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**Wall Street is demanding evidence that artificial intelligence investments are generating measurable returns for corporate customers, not just for the companies selling the infrastructure.** CNBC's Jim Cramer said Wednesday he needs "cold hard" proof that AI is paying off for enterprise clients, as a growing divide emerges between companies supplying AI infrastructure and those trying to use it. His comments come as IBM's disastrous pre-announcement — shares plunged 25%, wiping out about $70 billion in market value — showed that the shift in corporate technology spending toward AI hardware is actively hurting demand for traditional enterprise software. "The conditions require our teams to execute perfectly, and this quarter we faltered," IBM Chief Executive Officer Arvind Krishna wrote in a letter to investors, acknowledging the company underestimated how quickly clients would redirect capital toward servers, storage and memory chips to secure supply-constrained AI infrastructure. The tension crystallizes a question that has hung over the technology sector for two years: When will the hundreds of billions flowing into AI show up in corporate customers' profit-and-loss statements? Microsoft, Amazon and Alphabet are committing roughly $575 billion collectively this year on AI infrastructure, on top of hundreds of billions already invested. Yet enterprise software companies are seeing the opposite — their customers are delaying purchases or building in-house alternatives. **The Enterprise Software Squeeze** IBM now expects second-quarter revenue of about $17.2 billion, representing annual growth of just 1% and falling short of analysts' estimates of $17.86 billion. Adjusted earnings per share are projected at $2.93, below Wall Street's $3.02 consensus. The guidance triggered a selloff that spread across the software sector, dragging down Microsoft, Salesforce, ServiceNow and Intuit. Salesforce has been hit even harder than IBM, plunging 36% year to date on similar concerns that AI tools will replace rather than complement traditional software. Last week, Bloomberg reported that Starbucks is looking to reduce the $400 million it pays Microsoft and IBM annually for software tools by replacing them with in-house applications built with AI. Citi analysts offered a contrarian view on Microsoft's Copilot, raising their adoption estimates and predicting "notable stronger Copilot adoption momentum" with M365 Copilot net adds of 8 million versus 5 million in the prior quarter. Microsoft reports fiscal fourth-quarter earnings after the close on July 29. Citi maintained its buy rating but cut its price target to $570 from $620, citing multiple compression in enterprise software. Microsoft shares rose more than 3% on Wednesday, extending their month-to-date gains to 6%. Still, the stock is down 18% year to date and 27% below its record close of about $542 in late October 2025. **What's at Stake for Investors** The AI spending rotation creates a two-tier market. Infrastructure providers — Nvidia, data center operators, memory chipmakers — continue to benefit from the $575 billion capital expenditure wave. But enterprise software companies face a period of uncertainty as customers reassess budgets and build internal AI capabilities. For Microsoft, the path to justifying its roughly 30x forward earnings multiple depends on showing that Copilot and Azure can convert infrastructure spending into recurring software revenue. IBM's Red Hat business, which grew 11%, and its distributed infrastructure backlog of about $500 million offer some bright spots, but the core software business is under pressure. The broader question — whether AI will ultimately expand the software market or cannibalize it — may not be answered until enterprise customers report their own cost savings and revenue gains from AI deployments. Until then, Cramer's demand for "cold hard" proof reflects a market that has priced in the promise but has yet to see the payoff. This article is for informational purposes only and does not constitute investment advice.
A structural shift in enterprise IT budgets toward generative AI and cybersecurity triggered IBM's worst single-day selloff in 115 years, with a Bernstein CIO survey showing a record 54% of buyers plan to cut spending on the legacy technology provider. "These conditions require our teams to execute perfectly, and this quarter we faltered," IBM Chief Executive Officer Arvind Krishna wrote in a letter to investors, attributing the miss to clients redirecting capital expenditure toward servers and storage ahead of expected memory price increases. IBM's preliminary second-quarter revenue of $17.2 billion missed the $17.858 billion consensus by about 4%, while non-GAAP earnings of $2.93 per share fell 8 cents short of estimates. Infrastructure revenue dropped 7%, consulting was flat, and software grew just 5% — well below the double-digit target. Only Red Hat showed momentum with roughly 11% growth. The selloff pushed IBM shares to $217.07, surpassing the Black Monday crash of 1987 as the stock's worst day ever. With a 26.7% year-to-date decline and a Polymarket probability of just 25.5% that IBM beats consensus when it reports full results on July 22, the question is whether this is a buying opportunity or the beginning of a longer decline. The Bernstein survey, conducted in May 2026, captured the sentiment of chief information officers across major enterprises. Net 54% of CIOs said they plan to reduce spending on IBM — the worst reading since the survey began and a deterioration from 49% in November 2025. Among all major hardware vendors tracked by Bernstein, IBM ranked last in customer spending intent. The data points to a structural retreat from IBM's core businesses. One-third of CIOs said they plan to cut mainframe MIPS capacity over the next five years, up from 23% six months earlier, while 14% intend to migrate off the mainframe platform entirely. Net 15% of CIOs said they expect to reduce their use of third-party IT consultants, directly pressuring IBM's consulting segment, which generated roughly $53.4 billion in quarterly revenue — flat year over year. **The Memory Chip Squeeze** The immediate trigger for IBM's miss was a rapid shift in enterprise procurement driven by the worsening memory chip shortage. Dynamic Random Access Memory prices surged 100% to 116% in the first quarter of 2026, and SK Hynix has said its DRAM and NAND capacity is essentially sold out for the year. Intel's chief executive warned there is no relief until 2028. In response, businesses rushed to buy servers, storage and memory hardware before prices rose further, deferring software licenses, consulting engagements and mainframe upgrades. Sandisk reported data center revenue jumped 233% sequentially to $1.5 billion, while Micron Technology's data center revenue climbed 102% sequentially to $11.52 billion. IBM, caught off guard, saw "numerous large deals fail to close on the timelines we expected," Krishna said. **Can IBM Recover?** IBM's software miss was concentrated in transaction-processing software tied to the z17 mainframe launch, rather than a broad-based deterioration, Bernstein analysts noted. Red Hat's 11% growth and a 37% gain in the distributed infrastructure segment — which includes power and storage products with a $500 million backlog — offer some bright spots. But the structural headwinds are formidable. HSBC downgraded IBM to Reduce from Hold, cutting its price target to $191 from $231. The average analyst target of $299.31 implies 39% upside from current levels, though those estimates may be revised downward after the pre-announcement. Morgan Stanley's Erik Woodring raised his target 10% to $293, but Polymarket data suggests only a 25.5% probability that IBM beats consensus on July 22. IBM shares, trading at roughly 14 times forward earnings before the selloff, now face a valuation reset. The company has increased its dividend for 31 consecutive years, which may provide a floor for income-oriented holders. But with CIOs systematically reallocating budgets toward AI infrastructure and cybersecurity — areas where IBM has less competitive exposure — the path to recovery runs through a fundamental repositioning of the company's product portfolio, not a single quarter's earnings beat. This article is for informational purposes only and does not constitute investment advice.
