HP Enterprise Reports Solid Results in Q3

HP Enterprise (HPE) has posted strong results in the third quarter, driven by robust growth in its networking business and rising demand for high-performance computing and generative artificial intelligence hardware and services.

Financial Performance

For the fiscal third quarter, which ended on July 31, HP Enterprise reported revenue of $7 billion, representing a 1% increase from the same period last year. After adjusting for currency effects, the revenue growth stood at 3.5%, aligning with Street estimates.

On an adjusted basis, HPE's earnings per share came in at 49 cents, surpassing both the company's guidance range of 44 to 48 cents and the Street consensus of 47 cents. According to generally accepted accounting principles, the company earned 35 cents per share, exceeding Street estimates by two cents.

Outlook for the Fourth Quarter

Looking ahead to the fiscal fourth quarter ending in October, HP Enterprise forecasts revenue in the range of $7.2 billion to $7.5 billion. Although the midpoint of this range slightly falls below the Street consensus of $7.47 billion, it still reflects HPE's confidence in its future performance. The company expects profits for the quarter to range between 48 and 52 cents per share, with the midpoint surpassing the consensus of 49 cents.

Full-Year Revenue Growth and Projected Profits

HP Enterprise reiterates its forecast for full-year revenue growth, anticipating a rise of 4% to 6%. Furthermore, the company maintains its projection of 35% to 45% compounded annual growth in annualized recurring revenue through fiscal 2025. In the third quarter, ARR reached $1.3 billion, signaling a significant increase of 48%.

Based on its current performance, management now expects full-year profits to range between $2.11 and $2.15 per share. This revised forecast surpasses the previous estimate of $2.06 to $2.14 per share and represents an increase of three cents per share.

HP Enterprise's solid financial results underscore its successful strategy in meeting growing market demands and positions the company for continued success in the future.

HP Enterprise Reports Accelerated Demand in HPC and AI Segment

HP Enterprise (HPE) has announced a significant surge in demand for its High-Performance Computing (HPC) and Artificial Intelligence (AI) offerings. The company reported a "wave of demand acceleration" in this quarter, resulting in its largest-ever order book in this segment. It appears that customers are increasingly recognizing HPE's unique capabilities in powering exceptional AI performance at scale.

While HPE's HPC and AI business had flat revenue during this period, the company experienced a remarkable 50% growth in its intelligent edge segment, which includes its networking business. Adjusted for currency fluctuations, the growth stood at an impressive 53% to reach $1.4 billion, surpassing market consensus by approximately $100 million. Additionally, HPE's compute segment saw a revenue decrease of 13%, with storage revenue dropping by 5%.

During an interview, CEO Antonio Neri shared that all business segments witnessed sequential revenue growth. Notably, the intelligent edge segment now contributes 20% of HPE's total revenue, marking a doubling of its share over the past eight quarters. Furthermore, profits from this sector currently account for 49% of the company's overall earnings.

Neri also highlighted positive trends in HPE's storage and compute businesses. Although storage revenue declined compared to the previous year, it has shown sequential improvement over the last two quarters. Similarly, compute revenue is displaying signs of stabilization, with a noticeable boost in July relative to the levels recorded in April.

The surge in demand for AI-related hardware and services has significantly contributed to HPE's success. The company reported an impressive order book, double the pre-pandemic level, indicating the growing interest in AI initiatives across various industries. HPE has already begun fulfilling orders from start-ups engaged in developing large language models, enterprise companies seeking to refine foundational models, and other entities requiring AI-related inference capabilities.