Is your infrastructure ready for your AI aspirations?

Your business may be ready, but can your IT infrastructure handle the extra demands of AI?

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Over the last decade, IT organizations have worked tirelessly to modernize their infrastructures to support the evolving needs of the business, driven primarily by the transition to the cloud and the software-as-a-service (SaaS) model. But the impact of the cloud now seems practically glacial compared to that of artificial intelligence (AI), which is transforming business—and putting pressure on IT to respond—at an unprecedented rate.

Traditional IT systems must quickly evolve to accommodate the immense processing power, storage, and data management requirements demanded by AI applications. Companies that hesitate to capitalize on these trends risk falling behind their peers in innovation, efficiency, and competitiveness. Without the ability to leverage AI, organizations risk missing out on data-driven decision-making and automation opportunities and fail to deliver the experiences that modern consumers demand.

A recent Cisco report highlights significant infrastructure bottlenecks as organizations strive to integrate AI technologies, revealing that only 14% of companies are "fully prepared" for AI adoption due to deficiencies in six key business areas: strategy, infrastructure, data, governance, talent, and culture. Infrastructure is identified as a particularly critical obstacle; although 95% of businesses acknowledge that AI will increase infrastructure demands, only 17% have networks capable of handling such complexities. A substantial portion of companies, 23%, report limited or absent scalability in their current IT frameworks, while 30% experience issues with network latency and throughput. Additionally, 54% of respondents admit their infrastructure has only "moderate or limited scalability," necessitating updates to support AI's computational requirements. Notably, only 31% of companies describe their infrastructure as "highly scalable," with a mere 13% claiming it is fully adaptable to AI demands.1

Now is the time to invest in your AI infrastructure. In 2024, 48 percent of professionals reported using AI tools at work, but that number grew to 72 percent in 2025.2 Ninety-two percent of companies say they plan to increase their investment in AI over the next three years.3 Ninety-three percent of enterprise IT leaders say they have implemented or plan to implement AI agents in the next two years.4 And there’s no letup in sight. The AI market is projected to continue its explosive growth for years, with a 25-fold increase from $189 billion in 2023 to $4.8 trillion by 2033.5

Infrastructure is key to your AI experience.

Investing in robust AI infrastructure is essential to enable your AI applications to perform efficiently, securely, and at scale. Consider the following areas:

Network bandwidth

You’ll need robust network capacity to handle vast AI data transfer and retention needs.

Compute and memory optimization

Dedicated resources are required to continuously refine infrastructure and AI models to achieve peak efficiency and responsiveness.

Security and compliance

Additional safeguards will be needed for AI data and processes to meet regulatory standards and protect against threats.

On-premise versus cloud strategy

You’ll need to select a deployment model that balances control, scalability, and cost based on your circumstances.

Edge computing

For real-time decision-making, you’ll need to process AI data closer to the source to reduce latency.

The KPMG approach to AI-ready infrastructure

Given the magnitude of the infrastructure changes required to handle computationally challenging workloads associated with AI, the need to prepare becomes significantly more urgent. Addressing these concerns starts with a comprehensive assessment of your existing infrastructure and operations to evaluate your AI readiness and to inform strategies to address data latency, throughput, and rate, each of which is strongly related to the performance of large language models (LLMs).

We’ve developed a two-phased methodology designed to help you develop an AI-ready infrastructure.

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Phase 1: Gather and analyze

This phase involves stakeholder interviews and current state assessments. It includes conducting an analysis of your infrastructure strategy, assessing your capability to adopt AI, performing market research, and evaluating investment plans. KPMG will leverage our Infrastructure AI-readiness framework to pinpoint where bottlenecks are likely to occur. By the end of this phase, you should have:

  • A robust understanding of the current state of your infrastructure
  • A report on the AI infrastructure market and its various vendors related to your strategic goals
  • A review of the existing AI use case roadmap from the business to characterize the increasing load on AI and profile how it may impact infrastructure resources

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Phase 2: Envision the future

This phase involves collaborative workshops to help you envision ideal future state scenarios. It includes designing future roadmaps, investment strategies, high-level system architecture diagrams, data flow diagrams, and more. By the end of this phase, you should have:

  • A clear picture of your AI infrastructure readiness level
  • An understanding of the steps required to implement your AI infrastructure
  • A roadmap of your future state, including a view of key investments in infrastructure that will create the runway for the AI ambitions

Proof. Positive.

KPMG helped a large manufacturing company address its system availability issues and transaction response time variability. We helped to develop a high-availability framework, identifying gaps and providing a roadmap for achieving 99.99 percent availability. This enabled the client to strategically realign its infrastructure investments, effectively communicate availability status, and confidently embark on a phased implementation of the recommendations.

What KPMG can do for you

KPMG LLP is the number-one-ranked firm in the US for quality AI advice and implementation.6 We can help you with system reliability and efficiency evaluations, in-depth performance metrics, and strategic guidance to elevate your business operations. Our solutions are tailored to your specific needs and precise architecture requirements.

Our goal is to provide you with a thorough understanding of the state of your existing architecture, what you need to implement an AI-ready infrastructure, and a detailed roadmap of your future state. We can help you diagnose potential bottlenecks in your infrastructure and show how you can grow your infrastructure to support more advanced capabilities.

Footnotes

1 "Most companies are not ‘fully prepared’ for AI: Cisco”, RCR Wireless News, November 14, 2023

2 "AI adoption surges to 72% among professionals," The CFO, June 3, 2025

3 "How Many Companies Use AI?", Anthony Cardillo, Exploding Topics, May 28, 2025

4 “Integration Key as 93% of IT Leaders Turn to AI Agents Amid Soaring Resource Demands – New Research,” Salesforce, January 29, 2025

5 "AI market projected to hit $4.8 trillion by 2033, emerging as dominant frontier technology," UN Trade and Development, April 7, 2025

6 “Perceptions of Consulting in the US in 2024,” Source Global Research, March 2024.

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