IBM's profit warning sent its shares down more than 25% on Tuesday, wiping out $69 billion in market capitalization, as customers redirected spending from software and mainframes to AI hardware and memory chips. "These conditions require our teams to execute perfectly, and this quarter we faltered," Chief Executive Arvind Krishna said. "While we anticipated some supply chain-related impact in our expectations, we did not anticipate the magnitude of the capex reprioritization." In June, clients shifted quarterly capital expenditures toward servers, storage and memory to secure supply-constrained AI infrastructure ahead of expected price increases, Krishna said. The company now expects infrastructure revenue to fall 7%, worse than its prior forecast of a low-single-digit decline. Sales of the z17 mainframe, IBM's flagship enterprise system designed for the AI age, also fell short. The selloff dragged down software peers including Salesforce, Workday, Adobe and ServiceNow, which fell 2.1%, 3.5%, 4.3% and 5.8%, respectively. The broader concern: if a company as diversified as IBM can be blindsided by AI budget crowd-out, pure-play software vendors face even greater risk as the July 22 earnings season unfolds. The warning marks a turning point in the AI spending cycle. For the past two years, enterprise technology companies benefited from a rising tide — customers increased overall IT budgets to accommodate AI experiments alongside existing software commitments. IBM's pre-announcement suggests that dynamic has flipped: AI is no longer additive but substitutional. Memory chip makers and cybersecurity vendors were the clear winners from the shift. SK Hynix surged more than 20% on Nasdaq as investors priced in sustained demand for high-bandwidth memory used in Nvidia-based AI training clusters. CrowdStrike and Palo Alto Networks also jumped, as Barclays analysts said IBM's comments likely referred to heightened security concerns tied to Anthropic's recently launched Mythos AI model, which has accelerated corporate spending on vulnerability detection. **The Crowd-Out Mechanism** The mechanics are straightforward. AI infrastructure is capital-intensive — training clusters require thousands of graphics processing units, high-bandwidth memory and specialized networking equipment, all of which carry price tags that strain fixed annual IT budgets. When a bank or retailer commits $50 million to an AI buildout, that money must come from somewhere. IBM's core customer base of financial-services firms — including Bank of America, Citigroup, Goldman Sachs and JPMorgan Chase — appears to be making exactly that trade-off. "This earnings season is going to be strewn with companies that fall in that category," said Gil Luria, head of technology research at D.A. Davidson. "They are hearing from their customers, 'We need to make room in our budget for AI.'" BNP Paribas analysts said in a note Tuesday there was "no indication that this trend has yet abated." IBM is scheduled to report its official second-quarter results on July 22, when Krishna is expected to provide more detail on the outlook. **Investment Implications** For software investors, the question is whether this is a temporary budget shuffle or a structural repricing. Barclays analysts argued the mainframe delay is probably temporary, with customers postponing purchases while absorbing higher infrastructure costs. But the pattern — hardware eating software budgets — could persist as long as AI chip supply from Nvidia and others remains constrained and prices keep rising. IBM's other software businesses, including Red Hat, continued to perform well, with revenue growth actually accelerating. That suggests the damage is concentrated in hardware-dependent segments rather than the broader software portfolio. Still, the 25% single-day decline — the largest in IBM's history — signals that the market is pricing in a more lasting shift. Chris Versace, chief investment officer at Tematica Research, called the warning "confirmation that AI adoption and usage are rising and companies are prioritizing it to drive efficiencies and productivity." For traditional enterprise tech vendors, that prioritization comes at a direct cost. This article is for informational purposes only and does not constitute investment advice.
**Enterprise IT buyers are diverting capital expenditure from software to servers and memory, a shift that erased $69 billion from IBM's market value in a single day and confirmed the memory super-cycle is spreading beyond hyperscalers.** IBM (IBM) closed down 25.2% on Tuesday — its worst single-day drop since at least 1968 — after preannouncing quarterly results that missed Wall Street estimates. The company reported adjusted earnings per share of $2.93 on revenue of $17.2 billion, below consensus forecasts of $3.02 and $17.86 billion. "In the last few weeks of June, we saw clients shift their quarterly capital expenditures toward servers, storage and memory purchases to secure supply-constrained infrastructure ahead of expected price increases," IBM Chief Executive Officer Arvind Krishna said. "While we anticipated some supply chain related impact in our expectations, we did not anticipate the magnitude of the capex reprioritization." The sell-off erased $69 billion in market capitalization, according to data compiled by Bloomberg. Prior to Tuesday, IBM stock had declined 4.8% year to date; it is now down 26%. Rivals have fared similarly: Oracle (ORCL) is off 33% year to date, Microsoft (MSFT) has declined 20%, and Accenture (ACN) is down 50%. **The Crowding-Out Effect Reaches Enterprise IT** Goldman Sachs analysts in Seoul described IBM's results as the strongest real-economy confirmation yet of the memory super-cycle thesis. The core logic: HBM (high-bandwidth memory, the specialized memory used in AI accelerators) consumes significant wafer capacity at Samsung Electronics and SK Hynix, crowding out production of traditional server DRAM. That supply constraint is now pushing up prices across the entire memory stack — and enterprise IT buyers are responding by front-loading hardware purchases. "This dynamic impacted client buying patterns," Krishna said. IBM had prepared for a low-single-digit decline in its z17 mainframe business for the quarter, but the actual drop was far worse. IDC's Ashish Nadkarni, who leads the firm's enterprise infrastructure research, wrote that Wall Street's reaction may have been stronger than warranted, but investors should not dismiss Krishna's warning. "It may not mean the collapse of the mainframe business, but it does mean that IBM is not isolated from the strategic reallocation of enterprise budgets in order to address the acceleration of AI adoption," he said. The memory shortage is also affecting consumer electronics. Apple's Mac and iPad lines, Microsoft's Surface devices, and video game consoles from Sony, Microsoft and Nintendo all face component constraints, according to industry reports. **KOSPI Finds Support as Institutions Buy the Dip** The confirmation of enterprise demand for memory comes as South Korea's KOSPI index — heavily weighted toward Samsung Electronics and SK Hynix — experienced a 9% single-day crash on Monday. Goldman Sachs attributed the severity to forced deleveraging of newly listed single-stock leveraged ETFs, which triggered a self-reinforcing liquidation cycle disconnected from fundamentals. Despite the volatility, the index held at the 61.8% Fibonacci retracement level, where local institutions and foreign investors turned net buyers. Retail investors, by contrast, have capitulated, according to Goldman's prime brokerage data and client feedback from Singapore roadshows. Most technology investors Goldman contacted expressed cautious optimism about capacity expansion, believing structural shortages in equipment and components — including ASML's lithography systems — will prevent the aggressive capacity buildout that bears fear. ASML is expected to raise its sales guidance, and the market will watch closely whether the company can scale production to meet surging equipment demand. Goldman Sachs maintains its KOSPI target of 12,000 points with a bullish stance, citing four positive developments: stocks have become cheaper after the third-quarter seasonal weakness, retail capitulation has cleaned up positioning, enterprise IT demand is proving stronger than expected, and both foreign and local institutions are buying at key technical support levels. **What This Means for Investors** For memory suppliers, the crowding-out effect strengthens pricing power. Samsung Electronics and SK Hynix stand to benefit from a "higher for longer" memory cycle as structural supply constraints — limited HBM wafer capacity, equipment shortages at ASML — cap the industry's ability to add DRAM output. Micron Technology, the third major DRAM producer, is also positioned to benefit from the pricing tailwind. IBM will hold its full quarterly earnings call on July 22, where investors will seek more detail on the magnitude and duration of the enterprise spending shift. The stock's 25% collapse has pushed its dividend yield above 4% for the first time in a decade, though analysts caution that the revenue headwind from the CapEx reallocation may persist for multiple quarters. This article is for informational purposes only and does not constitute investment advice.
