AI demands a new era of connectivity

AI is revolutionizing how organizations operate, from customer service chatbots to real-time data analysis and cybersecurity. But embracing these game-changing technologies does not come without its challenges. Across industries, businesses are feeling an urgent need to rethink their IT strategies.

While the promise of AI is vast, its potential can only be fully realized when supported by reliable, secure and scalable infrastructure. For many organizations — especially midsized businesses and those with limited IT resources — this shift and the hurdles that come with it can feel overwhelming. More than 40% of companies cite inadequate generative AI expertise as a barrier to adoption.¹ No matter the goal, the path forward requires clear planning, the right technology solutions and trusted partners who understand what it takes to make the most of AI.

40% of companies identify privacy or data confidentiality as a concern with AI adoption.²

AI has moved from experimental to operational

The perception of AI as an emerging or experimental technology is rapidly fading. Nearly 90% of organizations are now using AI in at least one business function, with more than half applying it across three or more.³ What started as proof-of-concept trials has evolved into enterprise-scale deployments impacting core operations. AI delivers tangible value in areas like image and speech recognition, sentiment analysis, advanced cybersecurity and real-time analytics. Businesses are automating repetitive tasks, enhancing customer experiences and identifying threats or fraud before they occur. In fact, two-thirds of C-suite leaders say AI adoption is moving faster than expected.⁴

As AI becomes an operational pillar for organizations, the demands on IT infrastructure are intensifying, reshaping the IT services landscape in the process. These aren’t passive background tools — they’re active, data-hungry systems that require high availability, rapid processing speeds and seamless connectivity across distributed environments.

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

Most cited improvements due to organizational AI usage:⁶

64%: Innovation

45%: Employee satisfaction

45%: Customer satisfaction

45%: Competitive differentiation

38%: Cost

Managing the pressure on your network

To support the advanced capabilities AI is making possible, companies must adapt their connectivity strategy. AI workloads require significant computing power and data bandwidth at headquarters and across branch offices, data centers and remote sites. An AI-ready infrastructure must be able to manage the demand for reliable long-haul and middle-mile fiber, seamless multi-cloud access and enterprise-grade security solutions — as well as high-capacity, low-latency connections.

These requirements only grow in complexity as businesses embrace edge computing, remote workforces and Internet of Things (IoT) devices. Each addition introduces more endpoints, more data and more risks, putting pressure on legacy networks that were not designed for such demands. This dynamic only heightens the need for stable, fast, diverse connectivity.

In many cases, outdated infrastructure becomes the bottleneck in AI adoption. As you take on new technologies, you need a network that can keep up with the additional pressure and enable you to get the most out of your technology investment. This means accommodating the data flows required by real-time AI applications and ensuring the security of sensitive data as it moves between users, devices and the cloud.

Security in the age of AI

AI not only increases the need for the right infrastructure, but also expands the cybersecurity attack surface. Beyond traditional threats, organizations must now contend with AI-enabled cyberattacks, including hyper-realistic deepfakes, AI-generated phishing schemes and the manipulation of machine learning training data. Meanwhile, 30% of data breaches involved data stored across multiple environments, with these breaches incurring the highest average cost at $5.05 million.⁷

When AI applications are running 24/7 — powering mission-critical decisions or engaging directly with customers — security lapses can have costly and far-reaching consequences. When adopting AI, security must be embedded at every layer of the network. Organizations need comprehensive solutions such as:

1.     Secure access service edge (SASE) and software-defined wide area networking (SD-WAN) to control access across users, devices and locations.

2.     Unified visibility and centralized management to reduce vendor sprawl and complexity.

3.     Scalable bandwidth and application-aware traffic routing to ensure performance doesn’t degrade under heavy workloads.

4.     Advanced firewalls, malware protection, distributed denial of service (DDoS) protection and automated patching to stay ahead of emerging threats.

42% of organizations struggle to identify a financial justification or business case to move forward with generative AI.⁸

The struggles around budget and resources

While large enterprises often have dedicated teams and budgets to support their AI initiatives, many midsized businesses and IT-lean organizations do not. These firms face multiple challenges ranging from determining AI’s ROI to navigating data governance and hygiene requirements. Over a third (36%) of professionals identify the time and resources required for implementation as a barrier to AI investment.⁹ Leaders must also contend with managing diverse application needs across multiple sites while supporting hybrid workforces that rely on limited infrastructure.

