(Zero Hedge)—It’s widely accepted that quantum computing remains a long-term bet, with meaningful commercialization unlikely before the 2030s—if not later.
Investor enthusiasm plunged sharply in early January after Nvidia CEO Jensen Huang remarked that “very useful” quantum computers are still years away. Since then, however, quantum computing stocks (IonQ, Rigetti Computing, D-Wave Quantum, and Quantum Computing) have soared, adding billions of dollars in market capitalization.
Morgan Stanley’s latest report, “Quantum Computing – How Will It Impact AI?”, offers one of the most comprehensive overviews to date, mapping out the evolving quantum landscape and its growing convergence with the artificial intelligence boom.
A team of analysts led by Shawn Kim told clients that quantum computing is entering a new era, marked by breakthroughs such as Microsoft’s ‘Majorana 1’ and Google’s ‘Willow’ chips, which promise to outperform today’s supercomputers.
They noted that these advances could accelerate AI development by enabling solutions to problems currently beyond the reach of classical computing. Rather than replacing classical systems, quantum computing is expected to serve as a powerful accelerator, enhancing AI’s capabilities, particularly in finance, logistics, pharmaceuticals, and energy.
While practical applications remain in the early stages, cloud-based access from big tech is making quantum tools increasingly accessible. Although widespread commercialization is still years away, early investments in the quantum AI ecosystem have already begun, and growing speculation over the industry’s long-term potential has sent related stocks soaring.
Here’s how the analysts frame the broader outlook for the quantum computing industry to clients:
- A Quantum leap beyond the Silicon Age. Microsoft’ Majorana 1′ or Google ‘Willow’ quantum chips were launched earlier this year, representing a paradigm shift in the ability to harness the laws of quantum mechanics to perform calculations orders of magnitude faster than today’s supercomputers. This could lead to faster breakthroughs in AI that are currently beyond the reach of classical computing, transforming how we approach complex problems, develop intelligent systems, and make predictions with a level of accuracy and speed that was previously impossible.
- A powerful synergy – augmenting AI capabilities. We view a merging of the speed of quantum computing with the learning power of AI as a partnership rather than a competition with classical computing. Quantum chips are designed to work as quantum accelerators alongside AI systems to unlock entirely new capabilities that can amplify AI’s potential beyond the reach of classical computing. The two technologies have very different strengths and therefore lend themselves to different use cases with AI excelling at creativity, language and video processing, while quantum computing is more suited for tackling complex problems that are beyond the capabilities of classical algorithms.
- There will be no shortage of commercial applications. Quantum computing has become more accessible as big tech companies are now offering services via their cloud services, narrowing the gap between theory and practical implementation with the potential to reshape many industries such as finance, pharmaceuticals, logistics and energy by solving complex AI problems much faster than classical computers. Most real-world uses are relatively small today and still in development, but the future looks promising.
- Preparing for a quantum AI future. The practical applications and integration of quantum computing into AI systems are still in the early stages of development, but much like in the early days of semiconductors, early investments in successful quantum companies and their ecosystems will likely yield substantial returns. An important question remains around the commercial timeline, although many early leaders are computing incumbents and some start-ups.
The analysts outlined the rationale behind publishing this report to clients:
Why we’re writing this report: Following our first deep dive into quantum computing nearly five years ago ( The New Processing Paradigms, 19 July 2020 ), we wanted to take stock of the many moving pieces in the sector after several tech giants released new quantum chips earlier this year. Hyperscalers such as Google (Willow), Microsoft (Majorana1), IBM and Amazon (Ocelot) are all investing in the rapidly evolving quantum race. Some of them are partnering with quantum computer companies and some are doing it in-house. In this report we focus on quantum developments and how they could impact AI in three domains – computing, metrology, and communication – in terms of commercial use cases. As the quantum computing market continues to evolve, staying informed about advances, commercial applications, and regulatory developments will be essential for making sound investment decisions in this emerging sector.
Provided more insight into quantum computing’s impacts on AI:
Quantum computing allows AI to think much faster by introducing non-deterministic and probabilistic elements that allow for more intuitive reasoning vs. current AI that is largely a sophisticated pattern recognition machine. By leveraging quantum superposition, entanglement, and interference, new quantum AI models offer the potential for significant reductions in both computational cost and energy consumption. As quantum computing develops, its integration with AI has the potential to unlock entirely new approaches that are more efficient, enable significantly better accuracy, and hence better performance. AI tools like ChatGPT have already made a profound impact on society, but a critical limitation is the need for computational behemoths using classical large language models (LLMs) that are expensive to train. With fewer parameters required, quantum models could make AI more sustainable, tackling one of the biggest challenges facing the industry today.
