Industry Weighs in With 2025 Forecasts—Part 1: General Predictions

On this New Years Day, we share 2025 predictions from leading companies in our industry.

Happy New Year! 2025 is here, and it’s a natural time to make some predictions about the year ahead. To help gather some insights, I reached out to several key companies in our semiconductor / electronics industry.

Image used courtesy of Adobe Stock (licensed).

You never know what to expect when you reach out to companies for predictions right before the holidays. So I sort of held my breath waiting for replies. 

Too Many Predictions for One Article

To my delight and surprise, I ended up getting over 3,000 words worth of predictions all totaled. That drove me to split my predictions article into two parts.

Here, in Part 1, I’ll share insights and quotes on general predictions. And in Part 2, posting later today, we’ll focus on predictions companies in our industry have about themselves.

With that in mind, we ask companies to answer the question:

What general predictions do you have for the electronics / semiconductor industry in 2025 and why?

These (in random order) are the responses:

Synaptics

“AI will permeate all aspects of the semiconductor and electronics value chains,” says a Synaptics spokesperson, “We see it moving out from the data center and closer to the user with AI on Edge devices, where it preserves user privacy while providing lower latency and incorporating multiple sensing modalities for greater context.”

“This context-aware computing will expand AI’s usefulness and provide users a more immersive, trusted, and personalized experience. AI at the Edge will be a key driver of growth and will have impact across consumer, enterprise and industrial IoT sectors.”

“It’s effective implementation requires a new breed of highly efficient and scalable processing and open software and development solutions in a dynamic partner ecosystem designed specifically for these operating and market requirements.”

“This will democratize AI at the Edge and accelerate its deployment across an increasing array of use cases and applications. This will be accompanied by increasing reliance on all kinds of IoT wireless connectivity, with evolving standards in both Wi-Fi and Bluetooth enhancing performance, range and security, the maturation of multi-protocol solutions to enable heterogeneous device connectivity, and differentiated offerings such as wireless sensing.”

Arm

For its part, Arm’s predictions center on chiplets and Moore’s Law.

Rethinking of Silicon design with chiplets

“From a cost and physics perspective, it is getting increasingly difficult to do traditional silicon tape-outs,” says Kevork Kechichian, EVP of Solutions Engineering, Arm. “The industry will need to rethink silicon designs and go beyond these traditional approaches. For example, there is a growing realization that not everything needs to be integrated on a single, monolithic chip, with new approaches like chiplets beginning to emerge as foundry and packaging companies find new ways to push the boundaries of Moore’s law, but under new dimensions.”

“The different implementation techniques of chiplets are getting more attention and having a deep impact on core architecture and micro-architecture.”

“For chiplets, architects will need to be increasingly aware of what different implementations offer, whether it's the manufacturing process node or the packaging technology, and then take advantage of the features for performance and efficiency benefits.”—Kevork Kechichian, EVP of Solutions Engineering, Arm.

“Chiplets are already addressing specific market needs and challenges, with this likely to advance in the years ahead. In the automotive market, chiplets can help companies achieve auto-grade qualifications during the silicon development process. They can also help to scale and differentiate silicon solutions through utilizing different computing components.”

“For example, chiplets focused on compute have a different number of cores, whereas memory-focused chiplets have different sizes and types of memories. So by combining and packaging these various chipsets at a system integrator level companies can develop a greater number of highly differentiated products.”

The Moore’s Law ‘recalibration’’

“Moore’s Law has put billions of transistors on a chip, doubled performance and halved power every year,” continues Arrm’s Kechichian. “However, this continuous push for more transistors, more performance and less power on a single, monolithic chip is not sustainable.”

“The semiconductor industry will need to rethink and recalibrate Moore’s Law and what it means to them. Part of this means moving away from solely focusing on performance as the key metric and instead valuing performance per watt, performance per area, performance per power and total cost of ownership as core metrics during silicon design.”—Kevork Kechichian, EVP of Solutions Engineering, Arm.

“There are also new metrics that focus on the implementation aspect of the system—which present the most challenges for development teams—and making sure performance is not degraded once the IP is integrated into a system-on-chip (SoC) and then the overall system.”

“Therefore, this will involve continuous performance optimizations during silicon development and deployment. These metrics are more relevant to where the wider tech industry is heading, as it pushes for more efficient computing for AI workloads.”

Analog Devices

AI moves closer to the edge.

“In the year ahead, we anticipate AI at the edge will further enhance applications and improve efficiency with increasingly specialized edge-AI chips that can enable tasks with lower power consumption,” says Rashmi Misra, Chief AI Officer at Analog Devices.

