Qualtrics, the cloud-based platform for managing online customer experiences, intends to spend $500 million on AI over the next four years.

The company made the announcement this morning alongside the launch of its new AI-integrated platform, XM/os2 (an unwieldy name, to be sure), which offers generative AI solutions tailored to enterprise experience management use cases.

“For the very first time, we’re bringing the power of generative AI to every part of our platform,” Qualtrics CEO Zig Serafin said in a press release. “It’s the most important innovation in experience management since we launched the category in 2017.”

The details of Qualtrics’ investment, which amounts to $125 million per year over the next four years, are exceptionally vague. It’s unclear how the tranche will be divided among the company’s business divisions — and which specific internal efforts it’ll fund, for that matter. We’ve asked for clarification.

But assuming it happens, Qualtrics’ investment is the latest example of a tech giant pouring huge amounts of capital into the exploding generative AI category.

Salesforce Ventures, Salesforce’s VC division, plans to funnel $500 million to startups developing generative AI technologies. VC firm Sapphire Ventures has set aside over $1 billion for enterprise AI startups. Workday recently added $250 million to its existing VC fund specifically to back AI and machine learning startups. And AWS a few weeks ago said that it aims to put $100 million into a program to fund generative AI initiatives.

Accenture and PwC, meanwhile, have announced that they plan to invest $3 billion and $1 billion, respectively, in AI, ahead of SAP’s investments in major AI players Anthropic, Cohere and Aleph Alpha.

McKinsey estimates that generative AI could add $4.4 trillion annually to the global economy, almost the economic equivalent of adding an entire new country the size and productivity of the U.K. ($3.1 trillion GDP in 2021) to the world. But other strategists say that the AI boom won’t lead to massive profits, warning that the hype mirrors that of the tech bubble of the 1990s.

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