Build the right infrastructure for AI adoption and competitive advantage

AI is delivering measurable value across industries. Organizations are moving beyond experimentation and into real-world AI deployment. Global spending on generative AI hit $33.9 billion in 2024, up 18.7% from 2023.¹ From intelligent automation to generative tools and predictive modeling, AI technologies are transforming operations, customer engagement and decision-making.

 

For businesses at the crossroads of innovation and digital transformation, the success of their AI initiatives depends heavily on the strength and flexibility of their IT infrastructure. It’s no longer enough to simply explore AI solutions — companies must build networks and systems capable of supporting the demands of modern AI workloads. Those that invest in AI-ready infrastructure and partner with the right managed services provider can accelerate innovation.

 

$1.8T

The projected size of the global AI market by 2030, up from $279.2 billion in 2024.²

 

Understanding the AI imperative and infrastructure demands

AI has evolved into a powerful engine for innovation and growth capable of addressing complex challenges and unlocking new opportunities across virtually every sector. Generative AI enables organizations to craft personalized experiences, quickly generate digital assets and interact with customers at scale. AI-powered predictive analytics allow more accurate sales forecasting, real-time inventory management and proactive maintenance strategies, all of which help reduce downtime and improve efficiency.

 

79% of companies regularly used generative AI in 2025.³

 

Also excelling in the automation of repetitive business processes, such as customer service inquiries or data entry tasks, AI frees employees to focus on higher-value responsibilities. In cybersecurity, AI-powered systems can quickly detect anomalies, identify patterns in large data streams and respond to threats faster than human teams alone could manage.

 

Most cited improvements due to organizational AI usage:⁴

●      64% – Innovation

●      45% – Employee satisfaction

●      45% – Customer satisfaction

●      45% – Competitive differentiation

●      38% – Cost

 

Together, these inroads spotlight the extraordinary potential of AI — not just to improve business operations, but to reshape them entirely. Once discussed as promising future enhancements, AI applications are quickly becoming operational necessities.

 

The competitive advantage of AI

The businesses that are adopting AI are breaking new ground and gaining a competitive edge. The advances AI makes possible are driven by a range of new and improved capabilities being realized across organizations. Faster decision-making is now a reality as AI enables data-driven insights that previously might have taken days or weeks to gather. The technology can also enhance operational efficiency by streamlining workflows, reducing manual overhead and helping companies make better use of their resources.

 

72% of organizations with high AI integration show significant productivity improvements.⁵

On the customer front, AI enables you to offer hyperpersonalized experiences, from customized recommendations to smarter chatbots, driving greater loyalty and satisfaction. In areas like risk assessment and fraud detection, AI provides real-time analytics capabilities that allow businesses to respond more quickly and confidently to emerging threats.

By reducing time to market, AI also fosters innovation. Rapid prototyping, automated testing and intelligent design tools make it easier for businesses to iterate and refine products faster than ever before. Regardless of your industry, the right AI deployment can help you get to value faster, bolstering your customer relationships and market position.

 

AI ranks as a top IT priority

AI has become a primary focus of IT investment. Given the many benefits AI offers, it is consistently identified as a key initiative among IT decision-makers.

Many organizations have moved beyond mere investment and are actively utilizing AI capabilities to help them reach their goals and move their business forward. Nearly 90% are already using AI in at least one area of their business, with more than half deploying it across three or more functional domains.⁶

These numbers highlight that AI is no longer reserved for early adopters or tech giants; mainstream businesses see it as an essential engine for growth and are leveraging it to drive real results.

 

Four common challenges when scaling AI

Despite the excitement surrounding AI, many organizations encounter significant challenges when it comes to scaling these technologies. Preparing for them can help you mitigate their impact and accelerate your AI initiatives.

 

1. Data readiness and governance

AI systems require access to large, high-quality datasets that are clean, structured and well-governed. However, many businesses struggle with fragmented or siloed data, making it difficult to train effective models or extract meaningful insights. Inconsistent governance practices can pose another hurdle, limiting the AI model’s accuracy and reliability.

 

2. Determining ROI and prioritization

Measuring the return on AI investments is another common obstacle. In the early stages, it can be especially challenging to quantify benefits or determine which projects are worth prioritizing. Over a third (36%) of professionals identify the time and resources required for implementation as a barrier to AI investment.⁷ This uncertainty can slow adoption, breed frustration and lead to misallocated resources, undermining the prospects for your AI efforts.

