Saudi Arabia is fast emerging as the next big hub for artificial intelligence infrastructure, fueled by its massive energy reserves, Groq CEO Jonathan Ross said, positioning the kingdom as a key player in the global AI race.
The kingdom’s abundant energy resources have made it an attractive destination for major tech companies, many of which are now unveiling large-scale infrastructure projects in the region. These initiatives align with Saudi Arabia’s Vision 2030, an ambitious roadmap aimed at transforming its oil-dependent economy into a diversified, innovation-driven powerhouse.
In an interview with CNBC’s Dan Murphy at the Future Investment Initiative (FII) conference in Riyadh, Ross said Saudi Arabia’s energy advantage could enable it to evolve into a global exporter of data, positioning the Kingdom as a central player in the next wave of AI infrastructure development.
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“One of the things that’s hard to export is energy. You have to move it, it’s physical, it costs money. Electricity, transporting it over transmission lines is very expensive,” he said.
Speaking about the data, “is very cheap to move,” Ross, who earlier worked on AI chips at Google’s parent company Alphabet, added. “So since there’s plenty of excess energy in the Kingdom, the idea is move the data here, put the compute here, do the computation for AI here, and send the results.”
“What you don’t want to do is build a data center right next to people, where it’s expensive for the land, or where the energy is already being used. You want to build it where there isn’t, where there aren’t too many people, where the energy is underutilized. And that’s the Middle East, so this is the ideal place to build out.”
PwC estimates that artificial intelligence could add as much as $320 billion to the Middle East’s economy and Saudi Arabia is determined to seize that opportunity, making AI a core pillar of its long-term growth and modernization plans.
The CEO of Humain, a state-backed AI and data center company collaborating with Groq earlier told CNBC that the firm aims to become the “third-largest AI provider in the world, behind the United States and China.”
Still, Saudi Arabia’s AI ambitions come amid intense regional competition, particularly from the United Arab Emirates, which has so far taken the lead in advancing AI adoption. PwC projects that by 2030, AI could add around $96 billion to the UAE’s economy (13.6% of its GDP) and about $135 billion to Saudi Arabia’s (12.4% of GDP). If these forecasts hold, the UAE could edge out its larger neighbor, leaving Saudi Arabia in fourth place on the global AI stage.
Yet, Saudi Arabia’s climate and talent landscape pose real challenges to its AI ambitions. Data centers require heavy cooling and significant water resources, a difficult feat in one of the world’s hottest and driest regions. On top of that, the Kingdom continues to grapple with a shortage of tech and AI specialists, though government initiatives aimed at upskilling the local workforce are steadily gaining momentum.
Despite those hurdles, Saudi Arabia’s momentum in AI shows no signs of slowing. Groq has partnered with Aramco Digital, the tech division of Saudi Aramco, to develop what it calls the “world’s largest inferencing data center.”
Ross noted that chips, manufactured in upstate New York are purpose-built for AI inference, the process of deploying trained models into real-world applications.
Earlier this year, the California-based firm received $1.5 billion in funding from Saudi Arabia to scale its operations and deepen its presence in the region. Groq is also contributing to the Saudi Data and AI Authority’s efforts to build its own large language model, further cementing the kingdom’s growing footprint in the global AI ecosystem.
“It’s optimized for interfacing with the kingdom, so if you need to be able to ask about something here, it has all the data that you need to get the appropriate answers. Whereas other LLMs haven’t been tuned, they don’t have access to a database that’s as rich with information about the local region,” Ross said.
As nations increasingly harness AI, the push for localized data has become crucial. Many countries are realizing that models trained primarily on English-language datasets from industrialized economies often fail to reflect their own cultural, linguistic, and social contexts underscoring the growing importance of developing region-specific AI systems.