Enterprise software companies are facing an unexpected budget squeeze as customers redirect capital expenditure toward AI hardware, a trend that pulled Salesforce shares down 5% on Tuesday and dragged the broader SaaS sector lower. The rotation became visible after International Business Machines Corp. disclosed preliminary second-quarter results that missed Wall Street estimates on both revenue and profit. IBM shares plunged more than 23% in their worst single-day decline in the company's 115-year history. "Customers shifted their quarterly capex spend toward servers, storage, and memory purchases to secure supply-constrained infrastructure ahead of expected price increases," IBM Chief Executive Arvind Krishna said in a letter to investors. He said the company did not anticipate "the magnitude of the capex reprioritization." The impact rippled across the software and consulting sector. Accenture Plc fell 8%, ServiceNow Inc. dropped 6%, and Workday Inc. and Salesforce Inc. each declined 5%. The selloff erased billions in market value from companies that had been viewed as beneficiaries of enterprise digital transformation spending. At the center of the shift is a global memory supply shortage that is inflating hardware costs. High-bandwidth memory and DRAM production is being consumed primarily by hyperscalers and AI infrastructure providers, leaving enterprises to pay significantly higher premiums for the hardware they can secure. With annual IT budgets largely fixed, the higher cost of hardware is crowding out software licensing, renewals, and new cloud projects. IBM reported software revenue rose 5% in the quarter, consulting was flat, and infrastructure revenue declined 7%. The company said clients were also distracted by "rapidly-evolving, industry-wide cybersecurity concerns" that delayed software investment decisions. The dynamic represents a reversal from the past two years, when enterprise software companies benefited from a wave of AI-related experimentation and tool adoption. Now, the build-out phase of the AI cycle is consuming the same budgets that funded those software purchases. For Salesforce, the timing is particularly challenging. The company has been pushing its Data Cloud and Einstein AI platform as growth drivers, pitching AI-powered customer relationship management as a must-have upgrade. If enterprises are deferring software purchases to lock in hardware inventory, those upgrade cycles may slow in the near term. The broader question for investors is whether this is a one-quarter disruption or the start of a structural shift in enterprise IT spending. IBM will provide its full-year outlook during its scheduled earnings call on July 22, which may clarify whether management expects the hardware spending surge to persist. If the reprioritization extends into the second half of the year, SaaS companies with high exposure to enterprise subscription revenue could face renewed pressure on growth rates and net revenue retention. Salesforce shares, which had gained roughly 8% year-to-date before Tuesday's decline, now trade at about 26 times forward earnings — a premium to the broader market but a discount to high-growth SaaS peers. The stock's next catalyst will be its own quarterly results, expected in late August, when investors will see whether the budget rotation has affected Salesforce's deal pipeline and close rates. *This article is for informational purposes only and does not constitute investment advice.*
**IBM Chief Executive Officer Arvind Krishna said cyber fears are the top customer priority, sending cybersecurity stocks higher as IBM shares suffered their worst drop in decades.** Cybersecurity stocks rallied Tuesday after IBM Chief Executive Officer Arvind Krishna said cyber fears have become a top customer priority, causing some major deals to be paused as businesses reallocate spending. "Cyber is the No. 1 priority for our clients right now," Krishna told CNBC's Sara Eisen. "In the last few weeks of June, we saw clients shift their quarterly capex toward securing supply-constrained infrastructure." The comments came as IBM disclosed preliminary second-quarter results that missed estimates, with revenue of $17.2 billion versus analyst expectations of $17.85 billion. IBM shares fell 24%, their steepest single-day drop since 1987. The warning centered on a shortfall in the company's Z mainframe business and associated software, which Krishna attributed partly to customers prioritizing cybersecurity and AI spending over traditional infrastructure. The divergence — cybersecurity stocks rising while a bellwether tech name collapses — shows a structural shift in enterprise technology budgets. Companies are redirecting spending from legacy hardware and software toward security and artificial intelligence, creating clear winners and losers across the sector. CrowdStrike Holdings Inc., Palo Alto Networks Inc. and Fortinet Inc. each gained more than 3% in afternoon trading, as investors interpreted Krishna's comments as confirmation that cyber budgets are expanding even as broader tech spending faces headwinds. The rally suggests the market sees cybersecurity as a beneficiary of the same spending reallocation that hurt IBM. Citi analyst Fatima Boolani said the disappointing results "stand to perpetuate 'AI-Loser' fears," while HSBC's Neil Churchill downgraded IBM to Reduce, saying he prefers "synthetic IBM to the real one." The analyst commentary highlights the challenge facing legacy technology companies caught between the AI investment cycle and the cybersecurity imperative. For cybersecurity vendors, the dynamic creates a tailwind. Enterprise spending on security software is projected to grow at a double-digit rate through 2027, according to industry estimates, as companies face an increasingly complex threat environment. Krishna's comments confirm that trend, even as they expose the pressure on traditional hardware and software lines. The IBM warning also raises questions about the broader enterprise technology market. If a company with IBM's scale and customer relationships is seeing deal delays, smaller vendors may face similar headwinds. The key distinction is where the money is flowing: toward security and AI, and away from legacy infrastructure. Microsoft Corp., which competes with both cybersecurity vendors and IBM in enterprise software, saw its shares trade relatively flat, reflecting its exposure to both sides of the spending shift. The company's security business, including its Microsoft 365 Defender and Azure Sentinel products, positions it to capture some of the reallocation. For investors, the takeaway is clear: the enterprise spending rotation toward cybersecurity and AI is accelerating, and the companies with direct exposure to those themes are likely to benefit at the expense of legacy hardware and software vendors. IBM, trading at 27 times forward earnings before the selloff, now faces questions about whether its mainframe-driven model can adapt to a world where customers prioritize security over infrastructure upgrades. This article is for informational purposes only and does not constitute investment advice.
