AI’s Infrastructure Challenge: Why Connectivity Matters for Scaling AI Workloads

Optimising AI Performance: The Critical Role of High-Performance Connectivity

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In this article

• TLDR
• Introduction: AI’s reliance on connectivity
• Why AI Workloads Demand High-Performance Connectivity
• Key Factors Driving AI Connectivity Needs
• Performance Benefits of Private Cloud for AI
• The Role of Private Cloud in AI Scalability
• BSO’s Role in Optimising AI Connectivity
• Future-Proofing AI with the Right Connectivity Partner

TLDR:

Artificial intelligence continues to expand across industries, yet many firms overlook connectivity when planning AI infrastructure. Speed, bandwidth, and latency directly influence AI training, inference, and real-time applications. High-performance networking ensures seamless data movement, unlocking better efficiency and scalability.

BSO delivers ultra-low-latency solutions tailored to AI-driven enterprises. Their high-bandwidth networks enhance model performance, ensuring rapid data transfer and minimal bottlenecks. Businesses adopting private cloud and hybrid infrastructure gain greater security and compliance while maintaining optimised connectivity.

Future-proofing AI depends on robust infrastructure. Companies prioritising scalable, high-performance networking will maintain a competitive edge in an increasingly AI-driven landscape.

Visit our AI Solutionsns page to find out how BSO can help you.

AI's Reliance on Connectivity

The rapid advancement of artificial intelligence (AI) is transforming industries, from finance and healthcare to manufacturing and retail. However, while most organisations focus on computational power, a crucial component is often overlooked: connectivity.

AI's success hinges on rapid and reliable data movement. Latency, bandwidth, and network efficiency directly impact model training, inference, and real-time decision-making. Without high-performance networks, AI models experience delays in training, inference, and deployment. This in turn reduces their effectiveness, making AI scalability a challenge. 

High-speed, low-latency connectivity ensures that AI applications can access and process vast datasets efficiently, making real-time decision-making possible. As AI adoption grows, businesses that prioritise robust network infrastructure will gain a competitive edge in innovation and operational efficiency.

Companies that are using and training AI models are looking to invest in better infrastructure in order to meet the need for growing AI workloads. BSO is a leader in addressing these AI infrastructure challenges. BSO offers ultra-low-latency networks, optimised cloud access, and scalable connectivity solutions that empower AI-driven enterprises to operate at peak efficiency.

Why AI Workloads Demand High-Performance Connectivity

Low latency refers to minimal delay in data transmission, ensuring rapid response times between systems. In AI, low-latency networks are crucial for applications such as high-frequency trading, autonomous vehicles, and real-time analytics. 

AI models process vast amounts of data across distributed environments, requiring continuous data transfer. Whether an organisation is training large-scale machine learning models, running AI-powered financial transactions, or optimising industrial automation, connectivity is critical. 

This means that high-performance networks are not just a luxury anymore. They are needed in order to support the continuous development of AI and to support AI workloads.

Key Factors Driving AI Connectivity Needs:

1. Data Movement Efficiency: AI models continuously ingest and process data from various sources. Without high-speed, low-latency networks, training times increase, leading to slower AI advancements.

2. Real-Time Decision Making: AI applications in finance, healthcare, and manufacturing require immediate insights. Latency-sensitive environments must leverage optimised connectivity to avoid delays.

3. Cloud & Edge Integration: AI workloads often span hybrid cloud environments and edge computing frameworks. Secure, high-bandwidth connections ensure smooth interoperability and data flow.

It’s no secret that data centers are requiring more bandwidth to support AI and machine learning workloads. In order to meet these needs, there is a huge drive towards scalability. According to OSI Global, a modern AI-focused server can consume up to 6000W of power. 6 of those go into a standard 42U rack where each rack consumes an average of 37W. And we aren’t just talking about 3 or 4 racks of hardware, but more than 100! The need for better infrastructure that can handle these AI workloads is increasing on a daily basis!

BSO is a global leader in providing ultra-low-latency infrastructure, leveraging its extensive network presence across financial hubs, data centres, and cloud environments to deliver industry-leading speed and reliability. BSO’s low-latency networks mitigate congestion and accelerate AI deployments, ensuring optimal performance.

Performance Benefits of Private Cloud for AI

Private cloud is a dedicated cloud environment tailored to a single organisation, offering greater control, security, and performance. For AI workloads, private cloud infrastructure ensures seamless scalability by reducing data transfer bottlenecks and enabling direct access to computing resources. 