“AI techniques like TinyML and model quantization will continue to advance, allowing more sophisticated AI algorithms to run on resource-constrained devices. We expect more real-time speech recognition, computer vision, and predictive maintenance on small edge devices, along with more local data processing.”—Rashmi Misra, Chief AI Officer at Analog Devices.

“Current edge applications mostly use pre-trained models, but a move toward real-time, on-device training and fine-tuning will become more common. This means edge devices could adapt and learn from local data over time, improving performance and personalization without relying on cloud retraining.”

Avnet Silica

“Everyone in the semiconductor industry hopes this year will mark a turning point, with early signs of recovery and growth following a particularly challenging 18 months,” says an Avnet Silica spokesperson. “Key areas include artificial intelligence, particularly generative AI and machine learning, as enterprises race to adopt transformative solutions.”

“Analysts project an 8.3% global growth for 2025, driven by demand for AI-related chips, which will propel industrial and automotive applications. The fragility of global supply chains will drive a renewed focus on supply chain resilience and sustainability, with carbon footprint reduction becoming a priority.”

“Meanwhile, power efficiency will be front and centre for many markets and technologies, propelled by advancements in GaN (Gallium Nitride) and SiC (Silicon Carbide) technologies.”

AMD

For its part, AMD shared with us three predictions specifically focused on the automotive industry in 2025.

Centralized Computing becomes the dominant architecture in vehicles.

“With the rise of electric vehicles and innovative ADAS, safety, and infotainment systems — many driven by AI, the automotive industry is experiencing massive changes,” says Wayne Lyons, Senior Director of Marketing, Automotive Segment at AMD. “Size, cost, and power constraints, along with the desire to embrace the era of Software Defined Vehicle by enabling OTA updates, are driving automotive design to use more centralized computing architectures to consolidate ADAS and IVI functions and reduce complexity.

“Rather than have many intelligent subsystems, automotive OEMs are moving to designs where intelligence is split between the edge and hub/domain/zonal controllers. For example, rather than having an MCU for each sensor, centralizing the compute in a hub, domain, or zone can consolidate data collection. This approach helps reduce wiring complexity, cost, and power consumption.” 

Premium AI-enhanced features will become an automotive industry standard.

“Technology becomes more affordable over time, and the automotive sensor and computing sector is no different,” says Lyons. “Premium safety features such as ‘blind spot detection’ used to be expensive and found only in high-end vehicles.”

“With smart sensors and in-vehicle computing capabilities becoming both smarter and more affordable, we’ll see advanced AI-enable features, such as parking assist or autonomous assisted driving, reach the mass-market. For the AI-enabled cars of tomorrow, these will become standard features required in all vehicles.” 

Continued integration of LiDAR, radar, and camera sensors will make vehicles safer.

“Advanced Sensors will make a significant impact on ADAS solutions by providing more accurate data and improving safety maneuvers, from lane-keep-assist to auto parking and braking,” says Lyons.

“As the number and different types of sensors within the vehicle, such as cameras, radar and LiDAR, continues to rise each year, pioneering companies like Waymo have already logged millions of autonomous miles in vehicles that leverage all three technologies. In addition, emerging EV companies in China are leveraging advanced sensors like LiDAR to differentiate their safety offering in the fiercely competitive EV market.”

“To achieve the real-time performance required so the various sensor data can be used in real-world driving situations, developers will need a flexible architecture that can provide the necessary performance with functional safety, all on a single chip.” 

Ceva

“In 2025 we will witness a transformative shift in how technology, particularly artificial intelligence (AI), integrates into our daily lives, with a significant shift towards on-device AI,” says Amir Panush, CEO of Ceva. “This will drive the need for low-power, highly efficient processing solutions across a spectrum of applications and marks the rise of the Smart Edge, where AI enhances safety, productivity, and entertainment in increasingly personal and direct ways.”
 

“The industry will likely see a greater push for multi-protocol wireless solutions to support the interconnected IoT ecosystem, enhancing user experiences in smart homes, healthcare, and industrial settings.”—Amir Panush, CEO of Ceva.

“We will continue to see the rollout of technologies that pave the way for new forms of interaction and connectivity, fundamentally reshaping our engagement with the digital world. 

Infineon Technologies

“The structural trends of decarbonization and digitalization will define the market long-term. Decarbonization is a strong driver for renewable energies and the expansion of the energy infrastructure,” says an Infineon spokesperson. “This will further accelerate the expansion of renewable energies and investments in energy efficiency.”