IBM reported preliminary second-quarter revenue of $17.2 billion, missing the $17.86 billion consensus estimate, as customers shifted technology spending toward AI infrastructure at the expense of traditional software. "In this quarter we faltered in adapting quickly enough to evolving market conditions," Chief Executive Officer Arvind Krishna said in a letter to investors. He cited "numerous large deals" that failed to close as expected. Adjusted earnings per share came in at $2.93, below the $3.02 estimate compiled by LSEG. The preliminary results reflect an industry-wide reallocation of corporate technology budgets toward AI servers, storage and memory purchases, reducing spending on legacy enterprise software and services. The 17% premarket decline puts IBM on track for its steepest single-day drop in recent years, erasing billions in market value. The miss stands in contrast to Big Tech peers that have benefited from surging AI-related demand. IBM's traditional enterprise focus has left it exposed as customers prioritize AI infrastructure over the consulting and legacy software deals that have historically driven its revenue. The preliminary results suggest IBM's efforts to pivot toward hybrid cloud and AI under Krishna's leadership have yet to offset the drag from its legacy infrastructure business. Investors will watch the full Q2 earnings release for segment-level detail and any updated guidance on the pace of the transition. This article is for informational purposes only and does not constitute investment advice.
Susquehanna Financial Group initiated coverage of International Business Machines Corp. with a neutral rating, acknowledging the company's quantum computing leadership but flagging valuation concerns. "There are so many reasons to like IBM," Susquehanna analysts said in an initiation note, "but quantum dominance alone does not justify the current valuation." IBM shares traded at about $302 at the time of the June 23 initiation, giving the stock a price-to-earnings multiple of roughly 26 times. The broader consensus among 25 analysts covering IBM is Moderate Buy, with 16 buy ratings and nine holds, according to MarketBeat data. The average price target stands at $306.47, implying limited upside from current levels. The neutral call puts Susquehanna on the more cautious side of the Street as IBM pushes deeper into quantum computing and artificial intelligence. The company's next earnings report, expected July 22, will test whether its software and AI revenue growth can close the valuation gap that Susquehanna flagged. Susquehanna's initiation follows a flurry of analyst activity on IBM. In the past month, JPMorgan upgraded the stock to overweight from neutral with a $291 price target, while Morgan Stanley raised its rating to overweight from equal weight. Bank of America boosted its price target to $330 from $315 earlier this month, citing stronger second-quarter potential and an improving software mix. IBM has gained about 14% year to date, outperforming the S&P 500's 8% advance. The stock's 50-day moving average of $257 sits well below its current price, reflecting the recent rally. The company reported first-quarter earnings of $1.91 per share in April, topping the $1.81 consensus estimate, with revenue of $15.92 billion rising 9.5% from a year earlier. The Armonk, New York-based company has been investing heavily in quantum computing, recently announcing a partnership with Oak Ridge National Laboratory and Cleveland Clinic to perform the first-known quantum computations of fusion materials. IBM also unveiled a cybersecurity partnership with Deloitte and Red Hat to help businesses defend against automated cyberattacks. The neutral rating signals that even as IBM builds credibility in next-generation computing, the stock's current price already reflects those ambitions. Investors will watch the July 22 earnings call for evidence that AI and software revenue growth can justify a higher multiple. This article is for informational purposes only and does not constitute investment advice.
President Trump signed two executive orders June 22 elevating quantum computing from a long-term research initiative to a national strategic priority, directing the White House to update the National Quantum Strategy within 180 days. "The revised strategy will prioritize domestic manufacturing, workforce development, public-private partnerships and the commercialization of quantum technologies," the White House said in a statement accompanying the orders, which also establish the Quantum Computer for Application Development and Discovery Science initiative at the Department of Energy. A companion executive order accelerates the federal transition to post-quantum cryptography, reflecting efforts to strengthen cybersecurity against future quantum-enabled threats. The orders build on earlier U.S. quantum initiatives, including the CHIPS and Science Act, under which D-Wave Quantum Inc. signed a letter of intent for $100 million in proposed funding in May. D-Wave also secured a $1.5 million grant under the National Science Foundation's National Quantum Virtual Laboratory program. The policy shift shows that quantum computing is increasingly treated as a strategic technology with implications for economic competitiveness, cybersecurity and defense. The updated National Quantum Strategy and the DOE's QC-ADDS initiative could support demand across the quantum value chain, including quantum hardware, advanced semiconductors, photonics, cryogenic systems and quantum software. While broad commercial adoption of fault-tolerant quantum computing remains years away, the executive orders suggest federal procurement and strategic investment will play a larger role in shaping the industry's growth trajectory. The investment implications extend beyond pure-play quantum developers. Companies such as International Business Machines Corp., Quantum Computing Inc. and D-Wave Quantum stand to benefit from growing federal support for the quantum ecosystem. IBM recently introduced the world's first sub-1 nanometer chip technology, featuring a breakthrough transistor architecture at the 0.7 nanometer node, packing nearly 100 billion transistors onto a chip the size of a fingernail. D-Wave is advancing both annealing and gate-model quantum computing systems, with its dual-rail technology developed through the acquisition of Quantum Circuits Inc., a Yale University startup. The push to accelerate the federal transition to post-quantum cryptography could create opportunities for cybersecurity vendors serving government and regulated industries. IonQ, another quantum computing company, recently unveiled its Clavis XG Multiplex product line designed to make quantum security more practical across metropolitan fiber networks, and opened a new laboratory suite in Boulder, Colorado, to support quantum computing research and semiconductor chip testing. The administration's approach mirrors a broader pattern of government equity involvement in strategic technologies. The government obtained a 10% stake in Intel Corp. after investing $8.9 billion in the American chipmaker's stock, and has also taken equity stakes in IBM and other quantum-computing companies. The previous U.S. quantum initiative, the National Quantum Initiative Act of 2018, authorized $1.2 billion over five years for quantum research, a fraction of what the current executive orders could unlock through the CHIPS Act and DOE programs. The executive orders also direct the development of a large-scale quantum computer for scientific discovery through the QC-ADDS initiative, positioning the Department of Energy as a central player in quantum hardware deployment. This marks a shift from the previous administration's focus on basic research toward a more commercially oriented approach that emphasizes domestic manufacturing and public-private partnerships. This article is for informational purposes only and does not constitute investment advice.
