Gartner

Darwinbox, a global HR technology platform, has appointed Akshay Murthy as Country Head for India. Murthy, who brings over 24 years of experience from Salesforce, Oracle, and IBM, will lead the company's enterprise growth in its home market. His appointment comes as Indian enterprises rapidly adopt AI in HR, with Deloitte reporting 40% of Indian firms using AI significantly versus a 28% global average. Darwinbox has responded by launching AI-native features like Super Agent and becoming the first HCM platform to launch a Model Context Protocol server. Murthy aims to close the gap between legacy HR systems and AI-native technology. Co-founder Rohit Chennamaneni highlighted that India serves as a model for fast-growing, multilingual markets globally. The company, founded in 2015, serves over 4 million employees across 130 countries.

1 reports · 1 sources · Updated Jul 27, 01:07 PM UTC

BloombergNEF (BNEF) has sharply raised its forecast for US data center electricity demand, projecting 194 gigawatts (GW) by 2035, an 83% increase from its December estimate. This would represent about 20% of total US power consumption, up from 5.9% today. The surge is driven by AI training and inference workloads, which are expected to account for nearly half of the capacity. BNEF warns that even record grid connection rates sustained through 2035 would leave a 19 GW supply shortfall. Regional impacts are significant: PJM Interconnection, serving Northern Virginia's data center corridor, could see 34% of its electricity go to data centers by 2035, while ERCOT in Texas would reach 22%. The report notes that nearly half of planned data center builds this year may be delayed or canceled due to transformer lead times of up to five years. Other forecasters, including EPRI and S&P, have also raised their estimates significantly.

1 reports · 1 sources · Updated Jul 22, 02:21 PM UTC

Pressure from President Donald Trump to manufacture advanced semiconductors in the U.S. is increasing costs and squeezing margins at TSMC, the world's leading chipmaker. Since Trump returned to power in 2025, TSMC has announced $200 billion in U.S. manufacturing commitments, including a recent $100 billion investment in Arizona facilities. While TSMC reported a 77.4% jump in second-quarter profit driven by AI demand, CFO Wendell Huang said overseas expansion is diluting gross margins by 2-4% over the next several years. Analysts estimate TSMC's U.S. chips cost 20-50% more than those made in Taiwan. The company is reportedly raising prices by up to 10% in 2027, with customers expected to absorb most of the higher costs due to TSMC's market dominance. The White House credits Trump's trade and economic policies for driving the investments.

1 reports · 1 sources · Updated Jul 22, 05:00 AM UTC

A survey by Avalara, a tax compliance AI firm, reveals that 92% of CFOs and senior finance executives feel personal pressure to demonstrate a return on investment from artificial intelligence. Only 7% of organizations prioritize AI governance over adoption speed. The survey of 1,505 executives in the U.S., U.K., Australia, and India found that 76% lack sufficient in-house expertise to understand their AI operations, and 44% are only somewhat confident they could explain AI agent actions to auditors. Half of respondents reported only limited measurable ROI from AI agents, and 23% said accountability for AI errors is unclear or falls to no one. The findings highlight a tension between rapid AI adoption and the need for proper controls, governance, and expertise, as global AI spending is forecast to surge 47% to $2.6 trillion in 2026.

1 reports · 1 sources · Updated Jul 21, 03:34 PM UTC

Nvidia has released new specifications and benchmarks for its Vera data center CPU, marking a strategic push into the server CPU market dominated by AMD and Intel. The company confirmed that Vera chips were delivered to major AI clients including OpenAI, Anthropic, and SpaceX in June 2026. Vera is Nvidia's first custom-designed server CPU, moving away from off-the-shelf Arm designs. The move is part of Nvidia's vertical integration strategy to sell complete computing racks. The article notes that the rise of agentic AI has increased the importance of CPUs, which are needed to manage data flow for AI agents. Wolfe Research estimates Vera chips will sell for about $5,000 each, with Nvidia shipping 1.3 million units this year. Nvidia claims the total server CPU market could eventually be worth $200 billion, compared to a current estimate of $37 billion.

1 reports · 1 sources · Updated Jul 21, 03:00 PM UTC

This Fortune analysis examines Bolt CEO Ryan Breslow's decision to eliminate his entire HR department, which he claimed was 'creating problems that didn't exist.' The author, an HR professional, argues Breslow was correct that something was broken—namely, that many people functions are built as reactive compliance mechanisms rather than strategic drivers. However, the author contends Breslow was wrong to blame the function itself, noting that he later had to staff a 'people ops' team to handle the same essential tasks. The piece contrasts compliance-focused HR with strategic people operations, citing Google's Project Oxygen as an example of the latter. It concludes that rebranding HR as 'People Ops' does not change the mandate given to it, and that true strategic value comes from empowering the function to read leading indicators and provide systemic insight across the organization.