 

3. Network and infrastructure constraints

AI demands high throughput, low latency and distributed compute. Unfortunately, legacy systems often lack the bandwidth, compute power or storage capacity needed for modern AI workloads. Poor network scalability, cloud access bottlenecks, unreliable connectivity and latency problems such as jitter and lag can hobble and even derail AI goals.

 

97% of senior IT leaders say a modernized network is

critical to rolling out AI, IoT, and cloud.⁸

 

4. Security and privacy concerns

Security and privacy remain persistent concerns for those addressing AI. Protecting data at rest and in motion becomes more complex. As these technologies expand into cloud-based platforms and remote working environments, the attack surface expands, putting organizations at greater risk of data breaches and compliance violations. The proliferation of connected devices, from Internet of Things (IoT) sensors to mobile endpoints, further expands security gaps and heightens the need for a more comprehensive security strategy.

 

Core IT requirements for successful AI adoption

To overcome the challenges, businesses must align their infrastructure with AI’s unique demands. Key requirements can include:

 

High-performance connectivity

AI workloads — particularly those involving real-time generative applications or automated decision-making — demand fast, reliable bandwidth, making high-performance connectivity essential. Fiber internet offers the high-throughput, low-latency performance and seamless cloud access necessary to support these and other use cases effectively. For example, high-performance connectivity is a non-negotiable for modern enterprises engaged in model training or data streaming.

 

Edge-to-cloud flexibility

Harnessing the power of AI requires organizations to ensure flexibility across their edge and cloud environments. AI models are often trained in the cloud, where there are vast compute resources, but deployed closer to the data source (e.g., IoT devices, sensors, mobile devices) to allow for real-time processing. This hybrid architecture demands seamless integration between centralized and decentralized computing resources to maintain performance, security and reliability. Failure can result in unwanted data silos, latency and model inconsistencies that undermine the effectiveness of AI.

 

Scalable storage and compute

As models become more complex and data volumes grow exponentially, organizations must be able to scale evolving workloads and underlying resources dynamically without major infrastructure overhauls or downtime. Such flexibility ensures that performance remains consistent during peak usage and that organizations can adapt quickly to shifting computational needs and continue to innovate.

 

Secure, managed networks

Your AI is only as strong as its security posture. Protection should include the encrypted connections, zero-trust access models and continuous monitoring necessary to safeguard sensitive data, prevent unauthorized access and maintain regulatory compliance. Consider implementing role-based permissions, automated threat detection and regular vulnerability assessments. Also, ensure that all endpoints — both cloud and edge — are secured against evolving cyberthreats.

 

Simplified management and monitoring

The right tools make it easier for your IT team to oversee network health, manage traffic, optimize resource usage and quickly resolve performance or security issues — without manual troubleshooting. Access real-time analytics, automated alerts and unified dashboards that help identify bottlenecks and streamline workflows for better overall operational efficiency and response times.

 

Enabling AI success with Spectrum Business solutions and managed services

AI success doesn’t just depend on the right tools — it needs the right network foundation as well as security, control and flexibility. Spectrum Business offers a suite of scalable, secure solutions and managed services to help you successfully execute your AI deployment.

 

Business internet

Reliable, high-speed business internet connectivity forms the backbone of AI deployments, ensuring dependable uptime and consistent access to data, models and cloud services. Spectrum Business provides scalable bandwidth options that can grow with your evolving data demands and compute needs, allowing you to remain agile and responsive. These include everything from reliable, high-quality business internet to our dedicated fiber services. Wireless and backup connectivity are also available.

 

Dedicated fiber connectivity

For organizations with latency-sensitive workloads, dedicated fiber connectivity delivers high-throughput, low-latency performance that’s ideal for real-time AI applications. This ensures dependable performance, even during peak hours, making it ideal for mission-critical AI services and applications. Our suite of internet solutions includes Dedicated Fiber Internet, which offers dedicated, high-speed, scalable, nationwide internet connectivity, with symmetrical upload and download speeds and bandwidth up to 100 Gbps. Our Secure Dedicated Fiber Internet service integrates fast, reliable, dedicated fiber internet with enterprise-grade cybersecurity protection. These high-speed, scalable, low-latency services empower organizations to run AI workloads in the cloud and at the edge efficiently while supporting rapid model training, data transfer and tight security.

