“The chip shortage is ending for some, persisting for others, and reshaping profit pools for everyone.”
The market signals say this: the worst phase of the semiconductor shortage is largely over in unit terms, but the economic shock is still working through balance sheets, capex plans, and product roadmaps. Lead times are down from the 40 to 50 week peaks that froze automotive and consumer hardware, yet pricing power, geographic concentration, and geopolitical risk keep the supply chain on edge. Investors now watch not “Is there supply?” but “Who controls margin, where, and for how long?”
The crisis phase was simple: not enough chips, too much demand, stalled factories. The current phase is more complex. Capacity is coming online, but it is uneven by node, by region, and by end market. Automakers still chase mature-node microcontrollers. AI startups fight for cutting-edge GPUs and high-bandwidth memory. Consumer electronics sees pockets of overstock. The question “Is the crisis over?” has a different answer if you are running a cloud GPU cluster, a smartphone OEM, or a tiny IoT hardware startup.
The business value angle sits in three places: pricing, optionality, and control. Pricing: who sets ASPs on critical components over the next five years. Optionality: who can switch fabs, packages, or architectures without burning a year of runway. Control: who can secure priority allocation when the next shock hits, whether that is a pandemic, a geopolitical flare-up, or a sudden demand spike from a killer AI product.
The shortage: what actually broke, and who paid for it
The headline narrative said “global chip shortage,” but the mechanics were narrower. The real choke points sat in mature nodes for automotive and industrial chips, ultra-advanced nodes for AI and high-end phones, and packaging and substrates that connect logic, memory, and power. Capacity at 200 mm fabs lagged. 300 mm capacity at leading nodes stayed concentrated in a handful of Asian regions. When demand spiked, there was no slack.
The first-order impact hit automakers. Assembly lines stopped not because of the lack of flagship processors, but because of 50-cent microcontrollers and power management chips made on older processes that nobody wanted to invest in a decade ago. Consumer PC and console makers paid up for GPUs and display drivers. Networking and cloud vendors entered allocation agreements for high-end CPUs, accelerators, and memory.
“At the peak, some automotive chips had lead times above 50 weeks. That is outside any reasonable planning cycle for production and inventory management.”
For tech startups, the shortage translated into two blunt costs: longer time-to-market and higher bill-of-materials (BOM) costs. Many early-stage hardware teams had boards designed around parts that simply could not be sourced at any reasonable volume. They either redesigned for whatever was available or delayed launches while burning runway on engineering and overhead.
The second-order impact landed on pricing power. Foundries pushed through price increases. IDMs prioritized large, stable customers. Distributors favored clients who could commit to volume and advance payments. The typical seed-stage hardware startup, buying a few thousand units at a time, had almost no leverage.
Where the shortage stands now: from crisis to chronic tightness
The market has moved out of pure crisis mode. Lead times for many standard parts have fallen back toward pre-pandemic levels. Inventory in some consumer segments has swung from deficit to surplus. Hardware founders no longer spend every day refreshing distributor portals and chasing alternative SKUs.
At the same time, two bottlenecks continue to shape strategy: cutting-edge compute for AI and mature-node chips for automotive and industrial.
“Overall lead times have normalized in many categories, but high-performance compute and auto-grade chips remain structurally tight relative to demand growth.”
For AI workloads, the focus sits on GPUs, advanced network switches, high-bandwidth memory, and CoWoS or comparable advanced packaging. Capacity is expanding, but the demand curve from LLM training and inference is steep and uncertain. The result is a market where volume buyers with deep capital commitments secure favorable allocation and pricing, while smaller players rent capacity in the cloud at a premium.
For automotive and industrial, demand for mature nodes keeps rising. Cars add more sensors, control units, and connectivity. Factories add more robotics and monitoring. Yet the economic incentive to vastly expand 40 nm and above capacity is mixed, since profit margins are lower than at cutting-edge nodes and demand visibility is hazier. This is where the shortage feels “over” only on paper.
Business value: who gains and who loses post-crisis
From a business perspective, the semiconductor shortage did not just slow products. It rewired bargaining power and margin structures across the stack. The key ROI levers now are:
1. Supply chain risk as a line item, not an afterthought.
2. Long-term contracts and prepayments as strategic tools.
3. Architectural flexibility as a financial hedge.
Foundries and large IDMs improved margins by increasing prices and prioritizing high-value customers. Some system integrators passed costs to end customers. Others saw gross margins compressed and valuations hit. Startups that could not ship hardware saw revenue pipelines freeze.
“Chipmakers used the shortage to reset contract terms and pricing. Many of those changes will not fully revert even as capacity loosens.”
For growth-oriented tech firms, the ROI case now favors more upfront work on sourcing and design tradeoffs. An extra quarter in design to qualify second-source components can save a year of supply risk. A small increase in BOM costs can protect gross margin stability over a multi-year product life if it reduces exposure to single points of failure.
