Stop guessing, start building: Why your AI ambition needs a readiness check

Technology often moves at a pace that can be hard to match. Each new wave builds on the last, changing how organizations operate and compete. Nowhere is this more evident than with AI — the most recent, and possibly the most transformative, technological advancement of our age.

AI has moved beyond experimental pilots and is now a defining force in competitive advantage. According to NTT DATA’s new 2026 Global AI Report: A Playbook for AI Leaders, organizations identified as AI leaders are nearly 2.5 times more likely than others to achieve revenue growth above 10% and 3.6 times more likely to sustain profit margins of 15% or higher.

The report draws on extensive research among more than 2,500 C-suite and other senior decision-makers across 15 industries and 35 countries. It defines AI leaders as organizations with an AI strategy that is well-defined or in progress, a “mature” or “evolved” level of AI capability, and significantly greater realized profits from AI than their peers.

It’s clear that recognition of AI’s business potential is no longer the issue. However, for many organizations, execution remains a challenge.

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When cloud isn’t an option

Consuming AI “as a service” through the cloud is often the simplest solution but not always the right one — or even possible at all. In industries such as defense, healthcare, finance and the public sector, deploying AI on-premises can be a necessity.

For public institutions, it’s about digital sovereignty — keeping sensitive data within national borders. For finance and healthcare, it’s about compliance, governance and the need to operate within stringent regulatory frameworks. And for defense and other critical sectors, it’s about security, privacy and availability, because they need to keep data in a local environment where systems remain resilient even when networks don’t.

Sometimes the decision is purely technical, relating to concerns around low latency, local control or avoiding data-transmission risks. But the principle is the same: Some organizations cannot rely on someone else’s infrastructure to run their intelligence.

The infrastructure readiness gap

If you can’t run your AI through the cloud, your own infrastructure has to shoulder the load. But if your infrastructure isn’t robust enough to keep pace with AI’s speed, scale and resilience demands, it quickly becomes a bottleneck.

The most powerful AI model is useless if the backbone it runs on can't deliver. Unfortunately, many organizations learn this the hard way. They have strong business use cases, but their systems aren’t built for it. This divide between aspiration and a reliable, high-performance AI deployment is what we call the infrastructure readiness gap.

Finding the best way to address this challenge is crucial: Our AI report shows that compared with other organizations, AI leaders are investing more in rebuilding their core applications with embedded AI capabilities rather than limiting themselves to surface-level add-ons.

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The biggest challenges on the path to AI

Many organizations hit a wall when trying to scale AI for two main reasons:

The translation gap

This occurs when your executive team has defined a powerful business use case, such as “Improve customer service with a GenAI chatbot.”

Next, you have to translate this business need into a list of specific technical requirements for your network, storage and computing teams. However, without a structured approach, what starts as a clear vision quickly dissolves into uncoordinated initiatives.

Fragmented infrastructure

Your existing systems might not have been designed for the demands of distributed AI workloads. In practice, this often means slow network connections, underused GPUs and fragmented data storage, leading to slow AI training, high costs and models that don’t perform well in production.

The baseline AI Readiness Assessment: Your bridge to architectural clarity

This makes NTT DATA’s baseline AI Readiness Assessment an important starting point. It’s the bridge that connects your high-level business use case to a clear technical blueprint — the practical plan for the infrastructure and systems you need.

Even if you’ve already done high-level strategic or transformation work with a consultant, this assessment remains vital because it looks beyond your business goals to check if your infrastructure can support these goals.

What we do: The baseline focus

Our assessment quickly gives you a high-level view across multiple areas in your IT environment.

• Use-case validation and translation: We translate each business case into a high-level technical focus area. This helps us establish which part of your technology stack needs to evolve first to make your business case possible.
• Domain alignment: We review all your technical domains — security, your data center, network, computing, storage and observability — to provide a broad view of your environment and ensure no critical area is overlooked.
• Strategic handoff: This baseline report gives you the information you need to take the next step. If a deeper dive into your technical domains is required, we run an advanced, domain-specific assessment for each domain. For example, if network performance is the biggest risk, we recommend an advanced data center networking assessment.

The outcome: Stop guessing, start building

Once you’ve completed your Baseline AI Readiness Assessment, you’ll have:

• A clearer focus: You remove the guesswork by isolating one or two critical infrastructure areas that need immediate attention to move forward with your use case.
• A stronger stance on risk: The baseline report gives you a broad view of the security and compliance risks associated with introducing AI workloads into your IT environment.
• An accelerated roadmap: You move from an abstract business goal to a concrete, prioritized technical roadmap that is ready for implementation.

In the AI era, infrastructure is strategy. It determines how fast you can innovate, how reliably you can scale and how effectively you can compete. It’s no surprise that 96% of C-suite leaders are confident AI will accelerate market-differentiating innovation. The vision is there — and under the right circumstances, with the right infrastructure partner, it can become a reality. Don’t let legacy infrastructure hold you back.

Ready to get started?

Get in touch to take our Baseline AI Readiness Assessment, define your technical focus and turn your AI ambitions into a prioritized, enterprise-ready roadmap.

If further analysis is needed, we continue with targeted deep-dive assessments focused on each technical domain, ensuring that every area is optimized for AI readiness.

This article was co-authored by Ralf Hustadt, Director: Data & AI Go-to-Market at NTT DATA.