How can you start an article about artificial intelligence in an interesting or unique way? After all, AI has dominated discussions in the business world for the past two years, leading to so much speculation about what it can do, what it will do and the impact it will have on organisations and their people.

Still, month by month, the conversation evolves. We’re at the stage where very few leaders need to be told that AI is reshaping – and will continue to reshape – how businesses operate, create, and compete. So, there’s a lot to be said for diving deeper into how that unfolds, be it by industry, job function or business outcome.

But that’s not of interest to me as I write this piece. I am less interested in how an organisation uses AI; for me, the question is how an organisation builds with AI, and how it embeds AI into the fabric of how it creates, operates and makes decisions. In other words, the journey to becoming “AI-native”.

By AI-native I mean organisations that put AI at their core, using the technology in an instrumental way within their product, service, operations and strategy, allowing it to shape how their learn, iterate and grow. But I’ll elaborate on that in more specific terms a little later.

Beyond experimentation

Right now, many organisations are stuck in the experimental phase of AI adoption. They’re dipping their toes in the water, running pilots, testing chatbots, or automating small pieces of their workflow. And on the fringes, away from official AI implementations, individual employees are also trying out different AI tools.

Much like the early days of digitalisation, when websites and mobile apps were treated as optional add-ons rather than integral parts of business, AI is still often seen as a tool to enhance existing processes. The real value emerges when it becomes part of a company’s DNA, shaping how products are conceived, designed, and delivered from the ground up, and transforming the broader strategy, operations and decision making.

To that end, it has been positive to see a marked shift in recent months in this regard. Businesses are moving from seeing AI as a solution to isolated challenges, and instead understanding it as an amplifier across virtually every team, from marketing and sales to product and tech.

This is the difference between adopting AI and making the leap to become “AI native”.

Understanding what it means to AI-native

As noted above, an AI-native organisation doesn’t just deploy AI tools on top of existing systems; it’s about so much more than tech stacks, it’s about integrating AI into every layer of what an organisation does and how it does it.

Amidst the explosion in AI solutions in recent years, to be AI-native is rare. There are so many off-the-shelf AI products that can easily be bolted on to solve specific pain points or overcome particular challenges that this remains the prevailing approach. And this is certainly true of mid- and large-size organisations, which typically attempt to integrate AI tools into their wider legacy IT systems.

To be AI-native means to weave AI into the core operating model so this intelligence drives how the business creates value and learns continuously.

Let’s take the example of a scaling mid-cap consumer goods business. Right now, they might be using AI in little pockets across the organisations – automated invoicing, a chatbot, a recommendation engine, and so forth. That’s helpful, but only realises a fraction of AI’s real potential.

If the consumer goods business thought in an AI-native way, the technology could be embedded across product development, operations and supply chain planning; customer insights could feel directly into new product launches; predictive analytics could help optimise inventory; the supply chain team can respond to peaks and troughs in demand. The point is that AI stops being purely about efficiency and becomes a force multiplier for smarter scaling, faster learning and better business outcomes.

A fintech startup would offer another clear case for becoming AI-native. It might currently use AI for customer support or basic automation. If AI-native, AI could be built into the operating model from those early stages, guiding product development, prioritising features, simulating growth strategies and optimising team workflows.

Acting strategically, not rashly

As with many technology trends, it often feels as though we’re in the midst of a gold rush. Organisations are trying to move at great speed, keen to gain a competitive advantage, or simply not get left behind.

Taking a pause for breath is sensible. We should not underestimate the leap that is required from the currently popular trend of viewing AI in isolated terms – specific AI-powered tools for particular pain points – to instead allowing AI to play an influential role in a business’ culture, operations and strategy.

Success won’t come from automation for its own sake. Nor will the adoption of piecemeal AI tools designed for very narrow purposes make a radical difference to productivity, quality or outcomes. No, it is becoming increasingly clear that those forging the way with AI are the ones rethinking how teams, tools, and ideas work together to create value.

The rise of the AI-native organisation isn’t a story about technology. It’s a story about human potential, amplified by intelligence that learns alongside us. The businesses that recognise this now, and build accordingly, will be the ones shaping the next generation of innovation.

Ritam Gandhi is the founder and director of Studio Graphene, a global digital product studio that turns ambitious ideas into AI-native products.