Then vs now: how the shortage flipped the market
The current environment does not look like the pre-2020 world. Pricing, bargaining power, and geographic exposure all shifted. A simple before and after snapshot helps frame it.
| Factor | Pre-shortage (Then) | Post-peak shortage (Now) |
|---|---|---|
| Average lead time for common MCUs | 8-12 weeks | 12-24 weeks, with spikes in auto/industrial |
| Foundry pricing power | Shared with large fabless clients | Stronger tilt to foundries on key nodes |
| Use of long-term capacity agreements | Mostly large OEMs and top-tier fabless | Standard for hyperscalers, growing among mid-tier |
| Focus on geographic concentration risk | Limited board-level attention | Core strategic concern for boards and investors |
| Startup bargaining power with distributors | Moderate for niche parts and growth stories | Lower; allocation favors large stable buyers |
| Use of cloud-based silicon access (e.g., GPUs) | Cost-driven choice | Availability-driven choice |
The shortage exposed how much value rested on “invisible” plumbing. Discrete power devices, analog signal chains, and humble MCUs suddenly became strategic assets. For investors, that reshaped the way they read hardware startup decks. Supply chain depth, not just product vision, started to influence valuations.
Retro specs: what 2005 taught us about chip cycles
To understand where we might be heading, it helps to look back. The mid-2000s had their own chip supply swings, though nothing on the same global scale. Consumer electronics ramped fast. Feature phones pushed volumes. The PC market showed steady demand. The underlying theme was still cyclical capacity and pricing swings, but the stakes and concentration were lower.
“In 2005, a ‘shortage’ for many OEMs meant a few quarters of limited graphics cards or DRAM price spikes, not multi-industry shutdowns.”
The technology gap between then and now is huge, but the business patterns echo: overshoot in capex, periods of glut, periods of tightness, and repeated industry debates about how much capacity is enough.
Retro user reviews from 2005: what buyers cared about
Looking at user reviews from 2005 for popular devices gives a sense of how different product tradeoffs looked, and how far expectations moved.
“My Nokia 3310 never crashes. Battery lasts for days. I do not need more features, I just want it to keep working.” (Forum post, 2005)
“This new smartphone is cool, but it freezes, and the battery dies too fast. My old phone was more reliable.” (User comment on early smartphone, 2005)
“I paid extra for the faster CPU, but honestly I cannot see a big difference except when playing games.” (PC review site, 2005)
These comments highlight three points that matter for the current chip story:
1. Reliability and battery life felt more important than raw performance for many mainstream users.
2. Single-purpose devices (feature phones, basic MP3 players) had simpler supply chains and more stable component needs.
3. The performance gains that drove upgrades were visible but not tied to heavy cloud infrastructure or large AI models.
Then vs now: hardware expectations and silicon inside
Compare a classic device from the mid-2000s to a current flagship, and the pressure on semiconductors becomes clear.
| Device | Then (circa 2005) | Now |
|---|---|---|
| Phone model | Nokia 3310 | Flagship smartphone (e.g. iPhone 17-class) |
| Primary chip | Simple baseband + low-power MCU | Multi-core SoC with CPU, GPU, NPU, modem |
| Process node | Feature size in the hundreds of nm | Single-digit nm class logic, advanced RF |
| Memory | Low MB range | Multiple GB RAM, hundreds of GB storage |
| Supply chain exposure | More suppliers, more commoditized parts | High reliance on a few logic and memory foundries |
| User expectation | Calls, texts, long battery | Camera, gaming, AI features, constant connectivity |
In 2005, a phone launch did not hinge on a single advanced node at one or two fabs. Today, a flagship delay can ripple through a supply chain highly tied to just a few production centers. That structural difference is why the latest shortage cut deeper and why boardrooms now treat geographic and node concentration as strategic risk factors.
Capex binge: will overbuild end the shortage or start a glut?
One of the sharpest business questions today is whether the current wave of fab construction and tool orders will swing the market into oversupply. Governments in the US, Europe, and parts of Asia are pushing for local capacity with subsidies and tax credits. Major foundries commit to multi-year expansion plans.
On paper, that sounds like a cure for shortage risk. In practice, the timing and targeting of this capacity matter. Lead times for new fabs are long. Getting from announcement to high-yield volume can take several years. Most projects focus on either:
* Advanced logic nodes to serve CPU, GPU, and mobile SoC demand.
* Select mature nodes for automotive, industrial, and power.
The risk for investors in the sector is that capacity optimization by node, geography, and customer segment stays imperfect. Overbuild at one node can overlap with persistent tightness at another. From a startup point of view, that means the headline “More fabs are coming” does not automatically translate to lower BOMs or secure allocation.
Geopolitics, concentration, and the cost of risk
The crisis pulled geopolitical risk out of policy journals and into boardroom charts. A large share of cutting-edge logic production sits in a small geographic region exposed to natural, political, and military shocks. Even with new fabs planned in the US and Europe, concentration remains high.
Investors now ask founders harder questions:
* Where are your critical components fabricated and packaged?
* Can you dual-source between at least two fabs or vendors?
* What happens to your revenue model if a key region goes offline for 3 to 6 months?