The US Commerce Department committed $2 billion to quantum computing firms in exchange for ownership stakes, while China's Taiyi Quantum raised $44 million in Pre-A funding, escalating a race for technological supremacy with national security implications. "It is clear that we are now in a race for this technology," said Jay Gambetta, research director at IBM, which received half of the US funding package and will partner with the Commerce Department to build a standalone quantum chip foundry called Anderon. The US deals, structured as a pseudo-sovereign wealth fund mechanism, reached nearly all publicly traded pure-play quantum firms except IonQ, which was absent from talks. Google Quantum AI declined participation, citing conditions that would slow engineering progress. Shanghai-based Taiyi Quantum nearly doubled its original $29 million target, reflecting intensifying state-backed development in China, where quantum computing is designated as one of seven "future industries" in the latest Five-Year Plan. Quantum systems are expected to crack the encryption protecting much of the world's data within years, making the technology a national security asset. A mid-June executive order accelerated the US migration to quantum-safe systems to 2031, while Jefferies analysts project the race will accelerate this year, with Barclays predicting evidence of quantum superiority on useful problems within 12 to 24 months. **Patents and Progress: A Neck-and-Neck Sprint** Data from McKinsey and Barclays Research shows the US and China are nearly tied in quantum patent volume, with China leading in quantum communication and the US ahead in quantum sensing and computing. China operates the world's largest integrated space-to-ground quantum network, a lead built through sustained investment. "China definitely has a lead in quantum communication," said Joe Fitzsimons, CEO of Horizon Quantum. "It really depends where you put in the investment." The last time the US faced a comparable technology gap was in the 1940s Manhattan Project, which produced the first atomic bomb in 1945; China followed in 1964. IonQ CEO Niccolo de Masi said the quantum gap is narrower. "I hope they're 10 quarters behind, but they're definitely not 10 years behind," he said. **State Control vs. Market Forces** China's quantum ecosystem is increasingly consolidated under state control. Baidu and Alibaba shuttered dedicated quantum research groups in 2023, transferring equipment to the Beijing Academy of Quantum Information Sciences and Zhejiang University. Tencent remains the only major Chinese tech firm still operating its own quantum lab. QuantumCTek, the first quantum technology company listed on a Chinese exchange, is now majority-controlled by China Telecom Quantum Group and serves as a key government supplier. Its shares rose 3.75 percent. Last year, Shenzhen-based SpinQ made history as the first Chinese enterprise to ship a complete superconducting quantum system overseas, highlighting the country's growing export capability in the sector. In the US, the Commerce Department's ownership-stake structure marks a departure from traditional grants, blending industrial policy with direct government investment. IBM's Gambetta said the state has a responsibility to consult with experts across academia and the private sector. "If I'm still talking about the potential of quantum computing five years from now, we've failed," he said. "We need to make this exist for our nation." **Market Reaction and Forward Outlook** Investors have responded to the escalating competition. IonQ shares gained 9.27 percent, while Quantinuum, the Honeywell spinoff that overtook IonQ as the largest quantum pure play by market capitalization, fell 3.61 percent. IBM rose 2.35 percent. Christian Weedbrook, CEO of Xanadu Quantum Technologies, described China's quantum effort as "a huge black box" in an earlier interview, highlighting the difficulty for US investors in assessing Chinese progress. Barclays analysts described China as an emerging quantum computing hub, noting that state involvement in the industry has intensified in the last two years. Jefferies projects the race will accelerate this year, with both governments pouring resources into a technology that could reshape global data security, defense systems, and scientific computing. The US executive order signed in mid-June mandates federal agencies to accelerate migration to quantum-safe cryptography by 2031, creating compliance-driven demand for quantum security solutions across government networks. This article is for informational purposes only and does not constitute investment advice.
ServiceNow and IBM are integrating watsonx.data, Red Hat Ansible and HashiCorp Terraform into the ServiceNow AI Platform to solve the data and legacy-application problems blocking enterprise AI, with joint solutions expected in the second half of 2026. "This partnership breaks through outdated systems and puts data to work for AI," ServiceNow management said in announcing the expanded collaboration on June 11. The deal targets two specific blockers — messy enterprise data and aging application layers — across a ServiceNow platform that runs more than 85 billion workflows annually. IBM's watsonx.data brings enterprise data capabilities, while Ansible, Terraform and Vault automate the infrastructure layer where most customers get stuck. The companies will deliver joint solutions aimed at modernizing legacy systems and enabling autonomous IT operations. ServiceNow shares have shed 36% year-to-date and 52% over the past year, trading at $100.39 — a forward multiple of 23 times earnings, the cheapest in years. The partnership generated no guidance lift and IBM rose less than 1% on the news, leaving investors to weigh a credible integration thesis against a sector-wide software selloff that has also hit rivals like Salesforce. **What the Deal Actually Changes** The collaboration extends ServiceNow Workflow Data Fabric with IBM's enterprise data capabilities, enabling autonomous IT operations across hybrid environments. For customers, the pitch is straightforward: instead of stitching together separate tools for data management, automation and IT service management, the integrated stack handles the full chain. The timing matters. ServiceNow raised its 2026 AI commit target to $1.5 billion from $1 billion, and Q1 subscription revenue grew 19% in constant currency with a 97% renewal rate. Those numbers suggest the underlying business is compounding even as the stock price compresses. **Why the Market Isn't Buying Yet** The software sector is in the middle of a brutal rerating. A viral post on wallstreetbets captured the mood: "Genuinely what on earth is going on with software right now? This is completely unhinged." ServiceNow's Reddit sentiment spiked to 82-84 on the partnership news, then collapsed to 22 as macro selling overwhelmed the story. Of 37 analysts covering ServiceNow, 33 still rate it a Buy. Bernstein reiterated a $236 price target — more than double the current price. But neither ServiceNow nor IBM tied the partnership to updated financial guidance, and without a revenue catalyst, the market has little to anchor on beyond the broader rotation narrative. The bull case rests on simple math: ServiceNow at 23 times forward earnings with 19% subscription growth and a $1.5 billion AI commit target is cheaper than it has been in years. The IBM deal, if it ships clean in H2 2026, accelerates deals already in motion. The bear case is that every rally fades into the next software wobble until guidance catches up to the narrative. For now, neither side has been proven right. This article is for informational purposes only and does not constitute investment advice.
**IBM Research has produced the world's first sub-1 nanometer chip architecture, packing nearly 100 billion transistors onto a fingernail-sized die and extending the semiconductor roadmap into the angstrom era.** IBM's new nanostack architecture, built at the 0.7-nanometer node, delivers up to 50% higher performance or 70% greater energy efficiency than its 2nm predecessor — a leap that could reshape the economics of AI data centers. "It's not just an incremental step, it's a meaningful leap forward, pointing to a future where computing becomes significantly more powerful without a corresponding increase in energy," Jay Gambetta, director of IBM Research and an IBM Fellow, said. The nanostack design stacks transistors vertically rather than laying them side by side, enabling nearly twice the transistor density of IBM's 2nm node chip introduced in 2021. IBM also demonstrated a 40% improvement in SRAM scaling, a critical metric for AI workloads that rely on high-bandwidth, low-latency memory. The architecture allows top and bottom transistors to be engineered separately with different materials, unlocking performance and power optimizations impossible in conventional planar designs. IBM no longer manufactures chips commercially — it exited fabrication in 2015 by transferring its plants to GlobalFoundries — but its research pipeline has historically set the direction for the entire industry. Nanosheet technology, which IBM pioneered, now underpins all leading-edge 3nm and 2nm chips from TSMC and Samsung Foundry. If nanostack follows the same trajectory, it could influence the next decade of chip design for Nvidia, AMD, and Intel. **How Nanostack Works** The basic unit of IBM's nanostack architecture consists of two transistors stacked and bonded together, each containing three nanosheets individually 5 nanometers thick — equivalent to about 15 rows of silicon atoms. By staggering transistors in the vertical dimension, IBM effectively adds a third axis to chip scaling that the industry has largely exhausted in two dimensions since the transistor was invented in 1959. "This will be for the first time in our industry that we are able to stack and stagger transistors in a vertical direction," Huiming Bu, vice president of silicon technology research and development at IBM, said. The approach addresses a fundamental problem: traditional transistor miniaturization has approached atomic limits, and SRAM scaling — the ability to shrink the memory cells closest to the processor — had slowed to just a few percent between the 3nm and 2nm generations. IBM's 40% SRAM improvement through staggered-channel bit cells represents a step-change in an area where progress had nearly stalled. **The AI Data Center Connection** The timing of the breakthrough aligns with an inflection point in AI infrastructure spending. Nvidia's Blackwell GPU, built on TSMC's 4nm node, and the coming Rubin platform on 3nm, both push against power and thermal constraints in data centers. Hyperscalers including Microsoft, Amazon, and Alphabet are spending tens of billions annually on GPU clusters, where energy costs have become a binding constraint on expansion. "Everyone demands more performance, but no one wants to pay for the bill for the power," Bu said. IBM's SRAM improvements are particularly relevant because many AI chips dedicate large portions of die area to on-chip memory to reduce data movement — one of the largest sources of energy consumption in AI inference. More efficient SRAM designs could increase cache capacity and reduce the need to shuttle data between processors and external memory, directly lowering the total cost of ownership for AI workloads. **Path to Commercialization** IBM cautioned that the technology remains in the research phase, with earliest adoption at the sub-1nm node expected within five years. The company is working with partners including Japan's Rapidus on 2nm manufacturing and is preparing to use ASML's High NA EUV lithography tools at its Albany, New York facility — equipment that will be essential for printing the ultra-precise circuit patterns that nanostack requires. Gambetta declined to name specific commercialization partners but said the architecture is generic enough to apply across CPUs, GPUs, and mobile processors. "Within a decade, this will become another mainstream that we have invented and helped industry to transform," Bu said. For investors, the question is whether nanostack follows the nanosheet playbook — where IBM's research became the industry standard adopted by TSMC and Samsung — or remains a lab curiosity. IBM shares trade at roughly 22x forward earnings, with the stock's valuation driven more by its software and consulting businesses than its semiconductor intellectual property. A successful licensing pipeline for nanostack could add a new revenue stream, though the company has not disclosed any licensing agreements. This article is for informational purposes only and does not constitute investment advice.
