Qualtrics claims it’ll spend $500M on AI over the next four years
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 with the launch of its new AI integration platform, XM/os2 (a tricky name, of course), which provides generalized 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,”
“It’s the most important innovation in experience management since we launched the category in 2017.”
Qualtrics CEO Zig Serafin.
Details of Qualtrics’ investment, up to $125 million annually for the next four years, are particularly hazy.
It’s unclear how this round will be split between the company’s business divisions — and the specific internal efforts it will fund for that matter. We ask for clarification. But assuming that happens, Qualtrics’ investment is the latest example of a tech giant injecting huge amounts of capital into a booming AI portfolio.
Salesforce Ventures, the venture capital arm of Salesforce, plans to pour $500 million into startups developing generalized AI technology. Venture capital firm Sapphire Ventures has earmarked over $1 billion for AI startups. Workday recently added $250 million to its existing venture capital fund, specifically to support AI and machine learning startups. And AWS said a few weeks ago that it was aiming to invest $100 million in a funding program for innovative AI initiatives.
Meanwhile, Accenture and PwC have announced plans to invest $3 billion and $1 billion in AI respectively, ahead of SAP’s investments in leading AI companies like Anthropic, Cohere, and Aleph Alpha. McKinsey estimates that AI could add $4. 4 trillion a year to the global economy, roughly equivalent in economic terms to adding an entire new country the size and productivity of the UK ($3.
1 trillion GDP in 2021) to the world. But other strategists say the AI boom won’t lead to huge profits, warning that the hype reflects the tech bubble of the 1990s.