Most businesses want to innovate, but they may find it difficult due to a lack of internal resources required to build and manage enterprise-grade connectivity and security from scratch. They could conclude that they must choose between pursuing AI initiatives or maintaining operational stability, a vexing situation that can lead to inaction. In reality, the either/or proposition is a false choice. With the right strategy, partner and support, businesses can do both.

Top functions that experienced a revenue increase from 2024 to 2025 by using generative AI:¹⁰

· Marketing and sales: 67%

· Strategy and corporate finance: 65%

· Product or service development: 62%

· Supply chain and inventory management: 59%

· Service operations: 57%

· Software engineering: 57%

Bridging the infrastructure gap

What organizations need is not necessarily more technology, but the right technology adapted to their specific needs and scale. An AI-ready infrastructure must be reliable, secure, scalable and efficient. Organizations should consider prioritizing these four key ingredients:

1.     Managed services – Offload network design, implementation and ongoing management to experts. Rely on 24/7 monitoring and support, end-to-end accountability and cost-effective access to expert teams to bolster your in-house IT resources.

2.     Reliable, high-speed internet connectivity – Choose a high-speed fiber network with low latency and sufficient bandwidth for distributed workforces and multi-site operations. Pursue a scalable infrastructure, redundancy and diversity for greater network reliability and resiliency.

3.     A powerful, flexible computing infrastructure – Ensure the infrastructure addresses general-purpose and mission-critical applications and offers nationwide reach with strong service-level agreements (SLAs) that support performance and uptime across all your sites.

4.     Built-in cybersecurity tools – Safeguard networks, applications and users via a mix of technologies built for AI, including SASE support, unified threat management, secure access and identity management.

These and other solutions allow you to focus on driving business value with AI rather than getting bogged down in the technical details of maintaining a complex IT environment.

Choosing a trusted managed services provider

AI growth is focused on productivity and cost efficiency, but that value must be captured without new infrastructure headaches. Navigating this tightrope requires more than just technology — it demands guidance, expertise and exceptional support. More than 85% of IT leaders in North America report that a lack of sufficient IT skills has delayed their digital transformation efforts.¹¹ Given that reality, what might these IT leaders say about their AI adoption?

For many, the key to successful AI adoption lies in choosing the right partner. Whether they lack the internal resources to manage the AI transition or the requisite expertise to execute, many organizations benefit from aligning with partners who can fill the gaps. These valued resources can provide informed counsel, an end-to-end infrastructure and long-term accountability, among other advantages. When organizations hand off the complexity of network modernization, they’re free to focus on what really matters: growth, innovation and customer satisfaction.

Five things to look for in an AI partner:

1.     AI infrastructure modernization expertise

2.     Reliable and secure network services

3.     Solutions that elevate customer experience and employee productivity

4.     A commitment to 24/7 support with a deep understanding of business needs

5.     Cost-effective access to managed services and technical specialists

Spectrum Business® is your managed services partner

AI is no longer just a trend — it’s a business imperative. To keep up, organizations need a modern, intelligent network that enables innovation without compromising performance or safety. Making this transition successfully demands a fundamental shift in how you think about connectivity, scalability and security. That’s where Spectrum Business comes in.

We offer the infrastructure and expertise you need to support your AI initiatives effectively, efficiently and affordably. Whether you’re implementing chatbots, processing large datasets or building personalized user experiences, Spectrum Business can help ensure your network is up to the task — and grows with your goals.

With a portfolio of managed services, enterprise-grade connectivity and security, industry-leading SLAs and 100% U.S.-based support, available 24/7, we empower you to adopt AI confidently and without the burden of building and managing IT systems from scratch. Partnering with Spectrum Business means securing your network, empowering your workforce and readying your operations for the future.

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1.     Cole Stryker, “The 5 Biggest AI Adoption Challenges for 2025,” IBM, February 14, 2025.

2.     Ibid.

3.     “The State of AI in 2025: Agents, Innovation, and Transformation,” McKinsey & Company, November 5, 2025.

4.     “Accenture Pulse of Change,” Accenture, September 5, 2025.

5.     “Artificial Intelligence Index Report 2025,” Stanford University Human-Centered Artificial Intelligence, 2025.

6.     “The State of AI in 2025.”

7.     “Cost of a Data Breach Report 2025: The AI Oversight Gap,” Ponemon Institute and IBM Security, July 2025.

8.     Stryker, “The 5 Biggest AI Adoption Challenges for 2025.”

9.     “Future of Professionals Report 2025,” Thomson Reuters, June 2025.

10.  “The State of AI in 2025.”

11.  Sarah K. White, “67% of Digital Transformations Delayed Due to Skill Shortages,” CIO, January 22, 2025.