**IBM's nanostack architecture packs nearly 100 billion transistors onto a fingernail-sized chip, extending Moore's Law into the angstrom era.** IBM unveiled the semiconductor industry's first sub-1-nanometer chip technology, a vertically stacked transistor architecture that packs nearly 100 billion transistors onto a fingernail-sized die — nearly double the density of its 2nm node. "It's not just an incremental step, it's a meaningful leap forward, pointing to a future where computing becomes significantly more powerful without a corresponding increase in energy," Jay Gambetta, director of IBM Research and an IBM Fellow, said. The 0.7-nanometer, or 7-angstrom, node delivers up to 50 percent higher performance or 70 percent greater energy efficiency compared with IBM's 2nm node chips introduced in 2021, according to published technical results. The nanostack architecture builds on nanosheet technology — which IBM pioneered and which has become the industry standard for 3nm and 2nm chips at TSMC and other foundries — by stacking transistors vertically rather than shrinking features across the wafer surface. The breakthrough extends the semiconductor roadmap for at least another decade, threatening to widen the technology gap for competitors still scaling nanosheet transistors in two dimensions. IBM expects commercial adoption within five years and mainstream production within a decade, potentially reshaping the competitive dynamics among TSMC, Samsung Foundry and Intel. The nanostack design uses sequential 3D integration to bond two transistors — each containing three nanosheets 5 nanometers thick, equivalent to about 15 rows of silicon atoms — into a single stacked unit. The architecture allows top and bottom transistors to be engineered separately with different materials, enabling performance and power optimizations that are difficult in conventional planar structures. IBM researchers demonstrated the technology's viability through functional CMOS inverter operation with expected switching performance, presented at the 2025 IEEE Symposium on VLSI Technology and Circuits. At the VLSI 2026 symposium, the company showed a 40 percent improvement in SRAM scaling using a staggered-channel design that reduces bit-cell height — a development Gambetta said could prove significant for AI workloads requiring high-bandwidth, high-efficiency memory close to compute resources. The SRAM scaling achievement addresses a growing bottleneck in AI chip design. SRAM scaling improved only a few percent between the 3nm and 2nm generations, Gambetta said, making the 40 percent gain a structural shift for chip architects designing AI accelerators that rely heavily on on-chip memory to reduce data movement — one of the largest sources of energy consumption in AI inference. Huiming Bu, vice president of silicon technology research and development at IBM, said the industry has largely scaled transistors in two dimensions since the metal-oxide-semiconductor field-effect transistor was invented in 1959. "This will be for the first time in our industry that we are able to stack and stagger transistors in a vertical direction," he said. The work is being conducted at IBM's semiconductor research facility in Albany, New York, where the company and its partners — including Lam Research, Tokyo Electron and SCREEN Semiconductor Solutions — are preparing to deploy High Numerical Aperture Extreme Ultraviolet lithography from ASML Holding NV. IBM said High NA EUV will be critical for future logic scaling and could also improve nanosheet technology before nanostack reaches production. IBM has not disclosed commercialization partners for nanostack, though it is working with Japan's Rapidus Corp. on 2nm manufacturing. The company's track record of licensing its chip technology to partners including Samsung suggests a similar model for nanostack. TSMC, which independently developed nanosheet transistors for its 2nm node after IBM's pioneering work, faces pressure to develop its own 3D stacking solution to remain competitive. For investors, the implications span multiple tickers. IBM's breakthrough could pressure TSMC and Intel to accelerate their own sub-1nm roadmaps, potentially increasing R&D spending across the industry. If nanostack delivers the projected 50 percent performance gain, it could shift procurement decisions at hyperscale cloud operators — Amazon, Microsoft and Google — that spend tens of billions annually on AI chips. IBM itself, while not a commercial chip manufacturer, stands to generate licensing revenue from the architecture, though the company has not disclosed financial terms. This article is for informational purposes only and does not constitute investment advice.
