QUALCOMM

AI Infrastructure & Edge-to-Cloud

Growth Sales Plan

COMMERCIAL STRATEGY

A platform-led growth plan for extending Qualcomm compute, connectivity and software into expanding AI markets.

Demand

›

Platform

›

Partnersh

›

Deploym

ent

›

Expansio

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029 GROWTH FRAMEWORK

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

01 Sales Plan Overview

Commercial growth beyond handset-centric markets

Central commercial objective:

Expand Qualcomm beyond handset-centric markets by commercializing AI

platforms across edge, automotive, industrial, IoT and data-center markets.

Qualcomm’s opportunity is to bring high-performance, power-efficient compute and connectivity to AI workloads

wherever they run: in devices, vehicles, factories, networks and cloud infrastructure. The commercial approach shifts

from component transactions toward platform engagements that align silicon, software, connectivity and ecosystem

support to customer outcomes.

Strategic priority

Commercial focus

Desired customer outcome

AI infrastructure

Engage cloud providers and infrastructure

companies on inference, custom silicon and

connectivity architectures.

Efficient, scalable AI infrastructure

designs.

Edge-to-cloud

Map workloads across endpoint, vehicle, facility,

network and cloud.

A fit-for-purpose compute continuum.

Vertical platforms

Lead with Snapdragon Digital Chassis,

Dragonwing and AI compute capabilities.

Reusable platforms mapped to sector

requirements.

Partnership-led selling

Coordinate OEMs, cloud, software and

system-integration ecosystems.

Faster validation and broader

deployment readiness.

Expansion

Land on a well-defined workload; expand across

adjacent functions and systems.

Growing platform adoption over the

customer lifecycle.

Strategic framework

Demand

›

Platform

Fit

›

Partner E

cosystem

›

Deploym

ent

›

Expansio

The sales plan prioritizes customer problem definition, architecture discovery and deployment conditions before

product selection. Success is measured through durable design adoption, workload deployment and subsequent

platform expansion—not isolated component placement.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

02 Edge-to-Cloud Growth Strategy

Qualcomm’s computing-continuum approach

AI compute is distributed across endpoints, vehicles, industrial sites, networks and data centers. Each location has

different constraints for latency, power, privacy, reliability, bandwidth and operating cost. Qualcomm’s commercial

role is to help customers place inference and processing appropriately across this continuum and connect those

layers through capable platforms.

Edge

Devices

›

Automoti

›

Industrial

& IoT

›

Networki

›

Data

Center

Layer

Workload considerations

Qualcomm platform/customer connection

Edge devices

Responsive, private, power-aware

inference close to the user or sensor.

Snapdragon-based devices and edge AI capabilities;

engage OEMs and software developers.

Automotive

Safety, real-time response, cabin

experience and vehicle lifecycle support.

Snapdragon Digital Chassis; collaborate with

automakers and tier-one ecosystem.

Industrial & IoT

Local control, machine vision, reliability

and long service life.

Dragonwing and IoT platforms; engage industrial

OEMs, integrators and operators.

Networking

Move data reliably between endpoints,

sites and cloud systems.

Connectivity and networking capabilities aligned to

customer infrastructure.

Data center

Scalable inference and infrastructure

performance, efficiency and

interconnect.

Custom compute and connectivity opportunities with

cloud and infrastructure partners.

Commercial implication

Qualify each opportunity by workload placement, data movement, latency, power envelope and deployment

environment. Position one layer as the entry point, then articulate the interfaces and adjacent workload opportunities

that make a broader continuum valuable.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

03 Data Center AI Infrastructure Strategy

Building an emerging infrastructure business around AI inference and connectivity

The data-center opportunity extends Qualcomm’s power-efficient compute heritage into large-scale AI infrastructure.

Customer conversations should begin with the workload mix—particularly inference—then address architecture,

silicon customization, memory and system interfaces, connectivity and deployment integration.

