Page 10 - Connecting the Future How Connectivity and AI Unlock New Potential

Connecting the Future: How Connectivity and AI Unlock New Potential

broadband in next-generation networks. Together, the standards and frameworks developed by
SG13 and SG15 support a hybrid approach to last-mile connectivity, combining the performance
of fiber with the reach of wireless technologies to ensure equitable and sustainable access to the
Internet worldwide. 8
Regardless of the underlying technology – fiber, satellite, or mobile broadband – connectivity is
ultimately delivered to end users through wired or wireless access technologies. In most settings,
especially in developed countries, most internet traffic is transmitted over Wi-Fi, even when it is
caried by mobile operators. In lower-income regions or mobile contexts, cellular networks often
serve as the primary means of delivering internet traffic, particularly in outdoor or transit environ-
ments.
AI relies on strong, modern digital infrastructure; optimizing each segment of connectivity is essen-
tial to enabling widespread, effective AI use and demands coordinated investment and policy
action.

1�1�2 Unique Requirements for Artificial Intelligence

AI’s reliance on large amounts of data requires significant investment in both computing and
connectivity. However, many parts of the world may still feel less prepared for these upgraded
requirements: Cisco’s 2024 AI Readiness Index indicated that more than half (54%) of global
companies acknowledged their infrastructure “has limited or moderate scalability and flexibility
to accommodate” the increasing needs of AI, while 78% lacked confidence “in the availability of
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computing resources for AI workloads” . Maximizing AI adoption will depend on three key network
characteristics: bandwidth, latency, and stability of network access. Even with recent advancements
in connectivity optimization, cloud-based AI applications require bandwidths upwards of 10-100
Gbps, while complex AI tools like generative models and computer vision require 100-800 Gbps
or more. 10
These high data bandwidth requirements allow AI workloads to access, transmit, and process
massive datasets between Internet of Things (IoT) devices and specialized AI servers used for data
processing. Real-time AI applications, such as fintech, smart grid and smart healthcare, require
low latencies (near-instant response time) in data transmission, as even milliseconds of delay
could impact decision-making and safety. Equally important, successful AI usage requires stable
networks, guaranteeing uninterrupted operations and preventing service disruptions that could
erode trust in AI-driven solutions. 11
Successful use of AI-powered technologies will depend on reliable, redundant communication
networks for real-time data transmission, and the outcomes of AI integration hinge on the speed
and volume in which data can be accessed, processed, and acted upon. This network performance
requires delivery of services across different infrastructures (e.g., 5G, Wi-Fi, fiber and fixed wireless,
satellites) and among disparate systems and devices in the data center, cloud, and edge.
While AI is often associated with cloud-dependent models like LLMs, additional AI tools running on
edge devices – such as handheld diagnostic kits in rural clinics or smartphone-based soil sensors
in agriculture – are transforming services in areas with limited infrastructure. These systems use
onboard machine learning models that function offline and sync when network access is available,
thereby enabling broader inclusion in underserved rural or low-income regions.
As AI systems proliferate across everyday life, robust network infrastructure providing low latency
and network availability for high bandwidths will ensure widespread adoption and effectiveness.

1�2 Digital Infrastructure and Necessary Improvements

1�2�1 Subsea Cable Networks

The network of transoceanic data transmission has expanded to cover the globe with 570 in-ser-
vice systems through over 1,450,000 km of cables. Formerly servicing mostly long-haul Internet
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usage, these networks are now dominated by demand from cloud providers, and data processing
requirements fuel an increasing portion used by AI applications. AI data usage will certainly
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increase capacity demand in these first-mile networks, however government-imposed data sover-
eignty requirements and localized data processing could ultimately limit significant increases in
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capacity requirements. 16

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