Qualcomm Targets $1.7 Trillion Agentic AI Market With Edge-First Chip Strategy at Investor Day

Qualcomm used its June 24 Investor Day to position agentic AI as the primary thesis for doubling its revenue by 2030. Management outlined a full-stack strategy treating agentic workloads as a distinct market segment separate from traditional data center inference, with a total addressable market of $1.7 trillion by the end of the decade, according to Futurum Group’s analysis of the presentations.

The Revenue Targets

Qualcomm guided to non-GAAP earnings per share above $18.00 for fiscal year 2029 and set a target to double overall revenue by 2030. The company identified multiple markets reaching inflection points simultaneously: agent-ready edge devices, data center infrastructure, automotive systems, industrial networking, and robotics, per Futurum Group.

Edge-Cloud Distribution Thesis

The strategic bet centers on AI compute distribution shifting away from centralized cloud toward edge and device-embedded architectures. Rather than competing directly with NVIDIA on data center GPUs, Qualcomm is positioning itself for the inference workloads that run on phones, vehicles, industrial controllers, and edge servers, where latency and cost profiles favor local processing over round-trips to hyperscaler data centers, according to the Futurum analysis.

Agentic workloads in particular benefit from on-device inference. An agent controlling a robot arm, managing a vehicle’s decisions, or running automation on a phone needs sub-second response times that cloud inference cannot reliably deliver. Qualcomm’s argument is that the silicon for these use cases looks fundamentally different from training-optimized data center chips.

What $1.7 Trillion Covers

The TAM figure encompasses the full range of Qualcomm’s target segments: mobile chipsets for agent-enabled smartphones, automotive processors, industrial and IoT controllers, networking infrastructure, and data center inference accelerators. The number reflects Qualcomm’s view that agentic AI creates new silicon demand across categories rather than concentrating in a single product line.

For semiconductor investors watching NVIDIA’s dominance in training and data center inference, Qualcomm’s bet is that the next wave of AI spending flows toward the edge, where its existing position in mobile and automotive gives it distribution that data center incumbents lack.