AI Worklo

ads

›

Compute

Architect

ure

›

Custom

Silicon

›

Connecti

vity

›

Data-Cent

er Deploy

ment

Commercial lever

Customer discussion

Strategic value

AI inference infrastructure

Throughput, latency, utilization, power and cost

per delivered workload.

Translate operational requirements into

architecture criteria.

Custom AI silicon

Workload-specific compute and system

requirements; design collaboration.

Align silicon design choices to customer

infrastructure priorities.

High-performance,

power-efficient computing

Performance per watt, thermal envelope and

data-center operating efficiency.

Address total-system constraints

alongside peak compute.

AI data-center connectivity

Scale-out topology, bandwidth, latency and

system communication.

Treat interconnect and networking as

integral to AI infrastructure.

Optical connectivity

High-bandwidth links and optical solutions within

evolving AI systems.

Support connectivity needs as

infrastructure scales.

Cloud-provider

partnerships

Co-design, validation, integration and

deployment readiness.

Build platform relevance through close

ecosystem collaboration.

Long-term growth framework:

more than

$15 billion

in Data Center revenue is a Qualcomm corporate FY2029

target. It is a company-level strategic target, not a sales-team quota.

Commercial sequence

Establish workload and architecture fit

→

align silicon and connectivity roadmap

→

validate in the target system

→

support deployment integration

→

expand to additional AI workloads and infrastructure programs.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

04 Enterprise AI Customer Strategy

Architecture-led engagements across infrastructure and operating environments

Relevant customer groups include cloud providers, large enterprises, AI infrastructure companies, technology

companies, data-center operators, industrial organizations, automotive manufacturers, robotics companies and IoT

customers. The engagement starts with the technical and operating requirement, not a predetermined component.

AI Requir

ement

›

Architect

ure Asse

ssment

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Qualcom

Platform

›

Deploym

ent

›

Expansio

Discovery should establish inference versus training mix, deployment location, performance and power envelope,

connectivity requirements, software stack, system integration responsibilities and the path from evaluation to

production. Architecture-led selling connects those needs with compute, connectivity, software and platform

capabilities.

05 AI Platform Portfolio

From individual silicon components to integrated platform value

Platform area

Technology role

Customer need

Commercial application

AI compute

On-device, edge and

infrastructure processing.

Efficient execution of AI

workloads.

Edge inference, AI-enabled

devices and infrastructure

designs.

Low-power

processing

Compute under constrained

energy and thermal budgets.

Performance within device and

system limits.

Mobile, IoT, automotive and

edge systems.

Connectivity

Wireless and wired

connectivity capabilities

across product domains.

Reliable data exchange and

connected experiences.

Connected devices, vehicles,

industrial systems and

networking.

Edge AI

Local processing near data

generation.

Responsiveness, bandwidth

efficiency and local operation.

Industrial vision, devices,

robotics and embedded

systems.

Data-center

infrastructure

Custom compute and

connectivity direction for AI

infrastructure.

Scalable, efficient AI systems.

Cloud and data-center

deployments.

Software and

developer tools

Framework enablement,

model optimization and

developer access.

Lower friction from development

to deployment.

Platform adoption and

application expansion.

Commercial positioning should make the system-level proposition explicit: silicon, software, connectivity, reference

capabilities and partner integration collectively solve a customer requirement. Specific platform selection remains

workload- and product-dependent.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

06 Automotive AI Growth

Expand from cockpit and connectivity into a broader software-defined vehicle platform

The Snapdragon Digital Chassis is Qualcomm’s automotive platform framework spanning digital cockpit, connectivity

and driver-assistance/autonomous-driving capabilities. Sales engagement should connect vehicle programs with the

lifecycle of in-vehicle compute, user experience and connected services, while working through automakers and the

automotive supply ecosystem.

Digital

Cockpit

›

Connecti

vity

›

ADAS

›

Automate

d Driving

›

Connecte

d Vehicle

Services

Opportunity area

Customer value conversation

Expansion angle

Digital cockpit

Responsive, connected in-vehicle experiences

and integrated compute.

