Innovative… or AI native? Which AI descriptor should enterprises actually seek out

In the AI race, innovation seems to be the imperative. ChatGPT’s meteoric rise demonstrated how quickly a new category could become a global phenomenon. But just as swiftly, the launch of DeepSeek showed how easily such an edge, built on billions in R&D, can be challenged.

This brings us to the truth about innovation: while it’s a descriptor every organisation would like to associate themselves with, it isn’t necessarily the most helpful.

Being innovative often implies being first. But in practice, the organisations that extract the greatest value from new technology are not always the first to adopt it, but rather, the ones that integrate it most effectively.

The real differentiator lies in using technology to enhance every process, every interaction, every decision. This is the essence of being AI-native. Yes, innovation may capture headlines, but integration captures enduring advantage.

We’re already seeing leaders begin to recognise this. The Government of Abu Dhabi’s recently announced AI-Native Strategy is a case in point. Rather than celebrating a handful of impressive AI use cases, their ambition is far broader: to build a fully AI-powered model of governance. It’s a bold, visionary move designed to make AI an invisible but integral part of how the government operates, supporting decision-making, improving service delivery and strengthening public trust.

Crucially, their plan includes a people-centric initiative, “AI for All”, aimed at empowering citizens with the tools and skills to engage confidently with AI applications. This emphasis on upskilling ensures that the transformation is not just technological, but human. By equipping people to participate meaningfully in the digital future, Abu Dhabi is redefining what it means to be truly AI-native.

Becoming AI-native starts with a shift in mindset. Too many organisations still view AI as a discrete tool — a platform to license, a feature to enable. But to harness its full potential, we need to see AI not as a product but as a partner. It’s less about which model you’re using and more about how you use it to elevate the way work gets done.

That shift begins with individuals. When people start asking, “How can I use AI to make me more effective at what I do?” rather than “Should I be using AI?”, that’s when transformation takes root. In this sense, the journey to AI maturity is as much cultural as it is technical. Organisations must create an environment where employees feel empowered to experiment, to question, and to learn how to get the best out of these new tools.

Much like electricity in factories or the advent of mechanised labour, AI compels us to rethink value itself. For many, it still feels like a useful assistant, something to help draft an email or summarise a document. But that view underestimates the shift already underway. Across industries, AI is increasingly shaping how work is executed and decisions are made. It’s no longer just supporting productivity. It’s beginning to define it.

Turning that mindset into meaningful action requires structure. Giving people access to powerful tools without guidance is like handing them a piano and expecting a symphony. Instead, success lies in creating the right conditions for safe, responsible experimentation. This means clear frameworks, training and governance that balance creativity with control.

In practice, that might translate to nurturing internal “AI champions” to lead by example, sharing insights and helping colleagues find practical ways to integrate AI into their workflows. It also involves embedding AI literacy across the organisation so that everyone (not just the technically inclined) understands its potential and its pitfalls. Governance is also essential. Far from being a brake on innovation, it is the foundation for trust. When employees know there’s a clear structure for using AI ethically and effectively, they’re more likely to embrace it.

When such structures are implemented, then AI can be built in rather than bolted on.

Of course, there’s no escaping the fact that there are technical aspects to becoming AI-native. And of these, one of the biggest challenges is modernising legacy systems. Many enterprises still operate on outdated infrastructures that simply weren’t designed for the demands of modern, data-driven intelligence. They’ve layered digital veneers over old cores, hoping that will suffice. But this approach only takes you so far. To truly unlock AI’s potential, organisations need to modernise from within.

Here again, Abu Dhabi is showing what leadership looks like. As part of its AI-Native Strategy, the government is deploying AED13 billion (US$3.5 billion) between 2025 and 2027 to build the foundations of a truly AI-driven economy. This includes the establishment of a robust digital infrastructure, a unified enterprise resource planning (ERP) platform, and 100% adoption of sovereign cloud computing for government operations. It’s a masterclass in aligning technological ambition with structural readiness.

For enterprises, the message is clear: AI cannot succeed on brittle foundations. Interestingly, AI itself can even accelerate this journey, using intelligent code analysis to understand legacy systems, identify inefficiencies and propose faster, smarter ways to rebuild. The results can be transformative as projects once thought impossible can suddenly move from concept to completion at unprecedented speed.

So, what does success look like in an AI-native world? It’s not about having the most sophisticated models or the flashiest applications. It’s about making AI so deeply embedded in your workflows that it becomes almost invisible, quietly amplifying productivity, accuracy and insight behind the scenes.

Take, for example, a cross-functional initiative where finance and legal teams collaborate to automate contract data extraction. On the surface, it’s a process improvement. But underneath, it’s a shift in how teams think, trust, and work with technology. They’re no longer waiting for innovation from above; they’re building it into the everyday fabric of their jobs.

Innovation will always matter. The world needs pioneers to expand what’s possible. But for most organisations, the real advantage won’t come from creating the next ChatGPT. It will come from deeply embedding such powerful tools into the flow of work, to the extent that they become invisible.

Becoming AI-native means rethinking culture, modernising infrastructure, and empowering people to lead with technology, not follow it. It’s a journey that requires patience, courage and vision. But history tells us this much: the future belongs not to those who innovate first, but to those who integrate best.

- The writer is the Chief Technology Officer at Endava