While smartphones, network equipment, and customer premises equipment will drive the 5G chipsets and devices market in the short term, says the firm, as connected devices and sensor adoption proliferate, 5G chipset suppliers will also be able to leverage growth from other verticals, such as automotive, healthcare, Industrial Internet of Things, and retail. As a result, the analysis forecasts the market to grow at a CAGR of 59.7% between 2019 and 2025, with revenues rising from $1.6 billion to $27.8 billion.
“5G chipset growth potential will be driven by smartphones and network infrastructure in the first wave of commercialization,” says Prabhu Karunakaran, Industry Analyst at Frost & Sullivan. “However, the market’s future growth will expand beyond the traditional markets, as the successful trials in retail, industrial, and automotive verticals suggest.”
The report analyzes all related market verticals and provides detailed shipment and revenue forecasts through the year 2025 for every segment. The report also identifies the key growth opportunities in the segment and provides strategic recommendations to leverage them.
Currently, smartphones are a major revenue contributor for 5G chipsets, accounting for a 35.4% share of the total 5G chipset market in 2019, with an estimated revenue of $595 million. This vertical, says the firm, is expected to grow significantly toward the end of 2020 and early 2021. Revenues from 5G smartphones have been forecast to reach $18.6 billion by 2025, growing at a CAGR of 77.5% from 2019.
“5G smartphone shipments are expected to begin with high-end devices, as announced by leading OEMs,” says Karunakaran. “However, volume shipments will gain momentum only from 2021, when mid- and low-end smartphones enter the market.”
5G chipset and device manufacturers, says the firm, can also explore the opportunities in the following areas:
- Providing a cost-effective solution for the deployment of a high-speed, low-latency network for industrial use
- Developing automotive-grade reliable devices and networks for autonomous vehicles
- Focusing on cost-optimized solutions that can process large volumes of data and communicate quickly
- Improving the AI and ML capabilities in system on chip (SoC) applications
- Developing power-efficient devices to enable high-volume data processing in real time
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