Connect cabin systems with connectivity

and software-defined vehicle roadmaps.

Vehicle connectivity

Reliable links between vehicle, networks and

cloud services.

Extend platform engagement into

telematics and connected services.

ADAS

Compute and platform needs for

driver-assistance functions.

Coordinate system requirements and

integration with vehicle programs.

Automated driving

Longer-horizon compute, software and system

architecture requirements.

Build on customer roadmap and validation

milestones.

Cloud-connected

services

Vehicle data, updates and services across the

vehicle lifecycle.

Enable recurring service experiences and

connected ecosystem integration.

Qualcomm’s automotive strategy is built through collaborations with automakers and ecosystem partners;

commercial planning should attach claims to a documented program or public collaboration and avoid implying

unannounced awards, volumes or commitments. Cross-sell follows the customer’s platform roadmap rather than a

fixed sequence.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

07 Industrial AI & Robotics

Bring processing and connectivity closer to machines, operations and data

Industrial AI opportunities span automation, robotics, manufacturing, warehousing, machine vision, industrial

networking and edge systems. Dragonwing is Qualcomm’s platform brand relevant to industrial and edge AI

applications. Customer conversations should identify which decisions must occur locally, how systems connect to

existing operations and what integration conditions govern deployment.

Industrial

Requirem

ent

›

Edge AI

Platform

›

Connecti

vity

›

Deploym

ent

›

Connecte

d Operati

ons

Workload

Edge/industrial requirement

Sales approach

Machine vision

Process visual data near the production line

with suitable compute and network interfaces.

Map camera, inference, latency and

integration requirements.

Robotics

Coordinate perception, compute and

communications in mobile or fixed robotic

systems.

Engage robot OEMs, integrators and end

users around system design.

Manufacturing

automation

Support responsive processing alongside

existing control and operational systems.

Start with a bounded use case and

production integration pathway.

Warehousing

Connect mobile equipment, sensing and

operational workflows.

Assess coverage, device ecosystem and

local compute needs.

Industrial networking

Connect equipment and edge systems across

facilities.

Treat connectivity and device management

as part of the architecture.

On-premise and edge AI can place inference near equipment and operational data, helping address latency,

data-transfer and local-operation requirements where the workload architecture supports it. Deployment planning

includes system integration, software lifecycle, network readiness and production validation.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

08 IoT & Personal AI Growth

Address connected systems from industrial infrastructure to personal computing

Qualcomm’s IoT growth agenda includes industrial IoT, networking, robotics, AI PCs, personal AI devices, XR,

wearables and smart devices. Portfolio conversations should center on the experience or operating outcome, then

establish device compute, connectivity, AI processing and software requirements.

Market area

Customer requirement

Platform conversation

Industrial IoT

Connected sensing, local processing and

operational integration.

Edge compute, connectivity and industrial

platform design.

Networking

Connected infrastructure and high-capability

network endpoints.

Connectivity platforms and system integration.

Robotics

Perception, local inference and connected

operation.

Edge AI capabilities and robotics ecosystem

engagement.

AI PCs & personal AI

Responsive AI experiences with efficient

local compute.

AI compute, software support and OEM

ecosystem.

XR & wearables

Compact, connected, power-aware

experiences.

Integrated compute, connectivity and

developer ecosystem.

Smart devices

Useful connected experiences across

consumer and home settings.

Platform reuse across device classes and

applications.

Qualcomm corporate FY2029 IoT targets:

more than

$14 billion

total, comprising

$8 billion

from industrial,

networking and robotics and

$6 billion

from personal AI and compute. These are corporate targets, not individual or

team quotas.

Sales implication

Use portfolio breadth to develop adjacent opportunities while maintaining an explicit use case and deployment owner

for each design. Developer and OEM readiness are central to turning device interest into platform adoption.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

09 Strategic Customer & Ecosystem Partnerships

Coordinate the ecosystem required to commercialize platforms

Qualcomm’s platform model depends on collaboration across hyperscalers, OEMs, cloud providers, automotive

manufacturers, industrial technology companies, software companies and AI ecosystem partners. Partnerships

connect silicon roadmaps to operating environments, software stacks and customer deployment channels.

