Analyst(s): Ron Westfall
Publication Date: April 14, 2025
At Intel Vision 2025, new CEO Lip-Bu Tan prioritized a fresh customer-centric approach, highlighting portfolio advancements across AI PCs, Intel Gaudi 3 accelerators, and Intel 18A process technology.
What is Covered in this Article:
- Intel’s new CEO, Lip-Bu Tan, has consistently emphasized AI’s transformative potential across industries, particularly in areas requiring advanced computing power and infrastructure.
- Lip-Bu Tan’s nascent leadership at Intel reflects a commitment to regaining leadership in AI-driven solutions, including advancements in AI PCs, data center processors, and foundry services, as highlighted in his keynote at Intel Vision 2025.
- Investing proactively in Physical AI and World Foundation Models can position Intel as a leader in the next wave of AI-driven innovation. Leveraging its hardware prowess, Intel can power intelligent systems that interact with and understand the physical world.
The News: The Intel Vision 2025 conference, held March 31 to April 1, 2025, in Las Vegas, represented CEO Lip-Bu Tan’s public debut, spotlighting Intel’s latest innovations and strategies with a focus on enterprise-ready AI, cloud, edge solutions, and next-gen architectures, driving efficiency, cost optimization, and security.
Intel Vision 2025: Why Physical AI Beckons for Intel
Analyst Take: Intel’s new CEO, Lip-Bu Tan, has consistently emphasized the transformative potential of AI across industries, particularly in areas requiring advanced computing power and infrastructure. As the CEO of Intel since March 2025 and previously as a leader at Cadence Design Systems and a venture capitalist through Walden International, he has focused on enabling technologies that advance AI, such as cutting-edge semiconductor design, chip manufacturing, and system-level optimization.
His early leadership at Intel reflects a commitment to regaining leadership in AI-driven solutions, including advancements in AI PCs, data center processors, and foundry services, as underscored in his keynote at Intel Vision 2025. This suggests he sees AI, including its physical applications, as a critical driver of future innovation. As a result, from my perspective, Intel should consider investing heavily in Physical AI and World Foundation Models because these areas represent the next frontier in AI, with significant potential for innovation, market growth, and real-world impact. Here’s why:
Physical AI Rising
Physical AI refers to integrating AI with physical systems—think robotics, autonomous vehicles, smart manufacturing, and IoT devices. This is where AI moves beyond digital screens and into the tangible world, interacting with and manipulating physical environments.
- Market Opportunity: the demand for intelligent, adaptive physical systems is skyrocketing. Industries such as robotics, logistics (e.g., warehouse automation), healthcare (e.g., surgical robots), and transportation (e.g., self-driving cars) are projected to see massive growth. With its hardware expertise, Intel is well-positioned to lead the way in providing the computational backbone, including chips optimized for real-time AI processing in physical contexts.
- Competitive Edge: NVIDIA currently dominates AI hardware with GPUs, but Physical AI requires low-latency, energy-efficient, and edge-capable processors. These represent areas where Intel’s Edge AI, CPUs, XPUs, and custom silicon could flourish. Investing here could help Intel reclaim ground in the AI race.
- Real-World Impact: Physical AI enables machines to perceive, reason, and act in complex environments. For Intel, this means powering everything from factory robots to drones, aligning with its legacy of enabling transformative tech.
- Edge AI Alignment: Intel’s new AI Edge Systems, Edge AI Suites and Open Edge Platform software offerings help streamline and speed up AI adoption at the edge across industries such as retail, manufacturing, smart cities, and media and entertainment by simplifying integration with existing infrastructure. These portfolio capabilities align with the augmentation of Physical AI applications.
Growing Role of World Foundation Models
World Foundation Models are large-scale AI systems trained to understand and simulate the physical world. They integrate data from multiple modalities (vision, sound, physics, etc.) to create a holistic worldview. Think of them as the evolution of today’s language or image models but with a broader grasp of reality.
- Strategic Advantage: These models could become the operating system for future AI applications encompassing the underpinning of autonomous systems, simulations, and decision-making tools. If Intel invests early, it could capture early mindshare in the hardware (optimized chips) and software ecosystem, creating a portfolio edge against competitors.
- Synergy with Physical AI: World Foundation Models are critical for Physical AI, providing the “brain” that interprets sensory data and predicts outcomes in real-time. Intel could prioritize developing specialized processors to accelerate these models, especially for edge devices where power efficiency is key.
- Future Proofing: As AI shifts from narrow tasks (e.g., chatbots) to general-purpose systems that understand physics, causality, and human environments, World Foundation Models will be foundational. Intel risks falling behind if it doesn’t stake a claim in this space.
Why Intel Needs to Prioritize Physical AI
Intel’s strength lies in designing chips for diverse workloads. Physical AI and World Foundation Models demand high-performance, low-power, and scalable hardware in Intel’s wheelhouse. As AI moves from cloud-centric to edge-centric (e.g., robots processing data locally), Intel’s focus on edge computing aligns strategically. With over 100,000 real-world edge implementations with partners, many leveraging AI today, I find that Intel understands the unique challenges of edge AI, providing the foundation and impetus to play a major influential role in the build-out of Physical AI environments.
I believe Intel is equipped to handle the risks related to the strategic prioritization of Physical AI. These risks include addressing capital-intensive fields with long R&D cycles and mounting an enduring competitive challenge to players such as NVIDIA, AMD, and startups such as xAI, which are already in the game. Attaining market inroads in the nascent stage of the Physical AI market further reinforces the prime importance of execution, as Intel must stay on target in delivering its 18A process technology.
