The application of artificial intelligence (AI) has now gone far beyond the generative era and has moved from a global disruptor to a catalyst for economic growth.

Across the world, governments are accelerating investments into infrastructure that will propel adoption and innovation, and research from Morgan Stanley estimates that nearly $3 trillion of AI-related investment will flow through the economy by 2028, with more than 80 percent of that spending yet to come.

At the center of this transformation is a realization that AI is no longer a tech story; it is a macro variable influencing GDP, earnings, credit markets and geopolitics on a truly global scale.

What is becoming increasingly clear is that this fourth industrial revolution will be built on secure, scalable and resilient foundations that enable the growth of physical AI and automation, and provide ubiquitous digital services.

As the race continues to gain pace, AI will not only drive a step-change in how critical systems such as buildings, data centers, industry and the grid are designed, built and operated, but in how software systems are developed - uniting energy technology, data and intelligence to deliver unparalleled benefits to everyone.

Propelling adoption

According to research from the RICS, today 82 percent of construction firms using AI plan to increase their budget, harnessing "industrial-scale AI" to improve project delivery and business intelligence. Gartner has also reported that worldwide spending on AI is forecast to total $2.52 trillion in 2026, a 44 percent increase Year-over-Year, with software, services, and AI infrastructure responsible for 94 percent of the spend.

To that point, there are now several AI use cases driving adoption globally, moving multiple industries from the generative to the physical era. In North America, for example, driverless cars are being utilized in 11 US cities, while autonomous delivery drones now cover another 50 of the country’s major locations - both leveraging edge AI and low-latency connectivity to process and automate operational data in real time, which is a key example of inference in action.

Meanwhile, in the APAC region, medical, therapeutic, and rehabilitative robots powered by AI are becoming increasingly common, helping healthcare professionals during surgical procedures and advancing patient care to speed up recovery.

In Europe, the EU Commission has also developed an ecosystem for AI innovation, built to create Digital Hubs with Testing and Experimental Facilities that leverage AI gigafactories to increase digital sovereignty. France, in particular, has strengthened its position with a major investment of up to €75 billion ($86bn), working with SoftBank Group and Schneider Electric to expand its AI infrastructure in support of European technological sovereignty and together propelled advanced data center manufacturing.

Data centers have indeed become the AI factories, or machine rooms of the future, providing the infrastructure, hosting, connectivity and compute needed to power these AI training and inference workloads. JLL, for example, predicts that the sector is experiencing an unprecedented investment supercycle, requiring up to $3 trillion of new funding by 2030.

By that same date, the company believes that AI could also represent half of all workloads - competing with the hyperscale cloud - and that inference could also become the primary driver.

With data centers at the heart of this new industrial revolution, and demand expected to rise between 19 percent and 22 percent by 2030, the growth of AI has also created a new and complex dynamic for renewables and grid capacity globally.

Power and the grid

With the scale of build-out now anticipated, the demand for AI is beginning to challenge the traditional concept of power grids – ensuring data centers can become active energy assets or prosumers that both generate and consume renewables. Research from Goldman Sachs forecasts that data center power demand will increase to 3-4 percent of global consumption by the end of the decade, but with the news that 40 percent of the increase is expected to be met by green energy.

As the grids of the future are built out, they too are becoming increasingly complex and digitalized, allowing them to become more intelligent and enhanced with AI, and enabling operators to use energy tech and data to gain deeper insights than ever before. Researchers at the World Economic Forum (WEF) have also identified a paradox that accompanies this opportunity, and that with just a one percent improvement in system flexibility – the kind of flexibility needed for data centers to move from consumers to prosumers – the US alone could unlock 100GW of power capacity.

Catalyzing a new industrial era

The implications for infrastructure now go well beyond progress on power, and novel approaches to physical infrastructure, equipment design and system architecture - as well as innovations in liquid cooling - have all contributed to the ability for data centers to deliver the foundational layers on which the new industrial revolution will be built.

Ultimately, the fourth industrial era is well underway, and data centers will be the machine rooms or factories of the revolution.

I, for one, remain an optimist and believe that through responsible data center developments, where energy tech, intelligence, software, and renewables coincide, we can enable positive societal impact through AI adoption.

By building sustainable, resilient, and scalable AI infrastructure responsibly, we can enable global economies and communities to benefit from the technology, in the same way that steam, steel, and electrification transformed the industrial revolutions of the past.