This story was originally published on CIO Dive. To receive daily news and insights, subscribe to our free daily CIO Dive newsletter. Dive Brief: Data infrastructure issues are derailing enterprise AI investments, leading to $108 billion in wasted annual AI spend, according to a Hitachi Vantara analysis released Tuesday. The tech provider surveyed 1,200 IT decision makers for its report. More than 4 in 5 businesses with mature data estates reported ROI on their AI investments, compared with less than hal ...

Core Insights - The infrastructure supporting artificial intelligence is undergoing a significant transformation, driven by the convergence of open formats, AI capabilities, and the unsustainable costs of integrating numerous tools [1][2]. Group 1: Importance of Fundamentals - Basic skills remain crucial as architecture changes can disrupt pipelines, and data quality issues continue to plague organizations, costing an average of $12.9 million annually due to poor data quality [2][11]. - The key challenge by 2026 will not be the existence of these issues but the speed and method of their detection and resolution [2]. Group 2: Metadata Layer as a Battleground - The storage layer competition has concluded with Iceberg, Delta Lake, and Hudi emerging as winners, while Parquet has become the common language for data storage [3][6]. - The focus is shifting upstream to the metadata layer, which is becoming the operational backbone of data management, encompassing data lineage, quality rules, access policies, and business context [6][20]. Group 3: Simplification of Data Stacks - Organizations are experiencing tool fatigue, managing an average of 15 to 30 different tools across various data functions, which is unsustainable [7][9]. - By 2026, the integration process will accelerate, with platforms like Snowflake and Databricks consolidating functionalities to streamline data operations [10]. Group 4: Data Quality as a Business Function - Data quality metrics will shift from engineering-focused indicators to business outcomes, with organizations increasingly linking data pipeline failures to revenue impacts [11][12]. - By 2026, 80% of organizations are expected to deploy AI/ML-driven data quality solutions, emphasizing the need for accountability through data contracts between producers and consumers [12]. Group 5: AI Agents Replacing Dashboards - The traditional model of data observability through dashboards is becoming obsolete, with AI agents expected to take over operational responsibilities by 2026 [13][15]. - These AI agents will be capable of understanding business context, automatically tracing issues, and applying fixes, fundamentally changing the approach to data observability [15]. Group 6: AI Reshaping Data Infrastructure - The initial design of data stacks was for dashboard services, not AI workloads, but AI is now a primary user of data [16]. - By 2026, two types of companies will emerge: AI-native architectures designed for AI workloads and traditional stacks with AI capabilities added later [16]. Group 7: The Rise of Semantic Layers - Semantic layers, previously seen as optional, are becoming essential for AI applications, providing necessary context for data interpretation and ensuring data quality [17]. - These layers serve as a bridge between technical data and business meaning, crucial for AI agents to function effectively [17]. Group 8: Common Theme - A common theme across the predictions is the shift from passive to proactive data infrastructure, where systems will not only store and visualize data but also understand, reason, and act based on interactions [18][19].

Investment Rating - The report emphasizes that the highest return on investment in 2026 will come from modern data infrastructure rather than the latest AI models [11][14]. Core Insights - The gap between AI ambitions and actual operations is widening across industries, with organizations needing to focus on foundational work to achieve transformative wins [6][5]. - Companies are shifting from broad experimentation to specific, high-value use cases, moving AI from proof-of-concept to enterprise-level deployment [19][15]. - Successful organizations are prioritizing data lifecycle management, modernization, and human capabilities to shape their AI-driven transformation strategies [48][59]. Summary by Sections Overview - The report highlights a significant disconnect between organizational expectations of AI and the foundational work required for successful implementation [6][5]. - Many companies are still relying on outdated systems and manual processes, which hinders their ability to leverage AI effectively [6][9]. 2026 AI Trends - AI success in 2026 will be driven by data infrastructure rather than new models, with a focus on creating accessible and real-time data management systems [11][12]. - Organizations are expected to transition from broad AI experiments to targeted applications that deliver measurable business value [15][17]. Industry-Specific Trends - The report outlines predictions for various sectors, including: - Airlines will require rapid experimentation due to competitive pressures [65]. - Retail will see AI operating behind the scenes, influencing pricing and supply chain decisions [66]. - Healthcare will experience regulatory advancements that promote AI-driven innovations [69]. Preparing for 2026 - Companies need to invest in data management and governance to support AI initiatives effectively [48][51]. - A cultural shift is necessary for organizations to embrace AI as a core component of their business strategy rather than a standalone project [30][60]. Conclusion - The foundation laid in data infrastructure and governance will determine the success of AI initiatives in 2026, with companies that prioritize these areas likely to thrive [87][89].

