Page 22 - Connecting the Future How Connectivity and AI Unlock New Potential

Connecting the Future: How Connectivity and AI Unlock New Potential

Success Stories:
Leveraging AI to Drive Efficiency

AI-powered predictive maintenance can reduce maintenance costs by up to 30% and
increase equipment uptime by 20%, contributing to overall energy efficiency. Google’s
60
DeepMind AI, for instance, has successfully reduced cooling costs in data centers by 40%
61
through intelligent predictive climate control mechanisms. Additionally, AI algorithms
such as those used in Cisco’s StackPower adjust network component activity based on traf-
fic demand. Deactivating idle components during off-peak hours can lead to significant
energy savings in data centers. AI also facilitates the integration of clean energy sources
into network operations. By forecasting energy demand and intelligently balancing power
distribution, AI enables data centers to maximize their reliance on diverse sources of
power.
Reports indicate that 74% of IBM’s data center energy consumption in 2023 came from
renewable sources, alongside a 16.4% improvement in cooling efficiency. These gains
demonstrate measurable progress in grid flexibility and renewable energy use, under-
scoring the potential of AI to enable real-time, low-carbon energy management across
digital infrastructure. 62

2�3 AI-Driven Security: Safeguarding Data Integrity and Network
Resilience

The security of communications networks is paramount to ensuring data integrity, privacy, and
resilience against cyber threats. AI enhances cybersecurity by continuously monitoring network
traffic, detecting anomalies, predicting threats, and automating responses to security incidents.
Leveraging trusted networks and suppliers – particularly in sensitive AI use cases like healthcare
– further strengthens defenses by ensuring the underlying systems are secure, reliable, and free
from vulnerabilities. 63
The integrity of data used in AI applications depends on secure networks that protect against cyber
threats. AI strengthens endpoint security by detecting malware, ransomware and phishing before
they compromise networks. Advanced AI-driven security solutions employ behavioral analysis to
recognize suspicious activities and take pre-emptive action. Additionally, the ITU has stressed that
safeguarding digital infrastructure must evolve in parallel with AI development. In its global policy
guidance on AI, the organization calls for zero-trust models, data encryption, and privacy-by-design
standards to protect AI training data and digital citizens alike. As such, AI-powered zero-trust
64
security frameworks ensure continuous verification of network access, reducing the likelihood of
unauthorized intrusions.
At a global level, organizations and governments can also enhance their cybersecurity posture
by deploying AI-enabled defenses as an interim safeguard for vulnerabilities when immediate
patching or system replacement is not feasible. This is especially critical in regions where legacy
infrastructure and limited technical capacity increase exposure to cyber threats. These advanced
systems use real-time threat detection and adaptive learning to identify and mitigate potential
exploits, providing a critical layer of protection.
By isolating affected systems, segmenting network traffic, and actively monitoring for suspicious
activity, AI-enabled solutions minimize the risk of breaches while ensuring business continuity.
As digital infrastructure becomes more central to economic and social development worldwide,
deploying AI for proactive cyber defense is essential to ensure global digital resilience and trust.

16