Saudi Arabia's AI Aspirations Shine At Deepfest 2025

2025-02-12 12:58:37

(MENAFN- The Arabian Post)

DeepFest 2025, held from 9 to 12 February in Riyadh, has underscored Saudi Arabia's burgeoning role in the global artificial intelligence arena. The event, co-located with the LEAP technology conference, attracted over 48,000 AI enthusiasts, including thought leaders, data scientists, and innovators from around the world.

The Kingdom's significant progress in AI was highlighted by its ascent to the 14th position globally in the 2024 Global AI Index, making it the leading nation in the Arab world. This leap of 17 places from the previous year is attributed to substantial government investment and a clearly defined AI roadmap led by the Saudi Data & AI Authority .

Joe White, senior data analyst at Tortoise Media, described Saudi Arabia's advancement as“really impressive,” noting the government's commitment of $40 billion to AI initiatives. This investment is unparalleled and reflects the Kingdom's ambition to position itself as a global leader in AI development.

Despite these strides, experts emphasize the importance of diversifying efforts beyond state-led initiatives. White cautioned that an overly centralized approach might limit broader innovation, suggesting that authorities should consider investing in building talent and enhancing the operating environment to broaden the ecosystem's potential.

To address the talent gap, SDAIA has launched several initiatives, including bootcamps in data science and AI. In September, during the Global AI Summit in Riyadh, the authority announced a partnership with UK-based educational company Pearson to boost local capabilities in AI and digital fields.

DeepFest 2025 showcased the latest innovations across various sectors, featuring a thought-leadership conference, sector-dedicated tracks, live demonstrations, and an exhibition of the world's top AI companies. The event highlighted advancements in robotics, generative AI, customer experience, machine learning, automation, and large learning models.

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