DIGITIMES observes that Qualcomm has strengthened its capabilities in self-developed CPUs, cross-platform integration, and cloud AI-oriented application-specific integrated circuits (ASICs) through a series of acquisitions. This strategy allows Qualcomm to gradually extend its AI deployments from the edge to the cloud, shifting from traditional system-on-chip (SoC) architectures toward more flexible, modular designs.
Over the long term, this approach positions Qualcomm to challenge the high-end cloud AI accelerator market; however, whether it can penetrate the mainstream remains uncertain. Key determinants include the maturity of high-speed interconnect and chiplet integration technologies, as well as cloud service providers' (CSPs) willingness to adopt non-GPU and proprietary computing platforms.
Although mobile business has long accounted for the majority of Qualcomm's revenue, slowing demand has prompted the company to actively pivot toward AI PCs, automotive, Internet of Things (IoT), and cloud AI ASIC deployments.
Chart 2: Three key transformation strategies via six major acquisitions in five years
Chart 3: Four phases of Qualcomm in-house processor core development
Chart 4: Three key factors prompting Qualcomm to restart Oryon R&D
Chart 5: Timeline of Qualcomm's Oryon multi-platform architecture integration
Chart 6: Qualcomm from acquisitions to build edge and CSP ASIC soltuions
Chart 7: Qualcomm acquisition of Alphawave for cloud AI ASIC
Chart 9: Qualcomm product lineup for edge devices, inference and AI training ASIC
