Good morning. Global spending on AI infrastructure is expected to reach a whopping $31.6 trillion through 2050, according to projections from PricewaterhouseCoopers.
Right now, annual data center capital expenditure lands roughly at $800 billion, but that's expected to increase to $1.8 trillion in 2050.
This spending is unique for a number of reasons, besides the eye-popping numbers. For one, unlike traditional infrastructure booms-which taper off after the initial build-out-AI infrastructure investment is expected to accelerate, according to PwC' s Global Data Centre Outlook. That's because data center equipment like servers and GPUs needs to be refreshed every few years.
Of course, that's good news for chip giant Nvidia, which is still riding high from a blowout quarter last month. Recurring upgrades for chips, rather than construction, will drive most of its projected long-term capital investment, PwC said.
What does this mean for enterprises? One risk for companies, as we see it in the scenario PwC outlines: the revenue AI generates has to keep rising, which means adoption must keep pace.
Companies need to keep using, buying and seeing the ROI from the technology, in order to maintain the levels of investment required. If adoption stalls or pricing weakens, then the later years of the build-out will become harder to fund.
What's going on with data centers now? Tech giants including Amazon, Microsoft and Google have already committed billions to funding the data center build-out. But they're facing growing public backlash and political opposition to their plans.
Yet as my colleague Christopher Mims writes, there's actually a relatively straightforward way tech companies can address these issues: By slowing down the AI-infrastructure arms race and spending extra to build more modern, less noxious data centers.
Google Cloud, Accenture Launch Unit to Put AI Engineers On-Site
Google Cloud and Accenture are teaming up on the latest bet that forward-deployed engineers are key to unlocking business value from generative AI, the WSJ Leadership Institute's Isabelle Bousquette reports.
The companies have formed Accenture Gemini Enterprise Business Group, a new unit at the professional-services firm aimed at helping customers deploy Google Cloud's agentic AI platform.
As part of the arrangement, Google Cloud will help train up to 1,000 Accenture forward-deployed engineers, or FDEs, who will work with clients on-site to plan and build AI applications on the Gemini Enterprise platform. If this setup sounds familiar, that's because it is. The "forward-deployed engineer" model, popularized by Palantir, has become the go-to answer for turning AI investments into real business results, with OpenAI, Anthropic, Microsoft and AWS all rolling out similar programs recently.
The rush stems from a constant challenge. The ROI on enterprise adoption continues to be hit-or-miss, driven in part by companies struggle to integrate AI tools into corporate systems and customize them for specific business needs.
Companies also struggle with understanding how their business processes can be redesigned with AI and how to make organizational and labor changes as a result of that redesign, Google Cloud CEO Thomas Kurian tells the WSJLI. "There's a need for experts who can go and do these [things] for customers," he said.
Adds Accenture CEO Julie Sweet: "Clients want clear value and they're stuck."
The group will also include other experts from Accenture who will help scale FDE solutions and a small group of Google Cloud FDEs for limited engagements with top-tier customers.
Intelligence Layer
Earlier this year, fears that AI coding tools would make Salesforce and other corporate-software incumbents obsolete drove steep stock declines. But that so-called SaaSpocalypse hasn't materialized, says Heard on the Street's Asa Fitch.
Yes, AI has made it easier for companies to build new software and features from scratch, he writes, but coding agents still struggle with the less glamorous work of keeping existing software current and adapting it as business needs shift. The incumbents' deep integration with their customers' IT systems provides another bulwark against AI disruption. Meanwhile, Salesforce as well as ServiceNow, Snowflake and Workday have reported strong recent results, citing AI. The bigger long-term threats may be AI labs entering corporate software directly or AI-native startups.
On Our Radar
Apple kicks off its next launch cycle Sept. 9, with new CEO John Ternus taking the stage to unveil the latest devices, including a foldable iPhone, Bloomberg reports.
Mistral AI completed a new funding round led by Samsung Electronics that lifted the valuation of the French startup above $24 billion, the WSJ reports.
A new OECD study of 760,000 15-year-olds worldwide found that reading scores have dropped sharply over the past decade, a decline linked to AI tools and social media use, with students reading faster but less accurately and being less able to think critically.
The WSJ Technology Council
The WSJ Tech Council brings together CIOs, CTOs and CISOs advancing innovation and shaping the future. Join this trusted community where tech executives connect with peers to explore emerging trends and gain the perspective they need to stay ahead of disruption.
Request Information
About Us
Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute's new Executive Resilience series, where she's profiling America's top execs about their fitness and wellness habits.
Follow Belle Lin on LinkedIn and X for her latest reporting on enterprise technology and AI.
Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.
Tom Loftus is the editor of The Morning Download. He suggests following Isabelle, Belle and Steve on their various social channels. But if you insist, here's his LinkedIn.
Comments