AMD Chair and Chief Executive Lisa Su has forecast that the number of global daily AI users will swell from about 1 billion today to around 5 billion by 2030, underscoring her expectation that AI will become nearly ubiquitous worldwide within the decade. Su made the remark during her address at the AMD AI Developer Day in Shanghai, part of a broader push to position the company at the center of the fast‑expanding AI‑compute ecosystem.
In her Shanghai speech, Su outlined a five‑year trajectory in which AI adoption accelerates from roughly 1 billion people using AI tools each day to 5 billion by the end of 2030. She described this shift as a move toward an “agent‑style” AI era, where software agents increasingly handle routine tasks and decision‑making steps, broadening the role of general‑purpose processors such as CPUs alongside dedicated AI accelerators. Su emphasized that this evolution will elevate the strategic importance of CPUs in managing AI‑driven workflows across consumer and enterprise environments.
Su’s user‑growth forecast aligns with AMD’s broader market outlook, including previously stated expectations that the AI data‑center market could reach about 1 trillion dollars by 2030. In earlier investor commentary, she has also highlighted rising demand for both GPUs and CPUs, noting that the conventional assumption of a heavily GPU‑weighted compute mix has shifted toward a much more balanced GPU‑to‑CPU ratio as AI agents become more prevalent. AMD has more than doubled its long‑term server‑CPU market‑size estimate, now targeting a total addressable market exceeding 120 billion dollars by the end of the decade.
The 5‑billion‑users projection, if realized, would place AI‑enhanced services and devices within reach of a majority of the world’s population, reflecting Su’s view that AI will touch most major industries and everyday applications. For AMD, the forecast reinforces its strategy to expand its AI‑focused product portfolio across data centers, AI‑PCs, and edge devices, while leaning heavily on CPUs and custom compute platforms as complementary engines to specialized AI chips.
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