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Not long ago, I sat down with a senior executive at the world’s largest soft-drink maker to chat about the future of manufacturing. More specifically, what it takes to modernize a global production and supply operation, spanning legacy plants, evolving customer demands and a digital workforce that’s still finding its footing.

Over the course of the conversation, what stood out to me was their mindset. For them, modernization was how they built resilience into every process. That is, their aim was to recover when things went wrong, yes. But equally important to them, if not more so, was the ability to move faster when things went right.

That mindset is at the heart of what I believe responsible innovation looks like in the AI era. It’s about building the kind of enterprise that’s ready to take advantage of the full potential of AI, and that is strong enough to do so securely and at scale.

Let me show you what that looks like in practice.

Operational resilience means both being recovered and being ready

The soft-drink manufacturer I mentioned earlier faced a significant transformation challenge. Their various plants varied significantly in the age and digital maturity of their infrastructure and processes. Similarly, their people had different levels of fluency with new tools. And their supply chain had to move quickly in a standardized and consistent way. 

Their answer was a unified approach, a common operational model that let them roll out standardized processes across more than a dozen manufacturing sites. That made their cloud and AI investments far more impactful. Their modernization enabled smarter order-taking, laid the groundwork for AI-enabled deployment of new soft-drink recipes and built digital agility into their operations.

That agility is precisely what strengthened their resilience. Because in their view, resilience meant moving forward confidently and consistently, with the infrastructure to support it.

Responsible innovation requires digital transformation

AI is foundational to digital modernization for manufacturers because it enables cutting costs and improves uptime. But it also removes friction so innovation can happen faster. That’s something I’ve seen clearly in our work with a global logistics leader.

This organization had decades of technology layered across their global footprint. Some of it was aging, including components that were business-critical. Rather than overhauling everything at once, they focused on building a modern digital core. They established an AI-ready infrastructure with hybrid cloud flexibility and secure, intelligent data flows.

Now, they’re using that modern foundation to launch new digital services and streamline product development. They can also connect with their customers more effectively, enabling predictive, real-time insights. The point is that innovation can build on new ideas if — and this is key — the ideas are executable and scalable within a secure, adaptable environment.

Agentic AI is already here, and it’s already acting

When we talk about AI, especially agentic AI, we’re talking about systems that can analyze and then act autonomously based on their analysis. Those systems are already being deployed in the physical world.

A great example is what we’re doing with a global mobility manufacturer. Together, we’re building an AI-powered platform that enables autonomous vehicles and infrastructure to interact in real time. The goal is to achieve zero traffic fatalities.

This platform uses distributed edge computing, predictive AI models and real-time environmental sensing to make context-aware decisions. The system might slow a vehicle down before a blind corner or reroute it entirely. It’s not theoretical. It’s deployed. And it shows clearly that when we build AI systems responsibly, they can operate safely and autonomously in high-stakes environments.

Innovation without AI-enabled security isn’t innovation at all

Of course, none of this matters if the foundation isn’t secure, and our recent global research on GenAI adoption revealed a clear disconnect. While CEOs are moving ahead rapidly with investments, CISOs are sounding the alarm. Only a small fraction of organizations feel confident in their governance frameworks. The rest are still figuring out how to deploy GenAI responsibly without exposing themselves to unnecessary risk.

The reality is that the manufacturers I speak with every day have an abundance of excitement and ambition. What they need more of is alignment. Security leaders need to be involved from the start, as gatekeepers and as co-architects. Responsible AI adoption can’t happen if cyber resilience is treated as an afterthought. It has to be baked in.

Modernization is the most responsible move you can make

If there’s one thread running through all these stories, it’s this: Innovation starts with modernization. It might be flashy, it might be headline-worthy, but first it must build long-term capacity, clarity and confidence.

When you modernize responsibly, you upgrade your tech stack and empower your teams. You shorten the time from idea to execution. And you give your enterprise the resilience, flexibility and intelligence it needs to thrive no matter what’s ahead.

That’s what responsible innovation looks like. And that’s what we’re building for our clients.

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For a deeper dive on this discussion, download NTT DATA’s The executive’s guide to successfully navigating the supply chain.