Quantum computers have been around for decades, but mostly as experimental models in research institutions and technology companies. Unlike classical computing models, which are binary representations of electrical switches (transistors), quantum computers measure states of subatomic particles using qubits (quantum bits). Quantum computers are still not powerful enough today to do anything commercially viable in AI, due the sensitivity of quantum systems to noise and error. A lot of effort is being made to overcome hurdles, however, industry experts and hyperscale cloud providers predict the timeline for practical commercial applications of quantum computers may only be five years out.
- Quantum computing. Quantum computers store and process quantum data as opposed to binary data. Unlike current AI systems, which rely on GPU (graphics processing unit) or ASIC (application-specific integrated circuit) chips, quantum computers harness technologies such as superconducting circuits, trapped ions and neutral atoms in highly isolated environments to protect their fragile processing. The main challenge lies in scaling and improving the hardware to fully exploit the potential of quantum computing, which has a number of important uses in computing fields including optimization, power efficiency, and machine learning. Quantum computers are also known for their potential to carry out ‘Shor’s Algorithm’, which can be used to factorize large numbers to decrypt data transmissions.
- Quantum communication (transfer of quantum ‘signals’). Quantum communication takes advantage of properties unique to the physics of quantum mechanics, opening new paradigms for communication that cannot be realized by classical (non-quantum) communication. Quantum communication could enhance AI’s ability to process and share real-time data across distributed networks, and provide ultra-secure data transmission. Distributed quantum computers and quantum sensors are interconnected with a quantum communication network in the quantum equivalent of the classical internet.
- Quantum metrology and sensing. This uses the physical properties of quantum systems – photons and atoms – to set standards for units of measurement in science and industry, as well as for engineering other high-precision technologies. Enhanced imaging and sensing technologies from quantum sensors, combined with AI, could achieve breakthroughs in areas such as autonomous systems, medical diagnostics and environmental monitoring. Use cases include quantum imaging or quantum radar that compromise stealth technology. It is also the only known way to detect dark matter and energy.
Before readers get too excited about quantum stocks, the analysts note: “Quantum is still very much in its infancy.”
Perhaps most intriguing, the analysts frame the quantum race as a split between the West and the East.
Here are the key players to watch in the space:
- IBM – Most advanced ecosystem, aiming for 200+ logical qubits and commercialization by 2029.
- Microsoft – Game-changing topological qubit architecture.
- Google – “Willow” chip achieved major error-correction milestones.
- Amazon – “Ocelot” chip; working on bosonic error correction.
- IonQ, Rigetti, Quantinuum – Specialized quantum startups with wide-ranging partnerships.
Pure Play & Big Tech Stocks
And now to the part that matters most for investors: the timeline for commercialization.
According to the analysts:
What’s the timing? The consensus quantum computing timeline suggests meaningful commercial applications emerging around 2029-30, with more advanced utility-scale quantum computing expected in the early to mid-2030s. The timing for quantum computing commercialization varies across different milestones, with several key timeframes emerging from industry experts and companies in the field. There are coordinated efforts from companies and governments to make quantum work and still primarily in the research and development phase. Many experts believe the chance of Q- day happening before 2030 is over 50%. Businesses are taking it seriously, pouring billions into preparation and will likely to begin to derive value well before via cloud offerings that are already available today for basic quantum computations.
- Current state (2025): Quantum computing is still primarily in the research and development phase. Companies like Rigetti are working on scaling their systems, with plans to reach 100+ qubits by the end of 2025 with targeted improvements in error rates.
- Commercial applications (2029-2030): Multiple sources indicate that meaningful commercial applications of quantum computing are expected in approximately 4-5 years from now:
- Cryptographic threats (2030): A cryptanalytically relevant quantum computer capable of breaking common public key schemes such as RSA or ECC is expected by 2030. The National Institute of Standards and Technology (NIST) has set 2030 as the timeline for implementing quantum-secure algorithms and deprecating currently used cryptographic methods.
The Roadmap
Read the rest of Morgan Stanley’s deep quantum computing dive—available here for pro subs.
Two Storms, One Harvest
Every food crisis in living memory has been a one-shock event. The 2008 price spike was a commodity bubble. The 2020 shortages were a logistics failure. The 2022 grain scare was a war on one exporter’s ports. Each time, the system bent, adjusted, and recovered, and each time the experts assured us afterward that global markets are simply too big and too diversified to fail.
What nobody in Washington seems eager to discuss is that 2026 is shaping up to be something the modern food system has never actually faced. Two independent shocks, one climatic and one geopolitical, are converging on the same harvest cycle at the same time. Not sequentially. Simultaneously.
Start with the weather. The Pacific Ocean is currently building toward what forecasters now openly call a record event. NOAA’s Climate Prediction Center puts the odds of at least a strong El Niño near 88 percent, with roughly two in three odds it reaches “very strong” status, the tier reserved for perhaps three or four events in the entire satellite era. Every major global model now projects a median peak in Super El Niño territory, and most of them project it exceeding the 2015-16 event, which until now held the modern record. Sea surface anomalies were already brushing the super threshold in mid-July, months before these events normally peak. The atmosphere has already shifted into El Niño mode, and the event is forecast to crest in late fall and early winter.