Many startups still cannot fully answer these questions without help from their manufacturing partners. That gap is less about technical skill and more about cost. Diversifying across fabs, qualifying alternate parts, and maintaining extra inventory all cost money and extend design cycles. But the ROI can be compelling when measured against the revenue loss and valuation impact from a year-long product delay.
Impact by sector: who feels “post-crisis” and who does not
The answer to “Is the crisis over?” varies sharply by sector. It is more accurate to break it down.
Automotive and mobility
Automotive players sit in a hybrid state. For some key chips, supply is better. For others, especially auto-grade MCUs, power devices, and sensors at mature nodes, supply-demand balance remains fragile. Many OEMs shifted from just-in-time to what some call “just-in-case,” holding more inventory and committing to longer-term agreements.
That inventory comes with carrying costs and obsolescence risk, but it buys continuity of production. The business tradeoff is between higher working capital and lower probability of shutdown. For startups in EVs, ADAS, or commercial fleets, this means hardware design must align with suppliers that can commit to automotive lifecycles, not just volume at the moment.
AI, cloud, and data center
The AI sector is still in active shortage for the highest-end accelerators and associated components. Hyperscalers secure large, multi-year allocations with prepayments and co-investments. Smaller cloud providers and AI startups rely on residual supply or cloud rentals. For these buyers, the shortage is not “over” in any practical sense. Capacity growth is real, but so is demand growth from LLM training and inference.
This leads to a bifurcated ROI picture:
* Big buyers lock in capex-heavy access at lower per-unit cost.
* Smaller players accept higher opex via cloud usage, with less control over availability.
Gross margins and product pricing in AI services reflect that asymmetry.
Consumer electronics and IoT
Consumer electronics has moved closer to balance. Smartphones, laptops, and wearables see more normal lead times for many components. Some segments even face inventory hangovers as demand cooled from pandemic highs. For IoT startups, the picture is mixed. Simple modules and MCUs are easier to source, but niche parts or very low-cost components still face minimum order constraints and pricing pressure.
The key business lesson here is that “availability” does not equal “favorable terms.” Startups fresh from the shortage period still tend to over-index on security of supply, sometimes committing to volumes that outrun demand forecasts. That can trap precious cash in inventory.
Pricing models and margin shifts across the value chain
The shortage and its aftermath did not just change where chips are made. It changed who captures value per unit shipped. A simplified view across segments looks like this:
| Player | Revenue model | Then (pre-shortage) | Now (post-peak shortage) |
|---|---|---|---|
| Foundries | Wafer pricing by node and volume | Prices under heavier OEM pressure, frequent discounts for volume | Higher base pricing, stronger surcharges, more long-term agreements |
| Fabless chip firms | Per-chip ASP with volume tiers | Moderate pricing power, focus on design wins | Greater pricing strength for must-have parts, closer alignment with key customers |
| Distributors | Margin on inventory and allocation | Stable margins, many SKUs available from stock | Higher margins on tight parts, more strategic allocation decisions |
| OEMs / device makers | Product sales, service add-ons | Better ability to switch suppliers, more BOM flexibility | Tighter supply relationship costs, more locked-in components |
| Startups / small hardware firms | Low to mid-volume hardware, SaaS layers | Dependence on spot pricing, some negotiating room in niches | Weaker leverage, higher exposure to allocation and prepayment demands |
For growth investors, this shift highlights where margin expansion potential lives over the next cycle. It also affects how to judge startup pitches that rely heavily on hardware: who owns the key supplier relationships, and how sensitive is the unit economics to 10-20 percent component price fluctuations.
What this means for startups: from scramble to strategy
For early-stage tech firms, the shortage moved supply chain decisions from “operational details” to “board-level strategy.” Even as the immediate panic fades, the lessons remain valuable.
Key patterns now:
* Architecture choices must consider not just performance, but supply flexibility and vendor concentration.
* Building with more common, widely produced components can beat marginal technical gains from exotic parts.
* Early partnerships with distributors, design houses, and contract manufacturers can unlock better access and forecasting.
The ROI lens is simple: a slightly higher BOM today can reduce revenue volatility tomorrow. A modest delay in launch to qualify a second-source component can protect years of sales from single-node shocks.
Is the semiconductor crisis over?
From a pure availability standpoint, the broad, across-the-board chip shortage that froze global production has eased. Most standard components can be procured with lead times that fit into rational business planning. The “I cannot ship at all” phase is largely done for many sectors.
For AI accelerators, auto-grade parts, and some mature-node categories, constraints remain. For those segments, the crisis feels more like a chronic condition: manageable with planning and capital, painful for players without either.
The deeper shift is structural. Power in the supply chain tilted toward fabs and critical component vendors. Geographic concentration risk became a direct financial concern. Hardware startups entered a world where supply resilience is part of product-market fit, not an afterthought.
The question is no longer just “Is the shortage over?” The more relevant question for founders and investors is: “In the next shock, are you a priority customer, a flexible architect, or a stranded buyer?”