**A global technology stock rout deepened Tuesday as Federal Reserve rate-hike signals and concerns over stretched artificial-intelligence valuations triggered the worst selloff in semiconductor shares this year.** The Nasdaq Composite tumbled 2.2% to 25,587 as a global tech selloff intensified on Fed rate-hike signals and AI valuation concerns. "The AI beneficiaries are the selloff, and I don't think they're expensive, but they're crowded," Andrew Slimmon, senior portfolio manager at Morgan Stanley Investment Management, said. "It's captured the zeitgeist of the momentum traders, and when that happens, you're going to have sharp selloffs like we're having. I'd argue it's healthy." The S&P 500 fell 1.4% to 7,365, while the Dow Jones Industrial Average slipped less than 0.1% to 51,667. Six of 11 S&P 500 sectors posted gains, with consumer staples rising 1.8% and healthcare adding 1.4%, showing the narrowness of the decline. The Philadelphia Semiconductor Index tumbled 7.8%, with Sandisk and Micron Technology — both of which hit record highs Monday — plunging 13% and 13.2%, respectively. Nvidia lost more than 4%, while Intel fell 6% and AMD slid nearly 6%. The selloff erased more than $600 billion from SpaceX in the prior two sessions and dragged South Korea's tech-heavy Kospi down 10%, raising questions about whether the artificial-intelligence trade that powered this year's rally has become overcrowded. Micron's earnings report Wednesday will test whether the selloff is a healthy correction or the start of a deeper rotation. The selloff swept across global markets. South Korea's Kospi index plunged 10%, dragged by SK Hynix and Samsung, which each fell more than 12%. Japan's Nikkei dropped 3.6%, and Hong Kong's Hang Seng lost 1.8%. In Europe, the Stoxx 600 Technology index slid 3.2%, with STMicroelectronics and ASMI both down more than 7%. **Rate Fears Compound AI Rotation** The catalyst for the selloff was twofold. Fed Chairman Kevin Warsh last week said officials are "unambiguously and unanimously" committed to bringing inflation back to the central bank's 2% target, with derivative traders now pricing in nearly two rate increases this year. Separately, concerns that the billions of dollars in AI infrastructure spending may not translate into proportional profits have prompted investors to reassess the sector's valuations. "All of that means that these business models are going to turn out to be more cyclical, and that means they're going to be a lot more rate sensitive," Lisa Shalett, chief investment officer of Morgan Stanley Wealth Management, said. The 10-year Treasury yield hovered around 4.5%, while the U.S. dollar index traded near one-year highs, adding pressure on risk assets. West Texas Intermediate crude fell to about $73.40 a barrel, its lowest in nearly three months, after the U.S. and Iran signed an interim peace deal that reopened traffic through the Strait of Hormuz. **Defensive Rotation Takes Hold** IBM rose more than 4% to lead the Dow, while Merck and Verizon each gained about 3%. Cybersecurity names also bucked the trend, with Palo Alto Networks and Fortinet each advancing about 2%. On the downside, Carnival fell 5.5% after issuing weaker-than-expected profit guidance, and Oracle dropped 4% after disclosing it cut 21,000 jobs, partly through the use of AI. "Semiconductors are structurally more volatile and cyclical than the hyperscalers that carried markets through the last hiking cycle," Julia Hermann, global market strategist at New York Life Investment Management, said. "They are likely to be more rate sensitive, exposing the market to the consequences of tighter policy." Investors now turn to Micron's fiscal third-quarter earnings due Wednesday after the close, which will provide the next test of whether AI-driven demand is translating into earnings growth. FedEx also reports after the bell Tuesday, offering clues on corporate spending and logistics demand. This article is for informational purposes only and does not constitute investment advice.
**IBM is laying the groundwork to turn quantum computing from an expensive science project into a scalable commercial business, betting that federal backing and technical advances can deliver a research-grade machine within two years.** IBM is preparing to commercialize quantum computing at scale, positioning itself at the center of a $2bn federal push to build a research-grade quantum computer by 2028. The company's shift from laboratory experiment to commercial product comes as the US government awards roughly $1bn to IBM as part of a broader grant program that takes equity stakes in nine quantum firms. "Sound policy, sustained investment and public-private partnership are vital to sustaining US quantum leadership and technological resilience," IBM Chief Executive Officer Arvind Krishna said in a statement after President Donald Trump signed two executive orders on June 22. The first order directs the Department of Energy to develop a quantum computer "powerful enough for scientific research" within two years, with a commercially relevant machine targeted by the end of Trump's term. The administration awarded $2bn in grants across nine companies, with IBM receiving the largest allocation at roughly $1bn, according to reports. GlobalFoundries received $375m, while D-Wave Quantum, Rigetti Computing and Infleqtion each received about $100m. The government will take equity stakes in return, a departure from traditional federal research funding that typically carries no claim on upside. The transition from research project to commercial product represents a critical inflection point for quantum computing, a technology that uses subatomic particles called qubits to solve problems classical computers cannot. IBM, Microsoft and Google each target 2029 for their first large-scale commercial devices, but the government's equity-for-grants structure adds a new dynamic to the competitive field. The shift toward commercialization requires solving fundamental engineering challenges. Qubits must be maintained at temperatures near absolute zero to remain stable, and even minor vibrations or electromagnetic interference can introduce errors. IBM has pursued a strategy of gradually increasing qubit counts while improving error-correction rates, a path it calls quantum-centric supercomputing. The second executive order signed by Trump accelerates the government's migration to post-quantum cryptography to 2031, pulling forward a transition that agencies had been planning at a more gradual pace. The National Institute of Standards and Technology has been leading the effort to identify quantum-resistant encryption algorithms that can withstand decryption by a future quantum computer. The migration requires re-engineering the algorithms that protect classified communications, financial systems and critical infrastructure. Energy Secretary Chris Wright described quantum computing as the third pillar of future computing technology, joining artificial intelligence and high-performance computing powered by advanced semiconductors. "We're not there yet. We're close, but with this executive order and this coordinated effort, we will have scientifically relevant — meaning error-corrected — quantum computing during this administration," Wright said during the signing ceremony. For investors, the timeline matters. IBM's quantum commercialization push comes as its legacy consulting and mainframe businesses provide stable cash flow to fund long-term research. The $1bn federal grant, structured as an equity stake, reduces IBM's research and development burden while giving the government a direct interest in the company's success. Rivals including Google and Microsoft are pursuing different technical approaches, meaning the quantum race remains wide open. The 2028 federal target creates a hard deadline that could accelerate consolidation or partnerships across the sector. This article is for informational purposes only and does not constitute investment advice.
IBM shares jumped nearly 5% in premarket Tuesday after JPMorgan upgraded the stock to Overweight, citing accelerating software growth and AI adoption. "We are upgrading to Overweight with greater confidence in a second-half 2026 software acceleration following a deeper look at IBM's software business," analyst Brian Essex said in a note to clients Tuesday. Essex raised his price target to $291 from $270, implying about 15% upside from Monday's close. Software now accounts for roughly 45% of IBM's revenue and about two-thirds of consolidated profit, the analyst noted, adding that the shift toward software supports higher margins and better cash conversion. He pointed to tailwinds from Red Hat and OpenShift migration, as well as automation acceleration following the HashiCorp acquisition. The upgrade aligns with broader Street sentiment — 15 of 25 analysts covering IBM rate it a buy or strong buy, according to LSEG data. Shares remain down roughly 15% year to date, suggesting the market has yet to fully price in the software transformation. Morgan Stanley also raised its price target on IBM to $267 from $225 this week, keeping an Equal Weight rating, while noting that Wall Street estimates for 2026 and 2027 "look too low." The firm cited resilient enterprise server demand and growing AI-related infrastructure requirements. JPMorgan said that if IBM succeeds in becoming a significant beneficiary of growing AI demand, there could be room for multiple expansion. The company also stands to benefit from new US quantum computing initiatives, with Chief Executive Officer Arvind Krishna present at the White House when President Donald Trump signed executive orders directing accelerated domestic quantum development. The upgrade signals that Wall Street is beginning to recognize IBM's software-driven margin expansion and recurring revenue quality. Investors will watch the company's second-half 2026 results for evidence of the acceleration Essex expects. This article is for informational purposes only and does not constitute investment advice.
