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Cadence Lifts Full-Year Forecast on Surging AI Chip Design Demand
Cadence Design Systems Inc. raised its annual revenue and profit forecasts, signaling robust and sustained demand for its software used in designing advanced semiconductors for artificial intelligence. The company's shares jumped more than 5% in extended trading on Monday following the announcement.
Upgraded Financial Outlook
The electronic design automation (EDA) provider now expects full-year 2026 revenue to be between $6.26 billion and $6.34 billion, an increase from its previous projection of $6.13 billion to $6.23 billion. This updated range places the midpoint above the analyst consensus of $6.21 billion, according to data from LSEG.
On a per-share basis, Cadence lifted its annual adjusted profit forecast to a range of $8.05 to $8.15. The prior guidance was $7.85 to $7.95 per share, while analysts had estimated an average of $7.96.
AI Boom Fuels Performance
The upgraded forecast reflects the intense demand from technology companies and chipmakers, including Nvidia and Apple, who rely on Cadence's tools to engineer increasingly complex systems-on-chip (SoCs) and AI accelerators. This trend was evident in the company's second-quarter results.
AdFor the quarter, Cadence reported:
- Revenue of $1.584 billion, a 24.2% increase year-over-year and largely in line with analyst estimates.
- Adjusted profit of $2.11 per share, surpassing the consensus estimate of $2.05.
A strong pipeline supports the positive outlook, with the company's quarter-end backlog standing at $8.1 billion. Cadence expects to recognize $4.2 billion of that backlog as revenue within the next 12 months, according to Reuters.
Context: Product Innovation
The company is actively investing to capitalize on the AI trend. Earlier this month, Cadence launched AuraStack, an AI-powered tool described as a "super agent" that allows engineers to use natural language to direct complex circuit design and testing processes. This innovation aims to streamline the development of next-generation chips that power the AI industry.
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