Partner group

Role in commercialization

Joint engagement focus

Hyperscalers & cloud

providers

Infrastructure requirements, cloud

integration and deployment ecosystem.

Workload architecture, silicon customization,

connectivity and validation.

OEMs

Product definition, system integration

and routes to market.

Platform fit, product roadmap, software and

launch readiness.

Automotive manufacturers

Vehicle program requirements and

lifecycle integration.

Digital Chassis capabilities, program

architecture and ecosystem coordination.

Industrial technology

companies

Automation, systems integration and

operational deployment.

Edge AI, connectivity and compatibility with

industrial environments.

Software & AI ecosystem

Frameworks, optimized models and

application availability.

Developer tools, model enablement and

production support.

A September 2026 multi-generational collaboration with Amazon was announced involving customized silicon and

optical connectivity for AWS AI infrastructure. The collaboration illustrates platform commercialization through

coordinated compute and connectivity capabilities. Commercial teams should describe only publicly announced

scope and avoid extrapolating private terms or deployment commitments.

Partnership operating principles

• Define a shared technical outcome and customer value case.

• Align platform, software and system responsibilities early.

• Use partner engagement to reduce integration friction and broaden adoption.

• Expand from validated workloads into adjacent programs when customer priorities support it.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

10 Solution Selling Strategy

Lead with the customer architecture and deliver an integrated platform response

Solution selling positions Qualcomm as a platform partner—not solely a chip supplier—by connecting compute,

software, connectivity and system integration to customer requirements. The sales team orchestrates technical

discovery and ecosystem alignment from evaluation through deployment.

AI Requirement

↓

Compute Architecture

↓

Qualcomm Silicon

↓

AI Software

↓

Connectivity

↓

System Integration

↓

Customer Deployment

At each stage, establish measurable engineering acceptance criteria, the customer decision process, integration

dependencies and the next validation milestone. Maintain traceability from workload to architecture to selected

platform capabilities. The platform proposition is strongest when it addresses system-level trade-offs and provides a

credible deployment path.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

11 Customer Expansion & Cross-Selling

Solution pathways for growing platform presence

The pathways below are repeatable expansion logic for customer conversations, not prescriptive account plans.

Progression depends on customer architecture, product roadmap and validation.

Vertical

Solution-expansion pathway

Automotive

Automotive Customer

→

Digital Cockpit

→

Connectivity

→

ADAS

→

Autonomous Driving

→

Cloud

Services

Enterprise AI

Enterprise AI Customer

→

AI Infrastructure

→

Custom Silicon

→

Networking

→

Optical

Connectivity

→

Additional AI Workloads

Industrial

Industrial Customer

→

Edge AI

→

Industrial IoT

→

Robotics

→

Computer Vision

→

Connected

Operations

12 AI Software & Developer Ecosystem

Make platform capabilities accessible from development through deployment

Software and developer enablement influence where models run, how efficiently they execute and how quickly

applications reach production. Qualcomm’s software strategy connects developer tools, model optimization,

frameworks, edge inference, agentic AI initiatives and cloud integration with its compute platforms.

Develo

pers

›

Softwa

Tools

›

Optimi

zed

Models

›

Deploy

ment

›

AI Wor

kloads

›

Platfor

m Ado

ption

Qualcomm’s 2026 acquisition of Modular adds software technology and expertise relevant to its broader AI software

strategy. The commercial opportunity is to reduce friction between model development and efficient execution across

Qualcomm platforms, while working with framework, cloud and application partners.