Core Viewpoint - Marvell Technology has shown signs of improvement in its narrative and execution, leading to a positive shift in investor perception despite ongoing challenges with major customers like Microsoft and Amazon [2][4][11]. Financial Performance - Marvell exceeded Wall Street expectations with its recent earnings guidance, resulting in a significant post-earnings stock surge [3][4][11]. - The stock initially fell after earnings but later surged by as much as 14% before closing down from that peak [5][6][9]. Strategic Moves - The acquisition of Celestial AI is viewed as a strategic move to enhance Marvell's technical capabilities, particularly in high-growth sectors like AI and data infrastructure [3][12]. - Marvell's focus on custom accelerators and interconnects positions it well within the rapidly growing tech landscape, despite being smaller than competitors like Broadcom [10][11]. Market Position and Challenges - Marvell has historically struggled with execution and narrative challenges compared to larger rivals, but recent developments indicate a potential turnaround [6][13]. - Concerns remain about the potential loss of major XPU projects from key customers, but the company’s broader interconnect opportunities are expected to mitigate these risks [2][4][11].

Core Insights - Eaton Corp. announced a $50 million investment to expand its manufacturing capacity in Virginia, aiming to meet the increasing demand for data centers driven by AI and cloud growth [1][4] - The company plans to construct a 350,000-square-foot facility near Richmond to produce essential power-distribution equipment for data centers [1][2] - The expansion is expected to create approximately 200 new local jobs starting in 2026 [2] Manufacturing Expansion - The new facility will more than double Eaton's footprint in the Richmond area, consolidating and upgrading production of static power infrastructure [4] - The investment is part of a broader strategy to support rising demand for electrification and data infrastructure [5] - Since 2023, Eaton has invested over $1.2 billion in North American manufacturing [4] Market Context - The expansion responds to a record number of new data-center approvals in Virginia this year [3] - Virginia's state leadership has welcomed the investment, highlighting the readiness of local companies to meet growing power requirements [5] - The project is expected to strengthen the region's manufacturing base and job market [5] Stock Performance - Eaton Corp. shares rose by 1.41% to $346.58 at the time of publication [6]

Summary of NetApp Conference Call - December 09, 2025 Company Overview - **Company**: NetApp (NasdaqGS: NTAP) - **Industry**: Data Infrastructure and Storage Solutions - **Core Business**: Provides data storage solutions, including Keystone service in public cloud and traditional CapEx delivery through hybrid and all-flash solutions [8][10][54] Key Points and Arguments Core Enterprise Demand - **Current Demand Status**: Core enterprise demand is described as "not amazing, not terrible," with revenue growth in the mid-single digits in private Americas, APAC, and EMEA, indicating a tepid environment [10][12] - **Geographical Performance**: Approximately one-third of revenues come from EMEA, with Germany being a key market. The U.S. public sector business is down year-on-year due to cost-cutting measures [11][12][13] U.S. Public Sector Business - **Revenue Contribution**: U.S. public sector accounts for 10%-14% of total revenues, with about 75% from federal government contracts. This segment has been under pressure due to budget cuts [14][15][12] - **Segment Breakdown**: The federal business is divided into military, intelligence agencies, and civilian agencies, with no specific segment being highlighted as more affected than others [14][15] Supply Chain and Memory Chips - **Memory Component Costs**: DRAM constitutes a low single-digit percentage of costs, while SSDs are growing in importance. Total COGS is around $2 billion annually, with memory components being a minor part [18][19] - **Procurement Strategy**: NetApp manages supply chain costs by purchasing in volume and opportunistically, avoiding reliance on spot market prices [20][21] Pricing Strategy - **Price Management**: NetApp raises list prices in response to commodity cost increases while managing effective customer prices through discount strategies [21][22] AI and Storage - **AI Market Position**: NetApp anticipates growth in storage demand as AI spending shifts from training to inference, with 200 AI design wins reported, up from 100 a year ago [29][30] - **Data Lake Monetization**: Many design wins involve aggregating siloed data into data lakes, indicating that the industry is still transitioning towards AI inference workloads [31][32] Competitive Landscape - **Market Share**: NetApp holds a high teens market share in the all-flash market, gaining share as the market consolidates. The competitive environment is described as challenging but manageable [48][49] - **Emerging Competitors**: Smaller players are more disaggregated in their solutions, focusing on specific features, while NetApp continues to expand its all-flash and cloud offerings [51][52] Company Evolution - **Transformation**: NetApp has evolved from an HDD-centric company to a leader in all-flash solutions, with two-thirds of revenues now from all-flash products and a growing cloud business projected at $6.7 billion [54][55] Additional Insights - **Public Cloud Strategy**: NetApp's public cloud services are gaining traction, with a significant portion of new customers coming from this segment, indicating successful market penetration [44][46] - **Future Outlook**: The company is positioned for continued growth and innovation, adapting to changing market dynamics and customer needs [54][55]

