— Abu Dhabi’s flagship AI Adopters event, Machines Can Think 2026, will bring together more than 20 leading AI researchers from over 12 countries and top executives from global Big Tech companies. The summit, organized by Polynome, will debut on 26-27 January 2026 at Park Hyatt Saadiyat.
The event will feature more than 50 keynotes, multiple partners, including Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), over 10 hands-on workshops, and immersive demo zones where attendees can interact directly with breakthrough AI technologies and meet the teams behind them. Aligned with the UAE’s strong AI infrastructure and its national 2031 AI strategy, Machines Can Think 2026 reflects the country’s broader ambition to advance real-world AI applications that power economies and societies.
The program comprises three dedicated tracks — Co‑Evolution, Tech, and C‑Level — addressing the human–AI interface, technical breakthroughs, and executive strategies for responsible, scalable adoption. Highlights include UAE Stargate: Building a National AI Fabric; Foundation Models and Infrastructure; AI for Life Sciences, AI for Talents and Computer Vision — “Machines Can See and Act,” showcasing advances that enable systems to perceive and operate in the physical world. With AI expected to add $100 billion to the UAE’s GDP by 2030 and Abu Dhabi building the world’s first AI-native government, the summit spotlights the country’s rapid rise as a global innovation hub.
AI thought leaders will take the stage throughout the two-day program, including Michal Valko, Chief Models Officer at a Stealth AI Startup; Manohar Paluri, VP of AI at Meta; Andrey Doronichev, CEO of Optic (an AI-native biopharma company); Marc Hamilton, VP of Solutions Architecture and Engineering at NVIDIA; and Serge Belongie, Director of the Pioneer Centre for AI, alongside other global innovators shaping the future of intelligent industries.
Alexander Khanin, Founder and CEO of Polynome.ai, said: “The UAE is rapidly solidifying its position as a global AI powerhouse, supported by major investments from both government and Big Tech players. In this environment, the Machines Can Summits have become a catalyst for meaningful dialogue between creators and decision-makers. As AI is projected to contribute US$320 billion to the region’s economy, our mission is to turn this potential into tangible progress, helping nations, industries, and innovators build sustainable, intelligent systems that advance the region’s global leadership in technology.”
Ivan Laptev, Professor of Computer Vision at MBZUAI and Co-Founder of Machines Can See, added: “Abu Dhabi is rapidly strengthening its position as a centre for advanced AI, and Machines Can Think 2026 exemplifies that momentum by bringing together leading researchers and practitioners from around the world. As the UAE continues to invest in cutting-edge infrastructure and talent, MBZUAI remains focused on driving excellence in AI knowledge creation, transfer, and application. Across computer vision, machine learning, natural language processing, and computational biology, our community is developing research that can meaningfully advance industries and society. This summit provides a valuable platform to share that work, deepen global collaboration, and contribute to Abu Dhabi’s emergence as a hub for the international AI community.”
Machines Can Think is part of the broader Machines Can Summits (MCS) series, where AI creators showcase technologies reshaping industries, cities, and lives. Building on the momentum of last year’s gathering, which welcomed 3,500 attendees from 82 countries, 105 speakers from 30 nations, and five country delegations, the 2026 edition is set to elevate the conversation even further.
This year, MCS will take place across two flagship events: Machines Can Think in Abu Dhabi and Machines Can See in Dubai, both designed to accelerate responsible AI development and adoption. The summit is also partnering with Women in AI for a dedicated panel featuring global leaders driving inclusion in the AI ecosystem.