Sales engagement should establish developer workflow, framework compatibility, model performance goals,

deployment location and ongoing update requirements. Software readiness is an adoption lever: stronger tooling and

optimization can expand the pool of workloads suited to Qualcomm platforms.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

13 Global Market Expansion

Align geographic engagement with sector demand and ecosystem readiness

Qualcomm operates across global technology markets. Commercial focus should reflect regional customer

ecosystems, product development footprints, infrastructure investment and deployment conditions, without assuming

uniform demand or assigning unsupported regional targets.

Market

Demand areas to assess

Commercial emphasis

North America

AI infrastructure, cloud capacity,

automotive platforms, edge computing.

Cloud and infrastructure engagement; OEM and

ecosystem coordination.

Europe

Automotive technology, industrial

automation, connected devices.

Automotive and industrial platform partnerships;

local integration readiness.

Asia-Pacific

Manufacturing, connected devices,

automotive and edge deployment.

OEM ecosystem coverage and industrial

use-case development.

China

Connected devices, automotive

technology, manufacturing and networking.

Customer-specific platform fit and ecosystem

engagement.

Emerging technology

markets

Digital infrastructure, connected systems

and industrial modernization.

Partner-led deployment models and practical

integration pathways.

14 Sales & Commercial Metrics

Use reported business performance and deployment indicators

Commercial reviews should connect company-level reported metrics to customer evidence: design engagement,

platform adoption, production deployment and growth in workloads or product lines. Reported figures below are

company performance or management expectations—not sales quotas.

Metric

Reported value

Label / period

Revenue

$9.9 billion

Qualcomm Q3 FY2026 revenue

Combined QCT Automotive and

IoT revenue growth

28% year over year

Reported year-over-year growth, Q3

FY2026

Non-handset revenue including

Data Center

More than 60% year-over-year growth

expected

Management expectation for FY2027

Design-win pipeline

Track by documented program stage

Commercial operating indicator; report

period with each review.

Platform adoption & deployments

Track design adoption, production

deployments and workload expansion

Customer and portfolio indicators; report

period with each review.

For each review, separate reported historical results from forward-looking management expectations. Pair financial

measures with leading customer indicators and describe metric definitions consistently.

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

15 FY2027–FY2029 Growth Framework

Qualcomm corporate targets provide direction for portfolio-level commercial expansion

The FY2029 figures below are Qualcomm corporate targets. They describe the company’s long-term growth

framework; they are not salesperson quotas, sales-team targets or guaranteed outcomes.

FY2029 corporate target

Strategic meaning

$40B

Non-handset revenue

Expand growth contribution across automotive, IoT, data center and other

non-handset markets.

>$15B

Data Center

Build an AI infrastructure business spanning compute, custom silicon and

connectivity.

$10B

Automotive

Scale automotive platform commercialization and vehicle-program adoption.

>$14B

IoT

Grow industrial, networking, robotics and personal AI/compute markets.

Approximately one-third

Handsets as a share of QCT revenue

Reflect a more diversified QCT revenue mix as non-handset businesses expand.

Target composition: IoT includes

$8B

from industrial, networking and robotics and

$6B

from personal AI and

compute. The commercial planning implication is to balance near-term design conversion with sustained investment

in platform adoption across these growth engines.

16 Customer Growth Execution Flow

Close the strategy with a repeatable customer-to-platform sequence

01 AI Market Opportunity

↓

02 Target Customer Identification

↓

03 AI / Compute Requirement

↓

04 Qualcomm Platform Selection

↓

05 Silicon + Software + Connectivity

↓

06 Strategic Partnership

↓

07 Customer Deployment

↓

08 Production AI Workloads

↓

QUALCOMM | AI INFRASTRUCTURE & EDGE-TO-CLOUD GROWTH SALES PLAN

GLOBAL COMMERCIAL STRATEGY • FY2027–FY2029

09 Platform Expansion

↓

10 Long-Term Customer Growth

This sequence links market demand to architecture, ecosystem participation, deployment and expansion. It gives

commercial teams a common structure for progressing customer opportunities while keeping each engagement

grounded in validated requirements and platform fit.

Qualcomm AI Infrastructure & Edge-to-Cloud Growth Sales Plan

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