In short, investing in Physical AI and World Foundation Models could position Intel as a leader in the next wave of AI-driven innovation. Leveraging its hardware prowess, Intel could power intelligent systems that interact with and understand the physical world. I find this a bold move that can help redefine Intel’s role in the tech landscape.
Top Physical AI Use Case: Intel Should Prioritize Robotics
During Intel Vision 2025, CEO Lip-Bu Tan invoked robotics as a compelling use case, indicating that this segment is a potential area that Intel will increasingly prioritize in its portfolio development strategy. Intel should invest heavily in robotics because it is a high-growth, high-impact field that aligns with its core strengths in hardware, computing, and emerging AI technologies.
The global robotics market is expected to expand significantly, with estimates valuing it at over $100 billion by 2030, driven by demand in manufacturing, healthcare, logistics, and consumer applications. Intel can tap into this by powering the brains of these systems, including more focused development of specialized chips for robotics. From industrial robots optimizing factories to service robots in homes and hospitals, the need for efficient, scalable computing solutions is universal. Intel’s hardware and software capabilities could become the go-to platform across robotics and robotics-related sectors.
Robotics relies on Physical AI, which epitomizes AI that interacts with the physical world through perception, motion, and decision-making. Intel’s expertise in low-latency processors, edge computing, and AI accelerators positions it to meet the unique demands of robots operating in dynamic environments. Many robots need to process data locally (e.g., a delivery drone navigating obstacles) rather than relying on the cloud. Intel’s focus on edge-capable chips gives it an advantage in this space.
Today, NVIDIA dominates AI training with GPUs, but robotics emphasizes inference, especially real-time decision-making on resource-constrained devices. Intel’s current and evolving portfolio mix, including CPUs, XPUs, and custom silicon, could outmaneuver NVIDIA in this niche, especially for energy-efficient, compact systems. While competitors such as Qualcomm focus on mobile, automotive, and IoT, Intel could carve out robotics as a distinct pillar, leveraging its broad hardware portfolio.
Additionally, Intel’s majority ownership in Mobileye (88%) already powers autonomous driving, providing valuable real-world experience that is directly applicable to robotics. Extending this expertise to general robotics (e.g., vision systems, sensor fusion) is a natural step. Robots require a mix of high-performance computing (for AI), low-power operation (for battery life), and rugged durability. Intel’s fresh strategic commitment to designing custom silicon can also meet these needs.
Robotics is central to smart manufacturing, where Intel already has a foothold with IoT and industrial solutions. Investing here strengthens its role across Industry 4.0 environments. Evolving robotics use cases such as robots in healthcare (e.g., elder care), agriculture (e.g., precision farming), and disaster response (e.g., search-and-rescue bots) address societal challenges. Intel can play an integral role in powering these transformative technologies.
Diversification Benefits
Intel’s traditional markets in the PC and data center segments face increasingly saturated and fierce competition. Robotics offers a new revenue stream, especially as demand for intelligent machines grows across industries. By investing more directly in robotics, Intel could build a full stack – chips, software, and developer tools – creating a sticky ecosystem that fulfills a greater array of customer needs.
Naturally, Intel needs to weigh the risks and challenges attached to potentially top-prioritizing robotics, as robotics development is expensive and complex, requiring coordinated advances in hardware, software, and integration. Players such as Boston Dynamics, ABB, and Fanuc dominate robotics, representing intriguing collaboration opportunities as Intel rivals such as NVIDIA and ARM ramp up their targeting, including on the AI hardware/software side.
Looking Ahead
Overall, Intel is not starting from scratch and possesses the key portfolio building blocks, such as AI accelerators, edge computing expertise, and a legacy of powering complex systems, to become an integral player in the nascent Physical AI market. Key use cases, such as robotics, represent an opportunity to pivot from being a general-purpose chipmaker to a leader in a specialized, future-defining field. By prioritizing physical AI in portfolio development, ecosystem collaboration, and marketing, Intel can supply the computational muscle for physical AI use cases, reshaping how we work, live, and solve problems and elevating its relevance in an AI-driven world.
What to Watch:
- Can Intel show it is equipped to handle the risks related to the strategic prioritization of Physical AI, including addressing capital-intensive fields with long R&D cycles and mounting an enduring competitive challenge to players such as NVIDIA, AMD, and startups such as xAI who are already in the game.
- Intel must show it can meet the challenges of potentially top-prioritizing robotics, as robotics development is expensive and complex, requiring coordinated advances in hardware, software, and integration.
- Intel can compete in the Physical AI market by leveraging its edge computing expertise, cost-effective Gaudi accelerators, and open software ecosystem while addressing manufacturing challenges. Intel can become an enduring competitor by targeting affordability, scalability, and partnerships in robotics, automotive, and IoT.
See the complete Intel Vision announcement on the Intel website.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
Can Lip-Bu Tan’s Engineering-First Vision Get Intel Back on Track?
Qualcomm Ready to Usher in the Age of Industrial Intelligence
Image Credit: Intel
Author Information
Ron is an experienced, customer-focused research expert and analyst, with over 20 years of experience in the digital and IT transformation markets, working with businesses to drive consistent revenue and sales growth.
He is a recognized authority at tracking the evolution of and identifying the key disruptive trends within the service enablement ecosystem, including a wide range of topics across software and services, infrastructure, 5G communications, Internet of Things (IoT), Artificial Intelligence (AI), analytics, security, cloud computing, revenue management, and regulatory issues.
Prior to his work with The Futurum Group, Ron worked with GlobalData Technology creating syndicated and custom research across a wide variety of technical fields. His work with Current Analysis focused on the broadband and service provider infrastructure markets.
Ron holds a Master of Arts in Public Policy from University of Nevada — Las Vegas and a Bachelor of Arts in political science/government from William and Mary.
