In today’s fast-paced digital landscape, companies are increasingly recognizing the transformative potential of artificial intelligence (AI). 92% of companies plan to increase their AI investments over the next three years.1 And those investments are paying off. For every dollar invested in generative artificial intelligence (GenAI), some companies have realized an impressive 3.7x return on investment.2 To fully capitalize on these benefits, organizations must become AI-ready. Read on to explore what it means to be AI-ready, see where your business is on the AI readiness journey and what infrastructure requirements you’ll need for AI success.
AI Readiness: Building the Foundation
AI readiness is the state of an organization being fully equipped to strategically plan, adopt, integrate and harness the power of AI technologies. This means that the enterprise has the capability to embed AI into the nucleus of its operations. To be truly AI-ready, businesses must lay the right foundation to fully leverage AI capabilities in all aspects of the business, including IT stacks and networks, compliance, DevOps, organizational culture, data management, network and data security, and other vital processes and systems.
The Importance of Scalable Network Architecture for AI
AI initiatives require massive amounts of data to train models. To transport that data across your network, you need high-bandwidth and low-latency connectivity that is secure and reliable. The AI revolution is dynamic and rapidly transforming, so today’s infrastructure won’t necessarily work for your business tomorrow.
In addition to AI, many businesses are implementing advanced applications such as IoT, robotics, ML and big data analytics, while adopting hybrid, multi-cloud infrastructures, edge cloud computing and data centers. Scalable network architecture providing virtualized high-speed connectivity that adjusts capacity based on demand is essential to support and simplify management of multiple digital requirements.
Only after modernizing their networks and infrastructure can businesses fully implement AI applications and models—and start experiencing benefits such as enterprise optimization, cost savings, performance improvements and enhanced customer experiences.
The Journey to AI Readiness
The path to AI readiness can take many forms, but Lumen has found that most organizations can be categorized into one of three groups—Pre-AI, AI Consumer or AI Builder—depending on their level of AI implementation and approach to using AI.
Pre-AI: Not fully digital
Pre-AI describes the phase before an organization has taken any steps to integrating AI into their operations. While they may have made progress towards enhancing their IT infrastructure to be digitally ready, they have not implemented AI in their systems and processes.
These businesses typically rely on manual processes for data analysis using conventional data management and legacy systems not designed for AI. Due to older systems and manual processes, this stage can be characterized by higher operational costs, slower market responsiveness and potential data inefficiencies or security risks due to the absence of AI-driven automation and insights.
AI Consumer: Reliant on AI apps
Organizations that use third-party AI applications to enhance their operations, improve decision-making and drive innovation are classified as AI Consumers. These enterprises rely on AI applications developed by others for modernizing their companies, rather than developing AI technologies themselves. To be considered an AI Consumer organization, an enterprise needs to be using AI in at least one instance. Businesses in this category have varying degrees of AI readiness.
AI Builder: Ahead of the curve
An enterprise that builds AI systems and models to solve complex problems and drive innovation within the company or to resell to its customers is considered an AI Builder. These businesses are typically further along in their AI readiness and digital transformation journey and may require the most robust IT infrastructure to support their own AI demands and those of their customers.
Motivations and Challenges in AI Innovation
Several factors drive AI investment for each organizational type, including the need for competitive differentiation, often triggered by observing competitor success via automated, data-driven strategies. Companies also seek improvements to employee productivity, operational efficiency and customer experience, which is a common starting place for AI innovation for many companies. AI Consumer and AI Builder organizations may also lean in on AI-driven marketing strategies and workflow automation for increased differentiation. AI Builders are also innovating to bring AI solutions to their customers in response to market opportunities.
However, organizations just starting their AI journey, such as those in the Pre-AI stage, can struggle with a lack of knowledge about AI implementations and how to design infrastructure to support a more digitally advanced organization. With some AI experience and strategic partners to provide expert advice, AI Consumers and AI Builders may struggle less with lack of knowledge and education, but fragmented legacy systems and data silos can delay IT modernization and AI efforts. AI progress can also be slow due to perceived complexity and costs, the absence of a formal AI governance strategy and insufficient employee training.
Solving AI challenges with Lumen
The Lumen Network is designed to be AI-ready, providing seamless, secure and scalable connectivity across cloud, edge and data centers. Our high-performance backbone and agile networking portfolio simplify vendor complexity, supporting the advanced needs of AI-driven enterprises. By leveraging our ultra-low loss intercity fiber network, your business gains private and secure connectivity with enhanced cybersecurity protection. This not only minimizes operational costs and mitigates risks but can also help boost your ROI. Additionally, our direct interconnects to major cloud providers and extensive networking expertise enable us to efficiently support your evolving business needs.
Empowering your business starts with:
- Robust network backbone: Our 340,000 route miles of fiber network deliver secure, high-capacity connectivity across cloud, data centers and edge environments. With 2,200+ on-net third-party data centers and peering in 90 metro areas, your business stays connected, competitive and prepared for the future.
- Scalability and agility: We deliver 100G and 400G transport across 78,000+ route miles and connect businesses to 200+ data centers, providing direct, high-speed access to leading cloud providers such as AWS, Azure and Google Cloud.
- A trusted AI partner: We’re more than a network provider. We work alongside your business to design, optimize and advance your connectivity strategies to support AI, cloud and next-generation applications. With expert guidance, deep industry knowledge and hands-on support, we help to simplify multi-cloud integration, private and public networking, and AI-driven transformation. Our 100+ cloud on-ramps and operation of the #1 peered network with actionable threat intelligence via Black Lotus Labs® enable you to scale with confidence.
Every organization’s path to AI readiness will be unique. Whether you’re just starting to explore AI or are already integrating it into your systems and customer-facing applications, adaptability and openness to change are the keys to success. By modernizing your IT infrastructure and embracing new technologies, you are taking the first critical steps toward maximizing AI’s potential and thriving in today’s digital landscape.
Unlock the full potential of AI with a modern network. Read the report, AI Readiness: Shaping the Future of Enterprise IT, to learn more.
1McKinsey, Superagency in the workplace: Empowering people to unlock AI’s full potential, January 2025.
2Microsoft, Microsoft customers share impact of generative AI, November 2024.
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