**IBM is bringing frontier AI into enterprise security operations through OpenAI's Daybreak Cyber Partner Program, joining a wave of industry efforts to counter machine-speed threats.** IBM joined OpenAI's Daybreak Cyber Partner Program on Monday, bringing frontier AI models into enterprise security operations to help companies detect and respond to cyber threats that now move faster than human analysts can track. "The speed of modern cyber attacks demands a fundamentally different approach to defense — one that pairs human expertise with AI systems capable of reasoning at machine speed," Fouad Matin, OpenAI's cyber tech lead, said. The partnership gives IBM access to OpenAI's latest cybersecurity models, including GPT-5.5-Cyber, which scored 85.6 percent on the CyberGym benchmark — surpassing Anthropic's Mythos 5 at 83.8 percent. IBM will integrate these models into its existing security operations platform, which serves more than 4,000 enterprise clients globally. The deal positions IBM to capture a larger share of the enterprise cybersecurity market, projected to reach $345 billion by 2028, according to Gartner. IBM's security business generated $4.6 billion in revenue in 2025, and the OpenAI integration could accelerate growth as companies race to adopt AI-powered defenses. ## A Coordinated Push Across the Industry The IBM-OpenAI partnership is part of a broader industry mobilization. OpenAI separately announced Patch the Planet, a program founded with Trail of Bits and in collaboration with HackerOne and Cali that offers free security consulting to open-source maintainers. More than 30 open-source projects are already participating, and the initiative has uncovered hundreds of bugs and produced dozens of patches in its first week, Trail of Bits CEO Dan Guido said. Chainguard, a software supply chain security company, launched its own coalition called Athena with more than two dozen corporate backers including JPMorgan Chase, Cisco, Cloudflare, and Docker. Athena has processed more than 20,000 findings and delivered 2,000 patches across 500 projects since going live, Chainguard CEO Dan Lorenc said. ## Why the Urgency Now The Five Eyes intelligence alliance warned in a joint statement Monday that "frontier AI models are anticipated to exceed current industry expectations, fundamentally transforming both offensive and defensive cyber capabilities. The timeline is not years, it is months." Open-source developers — typically volunteers maintaining critical infrastructure with limited resources — are already struggling with a backlog of bug reports. The rise of AI-powered vulnerability hunting has made the problem worse, as automated tools generate large volumes of low-quality reports that pull attention away from genuine critical flaws. For investors, the IBM-OpenAI partnership shows that enterprise cybersecurity is becoming a key battleground for AI monetization. IBM shares trade at 22 times forward earnings, and the security business could see margin expansion as AI-driven automation reduces the need for manual threat analysis. Competitors including CrowdStrike and Palo Alto Networks are also investing heavily in AI capabilities, making this a race to deploy the most effective models at scale. This article is for informational purposes only and does not constitute investment advice.
International Business Machines Corp. shares fell 7% on Thursday, extending a two-week decline after sector peer Accenture Plc lowered its full-year revenue guidance and triggered a selloff across information technology services stocks. Accenture narrowed its fiscal 2026 sales forecast to $71.76 billion to $72.46 billion, down from a prior range of $71.76 billion to $73.16 billion, the Dublin-based company said in a statement. Wall Street analysts had projected $74.01 billion. The consulting firm also reported third-quarter revenue of $18.70 billion, missing the $18.75 billion consensus estimate, while adjusted earnings per share of $3.80 topped the $3.69 average analyst forecast. IBM's slide adds to a pullback from an early June record near $333, leaving the stock roughly 23% below that peak. The Armonk, New York-based company has beaten consensus earnings estimates for eight consecutive quarters. It is scheduled to report second-quarter results on July 22, with analysts projecting earnings per share of $3 on revenue of $17.85 billion. The selloff in IBM shows the pressure on legacy technology companies as investors scrutinize enterprise spending trends. The broader Dow Jones Industrial Average, of which IBM is a component, also faced headwinds as the technology sector led declines. The Cboe Volatility Index rose as traders hedged against further downside in equities. IBM's revenue grew about 9% year-over-year in its most recent quarter, a solid pace for a mature technology company, though investors are watching whether the company can sustain that momentum amid a cautious enterprise spending environment. The company has positioned its hybrid cloud platform, built around its Red Hat unit, and artificial intelligence offerings as key growth drivers. This article is for informational purposes only and does not constitute investment advice.
IBM fell 16% to $268.71 from its January high near $314.84, even as the company reported its highest first-quarter free cash flow in a decade. The decline has widened the gap between price and fundamentals to levels not seen in years, with the stock now trading at 22 times forward earnings. "IBM's Q1 was clean — software grew 11%, infrastructure surged 15%, and free cash flow hit a decade high," said Alex Sirois, a financial writer covering the stock. "The selloff reflects multiple compression from quantitative tightening under Kevin Warsh, not deteriorating business fundamentals." Of the 22 analysts covering IBM, 12 rate it a Buy or Strong Buy, 7 rate it a Hold, and 2 rate it a Strong Sell, with a consensus price target of $290.89. The stock has rebounded 22.5% from its recent lows but remains 8% lower year to date, while the S&P 500 has gained 10.7%. The divergence matters because IBM is delivering where it counts. Its generative AI book of business has reached $12.5 billion since inception, and the company has raised its dividend for 31 consecutive years, yielding 2.44%. The question is whether the market's macro-driven discounting is an opportunity or a warning. **What the Numbers Show** Q1 2026 revenue reached $15.92 billion, beating estimates by 1.7%, while earnings per share of $1.91 exceeded consensus by 5.45%. Free cash flow rose 13% year over year to $2.22 billion, the highest first-quarter total in a decade. Software revenue grew 11.3%, and infrastructure revenue jumped 15.3%, driven by a 51% surge in IBM Z mainframe shipments. The mainframe cycle is proving stronger than expected. The z17 platform's first-year installations have already surpassed the prior generation by more than $1 billion, and mainframes now handle 73% of global transaction value. IBM's Telum II processor processes 50% more AI operations per day than its predecessor, running models directly where enterprise data resides. Consulting remains the weak spot, growing just 1% on a constant-currency basis, signaling caution in enterprise discretionary spending. Total debt stands at $61.3 billion after acquisitions including Confluent, making the company sensitive to sustained rate increases. **The Risk-Reward at $268** At a forward price-to-earnings ratio of 22, IBM screens as undervalued relative to its growth trajectory. The 50-day moving average of $249.15 has flipped into support, and the 200-day moving average of $273.07 sits just above as overhead resistance. A retest of $260 would sharpen the asymmetry further, according to technical analysis. The broader market context adds pressure. The U.S. 10-year Treasury yield has climbed as Warsh's Fed maintains quantitative tightening, compressing multiples across enterprise tech. The U.S. dollar index has strengthened, adding headwinds for multinational earnings translation. IBM's annualized volatility tops 66%, reflecting the stock's sensitivity to macro shifts. What could invalidate the thesis: software growth slipping below 10%, the AI book stalling for two consecutive quarters, or z17 mainframe demand fading after the current refresh cycle. The next catalyst is Q2 earnings, where investors will watch for consulting acceleration and any upward revision to full-year guidance. This article is for informational purposes only and does not constitute investment advice.