Core Insights - The US stock market has experienced significant growth over the past seven months, with the S&P 500 index increasing by more than 30% from its year-to-date low in early April [1] Group 1: Market Performance - The S&P 500 index is currently up more than 30% compared to its low in early April [1] - The rally in the stock market is largely driven by enthusiasm surrounding artificial intelligence (AI) [1] - Resilient consumer spending has also contributed to the positive market performance [1] Group 2: Key Drivers - Artificial intelligence and data infrastructure are highlighted as major factors fueling the market rally [1] - The combination of technological advancements and consumer behavior is creating a favorable environment for stock market growth [1]

How much data do you think fuels Zentry’s adaptive AI?@Zentry zData layer aggregating 100+ social, onchain, and gaming sources and processes ~1TB of signals daily through a custom MCP/API stack to deliver fresh, contextual datasets for agentic reasoning.A glimpse at how real-time, participatory data infrastructure could reshape AI systems.Jeremy (@ItsFloe):As humans and AI become increasingly intertwined, the boundary between operator and system begins to blur.Real-time human signals, behavior, and feedback ...

~3k likes for a data infra change, to give you an idea of how big this is500 *billion* Solana txns, now searchablebut...it is not complete without an explorer that lets everyday people access thisbe a shame if we were to also release that todaytrillionsmert | helius.dev (@0xMert_):today, Solana changes foreverwe've solved the biggest data/RPC problem that existssolana historical/archival data — has now been redesignedquick context:today when you query historical data (getBlock/getTransaction/getSignaturesFo ...

Core Insights - The emergence of powerful market themes such as artificial intelligence, data infrastructure, and next-generation energy has led to significant stock performance, with companies like IREN Limited, Nebius Group N.V., and Oklo Inc. seeing gains of 300% to 400% year-to-date [1] - Recently, these high-growth stocks have faced pressure as the broader market consolidates, resulting in corrections of 20-30% in a short period [2] - Despite long-term potential, the near-term outlook indicates increased volatility, suggesting a cautious approach to selective buying [3] Company Performance - IREN, Nebius, and Oklo have experienced sharp declines following earnings downgrades, with IREN and NBIS seeing major revisions that have lowered their Zacks Ranks to 4 (Sell) [4][5] - IREN's current year earnings estimates have been reduced by nearly 40%, while NBIS's next quarter projections have dropped by 88% [5] - Oklo remains pre-revenue, highlighting its speculative nature despite a market cap of $20 billion, and is years away from generating meaningful cash flow [6] Profitability and Market Sentiment - Among the three companies, IREN is the only one currently producing positive earnings, while Nebius is loss-making and Oklo is still in development [7] - Stocks with little or no profitability tend to experience the steepest declines when market sentiment shifts [7] Technical Analysis - The technical outlook for IREN, Nebius, and Oklo is currently unfavorable, with all three stocks making new lows and lacking sustained buying pressure [9] - Each stock has retraced to its recent breakout zones, which are now being retested as support, indicating vulnerability in their setups [10] Future Outlook - A prolonged consolidation phase is anticipated for IREN, NBIS, and OKLO after recent drawdowns, with the potential for stronger advances in the future [13] - Patience is advised as the correction is not yet complete, and new bases need to form before considering entry points [15][16]