When it comes to connecting to cloud service providers, Enterprise Network Edge and Cloud Connect offer a high-performing, secure, fiber-based connection, enabling you to confidently access cloud-based applications from your WAN. Ethernet Services is built on a resilient fiber backbone to provide you with a fast, reliable, private WAN infrastructure. This makes it ideal for connecting distributed offices, data centers and manufacturing sites.

 

WiFi solutions

Enterprise-grade WiFi solutions enable widespread connectivity across locations, supporting AI-driven devices, sensors, cameras and mobile applications. This is especially valuable in edge computing scenarios, where data is collected and processed on-site in real time. Managed Network Edge, delivered with Cisco Meraki, and Enterprise Network Edge from Spectrum Business deliver turnkey, scalable networking solutions that integrate wireless connectivity and routing. As a managed or co-managed service, these platforms include automated updates and provide strong, high-capacity coverage across business locations. This ensures the reliable wireless infrastructure that supports AI-driven applications such as real-time edge inference, IoT device management, secure data collection and uninterrupted cloud interaction.

 

VPN and secure remote access

Allow your distributed teams to collaborate on AI projects from any location. By providing secure, encrypted access to cloud-based tools and data, VPN and secure remote access support hybrid work environments without compromising security. Our solutions combine VPN, zero trust network access, multi-factor authentication (MFA), endpoint protection and identity management. Secure Access with Cisco Duo protects your organization from unauthorized access to sensitive systems, data loss, regulatory violations and business disruptions. This fully managed solution lets your IT teams set access policies by user and device, no matter where they are located.

 

Managed network services

AI environments need more than just speed — they need control, security and adaptability. Spectrum Business delivers these benefits through its broad portfolio of managed services. Managed Network Edge offers comprehensive solutions that combine a software-defined wide area network, security, routing, firewalls and even environmental sensors on a single platform. Enterprise Network Edge provides businesses enhanced security features, edge networking capabilities and seamless integration with legacy WAN environments.

Both of these systems are highly configurable, allowing them to support a wide range of industry-specific needs. They are also AI-ready, automatically prioritizing critical data flows and adjusting network performance based on real-time demands. The platforms are cloud-controlled and feature intuitive interfaces, making it easy for IT teams to manage infrastructure, monitor performance and respond to threats. Organizations gain centralized visibility across all locations and devices through a unified portal, simplifying operations and reducing the risk of downtime.

 

Managed security services

In addition to Secure Access with Cisco Duo, Spectrum Business offers other enhanced cybersecurity solutions such as Cloud Security with Cisco+ Secure Connect, which provides MFA and zero-trust access control, securing devices, users and remote locations. These cloud-managed tools help businesses implement a secure access service edge (SASE) framework, which combines networking and security into a unified, scalable architecture. These platforms also help you meet compliance demands such as HIPAA and the Payment Card Industry Data Security Standard (PCI DSS).

For protection against large-scale distributed denial of service (DDoS) attacks, Spectrum Business offers the subscription-based DDoS Protection service. It uses AI-powered analytics and proprietary machine learning to detect and mitigate threats in real time, helping to maintain network availability.

 

Accelerate your AI initiatives with Spectrum Business

Once a distant goal, AI is now a competitive requirement. To fully capitalize on the benefits of generative AI, intelligent automation and advanced analytics, organizations must address network modernization. Spectrum Business provides the secure, scalable and high-performance foundation that modern AI workloads demand. With a full suite of managed services; enterprise-grade connectivity; industry-leading service-level agreements and 100% U.S.-based support, available 24/7, Spectrum Business empowers organizations to unlock the full potential of AI. The future of business belongs to those who build for it — start your AI journey today with Spectrum Business.

Learn more

 

1. “Artificial Intelligence Index Report 2025,” Stanford University Human-Centered Artificial Intelligence, 2025.
2. “Artificial Intelligence Market Size, Share & Trends Analysis Report By Solution, By Technology (Deep Learning, Machine Learning, NLP, Machine Vision, Generative AI), By Function, By End-Use, By Region, and Segment Forecasts, 2025-2030,” Grand View Research, 2024.
3. “The State of AI in 2025: Agents, Innovation, and Transformation,” McKinsey & Company, November 5, 2025.
4. Ibid.
5. “Artificial Intelligence Index Report 2025.”
6. “The State of AI in 2025.”
7. “Future of Professionals Report 2025,” Thomson Reuters, June 2025.
8. “Cisco Research: A Major Infrastructure Shift Is Underway. AI Could Double the Strain or Solve It,” Cisco, June 4, 2025.