This is not about “climate change.” It’s about the standard cycles of weather, and the cycle we’re currently in is one that has likely devastated societies in the past. We’re better prepared as a society today, but not all Americans are equally prepared.
Serious households have started doing the quiet math on their own. Grocery bills tell part of the story, and the forecast maps tell the rest, which is why long-term food storage has moved from fringe hobby to mainstream line item in the family budget, with established suppliers like Heaven’s Harvest seeing demand from people who five years ago would have rolled their eyes at the idea. That instinct is not paranoia. It is pattern recognition, and the pattern is worth walking through carefully.
Editor’s Note: Heaven’s Harvest IS a sponsor, but the warnings of this article are real and would be written even if we didn’t have a survival food sponsor. With that said, those who take advantage of what they offer can use promo code “Patriot” for 15% off.
The Fertilizer Clock Is Already Running
While the Pacific warms, the second shock has been unfolding in the Strait of Hormuz. The conflict with Iran turned the world’s most important energy chokepoint into a contested waterway, and the consequences reach far beyond the gas pump. Roughly a third of global fertilizer trade moves through Hormuz, and the disruption sent urea prices up 86 percent year over year by March, with a 53 percent jump in a single month.
The World Bank projects energy prices rising about 24 percent in 2026 and fertilizer about 31 percent. By its own accounting, fertilizer prices ran 35 percent higher in the first five months of this year than the same period last year.
Here is the mechanism the nightly news will not explain. Fertilizer is not a grocery item. It is a time-delayed input. The nitrogen a farmer in Iowa or Punjab could not afford to apply this spring does not show up as a problem this spring. It shows up as a thinner harvest six to twelve months later.
The World Bank’s own food security brief concedes that the effects of reduced applications earlier this season “are likely to become visible only later in harvest outcomes.” Translate that from institutional language into plain English and it means this. The damage is already done, it is already in the ground, and we are simply waiting for it to arrive on the shelf.
Now check the calendar. Six to twelve months from the spring planting season lands us squarely in late 2026 and early 2027. Which is precisely when the strongest El Niño in the instrumental record is forecast to peak, bringing its signature droughts to Southeast Asia, Australia, southern Africa, northern Brazil, and South Asia, the very regions that grow the world’s rice, sugar, and oilseeds.
The World Bank warns openly that a strong El Niño “could disrupt multiple crop belts simultaneously” on top of the conflict-driven input costs. Their baseline projection assumes the Middle East disruptions ease by autumn. What in the last two years of Middle East history suggests that assumption is safe?
The System Has No Slack Left
The comfortable answer is that global markets always adjust. But adjustment requires slack, and the slack is gone. Global cereal production is expected to decline from last year’s records even before El Niño does its work. The UN World Food Programme, hardly a den of right-wing preppers, is calling this the most significant disruption to its supply chains since Covid and the invasion of Ukraine, and its supply chain director put the stakes bluntly.
Today’s supply chain challenges are tomorrow’s hunger crisis.
There is also a political dimension that markets cannot price. When food gets scarce, governments do not behave like economists. They behave like politicians. Export bans, hoarding mandates, and panic buying at the national level turned the modest rice shortfall of 2008 into a global crisis, and analysts are already warning that import-dependent nations are the first dominoes.
The 2015-16 Super El Niño, a far weaker event than what is now forecast, threw tens of millions into food stress across Africa and Asia. This one is projected to be stronger, and it arrives with fertilizer already rationed by price and shipping lanes already contested by missiles.
What Joseph Knew
Scripture does not treat preparation for lean years as faithlessness. It treats it as wisdom delivered in advance to those willing to act on it.
Behold, there come seven years of great plenty throughout all the land of Egypt: And there shall arise after them seven years of famine; and all the plenty shall be forgotten in the land of Egypt.
Joseph did not respond to that warning with a hashtag or a committee. He stored grain during the years of abundance, and when the famine came, Egypt stood while its neighbors begged. The lesson is not that famine is certain. It is that the time to prepare is precisely when preparation still looks optional.
Nobody who filled a pantry in a year of plenty has ever regretted it, and nobody standing in an empty aisle has ever been glad he waited for certainty.
None of this calls for panic, and panic is the enemy of sound judgment anyway. It calls for the same unglamorous prudence our grandparents considered ordinary. Keep some cash margin, know your local growers, and put real food in deep storage while it is cheap and available, because the entire arc of this story is that cheap and available is a closing window.
Families looking for a straightforward place to start can visit Heaven’s Harvest and use promo code Patriot for 15 percent off long-term storable food. The forecasts may yet soften, the strait may yet reopen, and we should pray they do. But hope is a fine thing to hold and a foolish thing to eat.
