It was not too long ago that Artificial Intelligence was the stuff of research labs and sci-fi movies. Today, however, it is quietly becoming part of the infrastructure that can power our lives.

The scale alone is staggering: To take just one example of the growing complexity of LLMs, GPT-3 came with 175 billion parameters, and GPT-4 is estimated at 1.8 trillion. No wonder that, in just a few years, we have seen an exponential evolution from models that could barely autocomplete a sentence to systems that can now write code, draft policies and explain legal contracts. Add capabilities to deal with images, audio and logic, and it is evident that we are no longer building apps but plugging into intelligence.

Essentially, this shift is not about features, as much as it is about function – a wholly different way of getting work done. There was a time when we told machines exactly what we wanted them to do. Now, we ask. We prompt. We delegate. And AI figures out the rest.

In the enterprise, AI is already taking on operational loads. Banks are now using it to detect fraud patterns in real time. E-commerce firms use machine learning to forecast demand and recommend inventory shifts. And in Customer Service, AI can routinely handle queries at scale, reserving the human touch for the edge cases.

In day to day life, the changes are perhaps even more visible. From summarizing long articles to planning travel itineraries to rewriting clunky content – we now reach for AI the way we once reached for Google.

Yet, despite its growing presence in life and at work, our grasp of its impact remains uneven, at best.

Mustafa Suleyman calls AI “the most consequential wave ever,” urging us to treat it not as a tool, but as a new kind of digital species. Geoffrey Hinton warns us that “for routine intellectual work, AI will likely replace humans,” and suggests we pivot toward roles that rely more on dexterity, creativity, or emotional depth. Demis Hassabis cautions that we may be “overhyping AI in the short term but underestimating its long-term effects.” And Yuval Noah Harari reminds us that “intelligence is no longer something that belongs exclusively to biology,” urging societies to rethink how agency, ethics, and accountability will evolve in an AI-rich world.

So, where is all this headed?

In the coming years, we will likely see smaller, specialized models trained for specific industries gain a foothold – think legal assistant, radiologist, or financial analyst. We will also see multi-modal systems that can effortlessly handle text, visuals and voice, as seamlessly as we switch between apps. An optimistic view also suggests that lightweight, on-device models may be able to offer real-time help without compromising on our privacy. And finally, AI-powered dashboards won’t just show us what happened, but acquire the ability to tell us what to do next.

For most of us, I know it can be tempting to get all swept up in the hype, or simply push it all away for another day.

But the real opportunity lies somewhere in between. To engage with these tools. To understand how they are changing the shape of work. And to imagine what may be possible when intelligence starts working as infrastructure, hand in hand with us.