Businesses leveraging private cloud solutions can maintain high-speed data processing while ensuring compliance with industry regulations. This makes it an ideal choice for enterprises scaling AI initiatives. Private cloud solutions offer enhanced control and performance for AI workloads.

The Role of Private Cloud in AI Scalability:

1. Reduced Data Bottlenecks: AI applications rely on high-speed data ingestion. By implementing private cloud environments with dedicated connectivity, this allows for congestion issues to be eliminated.

2. Seamless Hybrid Cloud Integration: Many AI enterprises adopt multi-cloud strategies. Private cloud solutions ensure smooth interoperability across cloud providers without performance trade-offs.

3. Enhanced Security & Compliance: AI-driven sectors such as finance and healthcare need to consistently adhere to strict compliance and regulations. Private cloud connectivity minimises exposure to security threats and ensures compliance with data protection laws.

A recent Gartner study predicts that by 2027, over 75% of enterprises deploying AI will leverage hybrid cloud infrastructures to balance performance and scalability. 

BSO’s high-performance networking solutions provide the connectivity foundation for seamless AI expansion. According to 451’s research, with the amount of data being transferred with AI workloads, organisations are struggling to meet the full scale of demand for AI capabilities. That’s why BSO focuses on providing data-intensive businesses with the infrastructure that is needed to keep up with demand. With our highly available and diverse networking solutions, we provide access to markets that others can’t.

BSO’s Role in Optimising AI Connectivity

The Importance of Ultra-Low Latency Infrastructure for AI Development

Ultra-low latency infrastructure is a foundational element for AI's continued evolution. AI models require instantaneous data transfer and real-time processing capabilities, particularly in applications such as autonomous systems, predictive analytics, and financial modelling. Without ultra-low latency networks, AI systems experience delays that can be detrimental to time-sensitive environments. 

BSO Empowering AI Connectivity

BSO delivers industry-leading AI networking solutions that empower AI enterprises to scale efficiently. With expertise in ultra-low-latency infrastructure, dedicated cloud access, and edge computing enablement, BSO ensures AI workloads operate with maximum performance.

Key BSO Connectivity Solutions for AI:

1. Ultra-Low-Latency Networks: Our ultra-low latency networks at BSO are essential for time-sensitive AI applications such as financial trading, autonomous systems, and real-time analytics. 

2. High Bandwidth: Our high-performance network infrastructure is designed to support the immense data transfer demands of AI-driven workloads. Whether it's training large-scale machine learning models, processing vast datasets, or enabling real-time data ingestion, BSO delivers ultra-low-latency, high-bandwidth connectivity to keep AI operations running at peak efficiency.

3. Global Reach: With a robust presence in the world’s most critical data hubs, BSO provides seamless, high-speed connectivity for AI teams and applications operating across multiple regions. Our globally distributed network ensures minimal latency, uninterrupted data exchange, and reliable access to computing resources—empowering businesses to scale AI initiatives without geographical limitations.

By leveraging BSO’s infrastructure, businesses can eliminate connectivity bottlenecks, accelerate AI processing, and maintain seamless data flow across distributed AI environments.

Optimising AI Server Infrastructure for Maximum Performance

A well-configured AI server environment is essential for driving optimal performance and efficiency. AI workloads place unique demands on infrastructure, making hardware selection and architecture critical considerations.

BSO’s expertise in high-performance networking complements AI server optimisation strategies by ensuring seamless data flow and minimal latency. Selecting the right hardware, including high-speed GPUs for deep learning and scalable memory solutions, is crucial for maximising AI capabilities.

For AI applications requiring real-time processing, edge computing solutions help reduce latency by bringing computation closer to data sources. Meanwhile, high-performance storage solutions, such as fast SSDs, accelerate data retrieval, enhancing AI training and inference efficiency. By integrating cutting-edge AI server configurations with BSO’s connectivity solutions, businesses can unlock new levels of AI performance and reliability.

Conclusion - Future-Proofing AI with the Right Connectivity Partner

AI adoption is accelerating, but without a robust connectivity strategy, scaling AI workloads can become a costly and inefficient challenge. Businesses must prioritise high-performance networking to unlock the full potential of AI.

In knowing that 59% of respondents in the 2024 state of AI Infrastructure report, said their AI roadmaps include looking at increasing their investments into better IT infrastructure. 

BSO provides AI-driven enterprises with scalable, low-latency, and high-bandwidth connectivity solutions designed to optimise AI workflows. Whether deploying AI models in finance, healthcare, manufacturing, or retail, organisations can future-proof their AI strategies by partnering with BSO.

Explore how BSO’s AI connectivity solutions can empower your business.

Visit our AI solutions page today.