“Decarbonization requires a systemic change in the way in which we generate, transport and consume energy.“

According to calculations by the International Energy Agency, the share of global power generation accounted for by renewables will need to increase from around 12 percent to over 70 percent by 2050 to keep the 1.5 degree climate target within reach.”

“Although demand for semiconductors for solar power systems has recently been lower because customers and installers have built up substantial inventories, the installation rate remains high. We therefore anticipate that business involving Infineon’s differentiating power modules for solar inverters will pick up again once inventory levels have returned to normal.”

Alphawave Semi

The need to scale AI networks will lead to a focus on 400G-class signaling, something that would have seemed impossible just a few years ago,”  says Dr. Tony Chan Carusone, Chief Technology Officer, Alphawave Semi. “With the entire industry hyper-focused on addressing AI scaling and bandwidth challenges, research efforts will be strained in the face of compressed timelines for the development of new networking solutions.”

“AI will drive the R&D agenda with unique solutions emerging for the many specific connectivity problems of end users. Standards activity will ramp up to address this, but will have a hard time keeping up.”—Dr. Tony Chan Carusone, Chief Technology Officer, Alphawave Semi. 

“The drive for connectivity at 400G/lane will force the industry to consider abandoning technologies that have been used at 50-200G in favor of new ideas.  For example, the complexities and implications of PAM4 vs PAM6 vs PAM8 modulation will be reconsidered.”

“The industry will question why we are using the same pluggables in the same form factors for copper and optical connections at 224G and 448G as we did at 25G? New optical device technologies will ramp up using new material systems, and advanced packaging technologies will be critical.”

“And why do scale up and scale out networks have to look the same, when there is a huge market for each? I think in 2025 you will see different solutions crop up tailored to address different applications: high speed 448G links, clever slow / wide interfaces , and for the most demanding applications: wide-and-fast!”

“We will see coherent optical connectivity technologies penetrate applications over shorter reaches than ever before.  As their cost and power continue to drop, it will find more and new use cases.  Meanwhile, coherent solutions at 1600G per wavelength will keep it ahead of the curve, making it a key technology to meet bandwidth scaling demands over the next decade.”

Empower Semiconductor

“AI adoption will continue to accelerate in 2025 with the deployment of new high-power processors and GPUs architectures in data centers and cloud computing,” says Tim Phillips, Founder and CEO of Empower Semiconductor.

“Maximizing the performance-per-watt metric will be the focus, placing new demands on throughput, performance, and energy efficiency not only for the xPUs but also for adjacent and critical technologies and products such as power management, advanced packaging and thermal management.”—Tim Phillips, Founder and CEO of Empower Semiconductor.

Emerson

"Almost every industry, including test and measurement, is being influenced by more powerful edge computing and complex data management requirements. These challenges have a direct impact on the ability to successfully implement AI tools.”—Ritu Favre, President of Test & Measurement Business Group (National Instruments) at Emerson.

“For Emerson Test & Measurement, we're keenly aware of these challenges and are focused on enhancing our core hardware and software platform to allow companies to scale their T&M efforts in a way that enables them to get the most out of their data now, while ensuring that they are ready for future advances in technology,” says Favre.

”It will also enable greater collaboration at every level, across the wider engineering community up to large scale business partners, which is a critical component of success as systems and workflows become more complex."

Tektronix

“In the electronics industry, we continue seeing more intelligence being placed at the “edge” as systems become smarter, driving the needs for accurate and focused testing to ensure precision,” says Maria Heriz, CMO of Tektronix.

“AI will continue driving investment and growth in the semiconductor ecosystem as AI leaders strive for greater ROI of their boards, subsystems, and data centers.  As a result, testing requirements for quality and failure analysis are becoming more vital.”—Maria Heriz, CMO of Tektronix.

“Lastly, while Automotive will continue to face a tougher environment due to a struggling EV ecosystem, Space and Satellite systems will experience an innovation acceleration where Test and Measurement needs are required, from power to high-speed data communications analysis.”

What Are Your Predictions for 2025?

There’s no doubt that 2025 looks to be an exciting year. Almost every company quoted here stresses the demands of AI computing both in data centers and at the edge, white faster networking and new chip design approaches will be critical challenges.

Be sure to check out Part 2 of this article where we share insights on how companies see 2025 for themselves. And we definitely want to hear your predictions for technology in 2025 too. Please share them in the comments below. Here’s wishing you a happy, healthy, and prosperous 2025!