In a quiet first quarter for smartphone parts manufacturers, Apple iPhone maker Foxconn reported a 9.6% dip in revenue compared to the same period last year. The company’s first-quarter revenue was 1.32 trillion New Taiwan dollars, which was also 28.58% lower compared to the previous quarter and below economists’ expectations. Despite this, Foxconn still anticipates revenue growth in the second quarter, despite noting that it is a traditional off-peak season.
Following the release of the company’s figures, Foxconn shares were down 1.4% by the market close in Taiwan on Friday. The first quarter is typically a quiet one for smartphone parts manufacturers, with consumer appetite for handsets waning. There is currently no available data for smartphone shipments in the first quarter of 2024, but last year, overall shipments declined by 3.2% to 1.17 billion units.
Foxconn’s cloud and networking products were a bright spot for the company, with significant growth in this segment. The company saw “strong customers’ pull-in for the cloud segment, offsetting the negative impact from inventory digestion in networking products.” The Taiwanese technology giant is increasingly being viewed as a beneficiary of the recent buzz surrounding artificial intelligence, with its stock rising 14% in the past 12 months. However, it lags behind AI chipmaking grandee Nvidia, which has seen shares more than triple in the same timeframe. Foxconn’s shares have gained momentum of late, with a nearly 21% increase year-to-date.
Foxconn is an enterprise server maker for AI applications, with the cloud being a key technology powering today’s advanced generative AI. In March, the company put out a bullish forecast for revenues, anticipating a significant rise boosted by booming demand for AI servers. Foxconn is expected to hold its next earnings call on May 14. Last year, Foxconn and chipmaking powerhouse Nvidia announced a partnership to develop “AI factories,” a new class of data center using Nvidia chips to power a wide range of applications, including training autonomous vehicles, robotics platforms, and large language models.
