–6%	Domestic long-distance margins negligible; international margins low but supported by enterprise demand. Estimated from sector trends.
2022	~2–4%	~3–6%	Telecom services margin ~4.82%; domestic voice margins near zero. International margins are low due to wholesale price wars. Estimated from sector data.
2023	~2–4%	~3–5%	North America wholesale voice market faced intense competition, eroding international margins. Domestic margins are negligible. Estimated from sector trends.
2024	~2–4%	~3–5%	Wholesale voice market valued at $40.26 billion in 2025, but margins low due to VoIP and 5G. Domestic margins near zero. Estimated from sector data.

Also, VoIP was not the only huge driver of a shift in consumer behavior. “Calling” became something most people did on their mobile phones. 

Fixed-network revenue dropped from $200 billion globally in 2000 to under $50 billion by 2020, while mobile revenue grew from $500 billion to $1.6 trillion, for example. U.S. telco revenues likewise shifted from fixed to mobile; legacy voice to VoIP. 

U.S. Telco Revenues 2000 to 2024
Year	Mobile Voice	PSTN Voice	VoIP
2000	10	100	1
2010	60	60	21
2020	110	20	41
2024	130	4	49