We have our first question directly addressing Alphabet’s massive capex guide:
Goldman Sachs Group, Inc., Research Division
Two, if I could. Over the last couple of earnings calls, we’ve talked a lot about imbalances between demand and capacity for AI, both internally and externally. With the stuff function change in absolute capital dollars you’re projecting now in ’26, can you talk about the pathway to closing the gaps or the need for compute, both internally and externally and how to think about some of the outputs of closing that gap? As the year progresses. And again, the second part would be against that level of spend that you’re now projecting for ’26. How do you think about continuing to find operating efficiencies inside the business to fund those investment growth investments as well?
Chief Executive Officer
Thanks, Eric. You are right, and we’ve been supply constrained even as we’ve been ramping up our capacity. Obviously, our CapEx spend this year is an eye towards the future. And you have to keep in mind some of the time horizons are increasing in the supply chain, et cetera. So we are constantly planning for the long term and working towards that. And obviously, how we close the gap this year is a function of what we have done in the prior years, right?
And so there is that time delay to keep in mind. I expect the demand we are seeing across the board across our services, what we need to invest for future work for Google Deep Mine as well as for cloud, I think, is exceptionally strong. And so I do expect to go through the year in a supply-constrained way. And maybe [indiscernible] can touch on the second part.
Sure. Thanks, Eric, for the question. I’ve mentioned on 1 of the previous earnings call, our approach to how we look at efficiency and productivity and — we don’t view this as an episodic onetime project or effort, but rather how we run the business on a regular basis and always seek additional opportunities to drive efficiency across the business.
And certainly, with the demand we’re seeing, whether it’s from external customers or across the organization, the more capital we can free up within the organization to invest, the better we can turn this flywheel of making investments to drive future growth. And we’re doing this across the organization. whether it’s within our technical infrastructure, certainly, when we invest at these amounts, we look at how we can ensure that we are the most efficient with every dollar that goes towards our technical infrastructure.
There are scientific innovation that are with part of that process, technical innovation. As you know, and we’ve mentioned before, we primarily focus on construction of our own data centers. We do partner with some external parties on lease on occasion, but most of our data center, we can start ourselves, and we ensure that we do it in the most efficient way in a way that matches our workloads and our needs. We look at coating productivity that Sundar mentioned in the past are about 50% of our codes are written by agents, coating agents, which are then reviewed by our own engineers.
But certainly, it helps our engineers do more, move faster with the current footprint. We look at how we run the business across the organization to using AI within the business to drive daily operations. It can be all the way from the engineering team to small teams within our back office, even within my finance team, for example, we deployed agents within our treasury organization.
We’re deploying agents within how we run, how we pay and reconcile invoice, et cetera. So there are opportunities across the business that we evaluate on a regular basis to ensure we can free up more of that capacity to invest in our future.