Their December 2024 look-ahead was titled "Outlook for 2025: It’s All About AI".
From Institutional Investor, January 21, 2026:
The Physical World Upgrade: 2026 Outlook—When AI Spreads From Cloud to Edge
“PMI improves not when AI is built, but when AI spreads, and we’re moving from brain builders to economy-wide beneficiaries.”
For three years, the AI revolution has been a software story focused on Large Language Models and bubble fears. But this is just the beginning and represents only the first act. We stand at an inflection point where AI's evolution from text-based reasoning to multimodal perception and physical action will trigger the most significant hardware upgrade cycle in decades. NVIDIA's Blackwell and Vision-Language-Action models mark AI's migration from cloud servers into the physical world, requiring wholesale reinvention of nearly every compute device, industrial system, and physical asset. AI is following electricity's playbook. First you build the brains and the grid. Then you plug intelligence into everything, and that's when productivity shows up.
LLMs are disembodied intelligence optimized for linguistic tasks. Vision-Language-Action models integrate visual perception, language understanding, and physical manipulation. Where LLMs could be accessed through thin clients, VLMs demand edge compute, low-latency processing, continuous sensor fusion, and real-time actuation. Blackwell was designed for this transition: dedicated hardware for transformer inference, video processing, and sustained power delivery. The chip operates in milliseconds, processes continuous sensor streams, and makes decisions in physical space where failure carries real-world consequences. This represents NVIDIA's recognition that AI's next trillion-dollar opportunity lies in giving intelligence the ability to see, manipulate, and operate in the physical world.
Electricity mattered because factories reorganized around motors and productivity exploded. Right now, the "brain" lives mostly in the cloud with latency, cost, privacy, and reliability constraints. AI follows the same arc: from cloud-only to edge inference, from centralized to distributed intelligence. The move to the edge is driven by physics and economics. Agents can't wait on cloud calls. Inference at scale is too expensive centralized. Enterprises won't send crown-jewel data off-premises forever. This creates three parallel AI grids matching electricity's architecture: cloud for training, enterprise for private agents, edge for devices and robots.
VLM-capable phones will require neural processing units orders of magnitude more powerful, multi-sensor arrays, thermal management, and battery technology supporting continuous processing. Gartner forecasts AI PCs will reach 55% market share in 2026, up from 31% in 2025. Gartner predicts 40% of enterprise applications will feature AI agents by end of 2026, versus less than 5% in 2025, forcing hybrid architectures. Automotive demands complete reinvention: redundant processing, 360-degree sensors, real-time edge inference, vehicle-to-infrastructure communication. Every manufacturer recognizes that vehicles without VLM-capable systems will become unsellable within this decade.
Enterprise infrastructure upgrade represents larger capital deployment as AI agents transition to mission-critical systems operating continuously. AI agents don't sleep, generating transaction volumes that dwarf current loads. This demands wholesale buildout of edge server capacity, reducing latency from hundreds of milliseconds to single digits. The "always-on" nature creates demand for racks, switches, storage, power, and cooling across thousands of enterprise locations. This shift transforms AI from concentrated capital expenditure into broad economic expansion.
The military dimension is equally profound. Every major military power recognizes that AI superiority will determine conventional military outcomes, driving massive investment in hardened edge compute, satellite-based AI processing, and autonomous systems. Ukraine and Middle East wars made clear that modern warfare is about technological supremacy. The Department of Defense's JADC2 initiative previews this scale.
Humanoid robotics represents an entirely new hardware category rivaling smartphones in economic impact. Figure AI, Tesla's Optimus, and Chinese manufacturers are racing to bring robots to warehouses, factories, retail, and homes. Marc Andreessen: "We're entering the age of embodied AI where intelligence takes physical form." Each humanoid robot presents more complex hardware challenges than any consumer device. If humanoids achieve even a fraction of smartphone penetration, we're looking at hundreds of millions of units over two decades.
Underpinning all physical-world AI is exponential growth in data center capacity and power infrastructure. U.S. data centers consumed 4.4% of total U.S. electricity in 2023, projected to rise to 6.7% to 12% by 2028, with consumption rising from 176 TWh to between 325 and 580 TWh. This represents incremental demand equivalent to 74 to 132 GW of new capacity, forcing a shift from utilizing existing grid slack to requiring net-new generation and deep grid upgrades. This is the utility phase, not the productivity phase. We did not overbuild applications first, we overbuilt capacity.
Blackwell's power requirements dwarf previous GPU generations. The grid infrastructure to supply this compute doesn't exist in most markets. The 2026 cycle's distinction is acute concentration of bottlenecks in electrical engineering. U.S. transformer supply deficits are projected to hit 30% in 2026, with lead times extending to three to six years. These represent structural capacity constraints creating guaranteed revenue pipelines for electrical equipment manufacturers well into 2028. Utilities place orders years in advance, while hyperscalers invest directly into power. Alphabet's Intersect acquisition is expected to generate 10.8 GW by 2028. Natural gas peaker plants are being kept online as data center demand strains the grid. This is sustained infrastructure investment stretching across decades....
....MUCH MORE
