Cadence Design Systems (CDNS) Morgan Stanley Technology, Media & Telecom Conference summary

AI evolution and impact on EDA

• AI is following a similar innovation path as EDA, moving from brute-force computation to more efficient, partitioned, and latency-optimized methods.

• Compute demand is expected to rise for several years, driven by increased inference and domain-specific models.

• Workflow automation through AI is seen as the next major value driver in EDA, enabling faster and better design outcomes.

• AI's real value is expected to be realized in vertical applications rather than horizontal, with no single dominant model.

• Physical AI (cars, drones, robots) and science AI (life sciences, material science) are seen as future growth horizons.

Business performance and outlook

• Achieved 13.5% revenue growth and 42.5% operating margin in 2024, exceeding industry benchmarks.

• Provided a strong initial guide for 2025: 11.5%-12% revenue growth and 43.75% margin.

• Assumes flat growth in China due to regulatory uncertainty, with stronger growth ex-China.

• Design activity remains robust, with expectations of a market rebound in 2025 after two tough years for semiconductors.

• Record bookings and backlog signal strong future demand, with hardware segment driving growth.

Product innovation and technology strategy

• Hardware products like Palladium Z3 and Protium are critical for advanced system design, enabling emulation of trillion-transistor chips.

• Hardware releases have shifted revenue timing and set new industry standards for AI chip design.

• Investment in life sciences and digital biology is proportionate, serving as an option for future growth.

• AI-driven workflow automation reduces design cycles from months to weeks, improving both speed and quality.

• Focus on maintaining relevance across all AI phases and technology layers, including control theory and digital twins for physical AI.