1 reports · 1 sources · Updated Jul 21, 11:30 AM UTC

Bank of America's new no-fee rewards program, BofA Rewards, has enrolled over 3 million customers since its late May launch, with nearly one-third engaging with deals—three times higher than previous levels. The program removes the $20,000 minimum asset threshold, requiring only an eligible checking account, specifically targeting Gen Z. Shikha Narula, head of consumer deposits and rewards, stated the bank aims to build early relationships and trust with younger customers by offering benefits that resonate with their current life stage. Retail deals account for 45% of engagement, followed by gasoline at 20%. A Bank of America survey found 80% of Gen Z clients would use rewards to fund travel, reflecting a broader trend where consumers view rewards as part of their financial plan rather than just a perk. The program also offers experiential benefits at higher tiers, such as subscription credits.

1 reports · 1 sources · Updated Jul 21, 10:30 AM UTC

On July 14, 2026, IBM triggered a historic market rout after releasing preliminary Q2 results far below estimates, with revenue of $17.2 billion versus $17.86 billion expected. CEO Arvind Krishna cited clients diverting software budgets to AI infrastructure—servers, storage, and memory—to secure supply-constrained hardware ahead of price hikes. IBM shares fell up to 25%, wiping out over $50 billion in market value and dragging down software stocks like Microsoft and Salesforce, while semiconductor and cybersecurity stocks rallied.

29 reports · 5 sources · Updated Jul 23, 01:23 PM UTC

Heathrow Airport, the UK's busiest aviation hub, has successfully launched an AI-powered customer service agent named Hallie in partnership with Salesforce. Introduced in March 2025 via WhatsApp, Hallie handles traveler inquiries regarding security wait times, gate locations, and lost luggage without human intervention. This initiative stems from a three-year effort to deepen Heathrow's longstanding relationship with Salesforce, aiming to manage the increasing demand from nearly 85 million annual passengers. Peter Burns, Heathrow's director of digital, e-commerce, and marketing, highlighted that the tool significantly reduced the volume of customer support calls. Due to this success, Heathrow plans to expand Hallie's availability to its official website and mobile app later in the year. Industry experts note that customer service is an ideal starting point for AI adoption due to clear return-on-investment metrics, though they caution that maintaining up-to-date data is critical to preventing incorrect AI responses. This case illustrates the practical downstream effects of generative AI in high-traffic service environments.

1 reports · 1 sources

Major technology companies, including Coinbase, Amazon, Block, and Meta, are aggressively reducing their middle management layers, citing artificial intelligence as a catalyst for increased efficiency and flatter organizational structures. This trend, described by workers as an 'AI-fueled manager purge,' has led to significant workforce reductions, with Coinbase recently laying off 14% of its staff. Industry experts warn that while these changes aim to accelerate decision-making, they are eroding essential mentorship, support systems, and clear promotion paths for employees. Middle managers now face expanded responsibilities, often required to act as both supervisors and individual contributors, leading to increased pressure and potential bottlenecks. Data from Revelio Labs indicates a 42% drop in middle manager job openings in the US since 2022. Critics argue that this shift towards asynchronous, agent-driven management treats employees like 'guinea pigs' in an unproven structural experiment, potentially degrading product quality and workplace culture as human interaction diminishes in favor of AI-driven processes.

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Bitdefender highlights that the primary security risk for organizations is no longer external malware but the abuse of trusted administrative tools, known as Living-off-the-Land binaries (LOLBins). Analysis of 700,000 high-severity incidents revealed that legitimate tool abuse occurred in 84% of cases. To address this, Bitdefender introduces a complimentary 45-day Internal Attack Surface Assessment for organizations with over 250 employees. Utilizing GravityZone PHASR technology, the engagement profiles user-machine behaviors to identify and restrict unnecessary access to utilities like PowerShell and WMIC without disrupting business operations. The process involves behavioral learning, an exposure score review, optional reduction sprints, and a final quantification of surface shrinkage. Early adopters reported reducing their attack surface by 30% to 70%. This approach aligns with Gartner’s projection that preemptive cybersecurity and dynamic attack surface reduction will dominate IT spending by 2030, shifting focus from slow detection loops to proactive removal of attacker capabilities within Windows-heavy environments.

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eClerx Services Ltd announced its financial results for the fiscal year ending March 31, 2026, demonstrating robust growth despite macroeconomic challenges. Total revenue for FY26 reached INR 4,217.4 crore, a 22.6% increase from the previous year, while operating revenue in US dollars stood at USD 468.9 million, reflecting a 17.9% rise. Net profit surged by 30.5% to INR 706.2 crore, and EBITDA grew by 28.8% to INR 1,152.6 crore. For the fourth quarter alone, revenue climbed 23.9% year-over-year to INR 1,135.4 crore. The company also reported a 33.5% increase in basic earnings per share and expanded its delivery headcount by 16.9% to 22,518 employees. Managing Director Kapil Jain attributed the performance to steady client momentum and disciplined execution. Additionally, eClerx was recognized as a Representative Vendor in the Gartner Market Guide for Digital Shelf Analytics. The firm continues to focus on AI-powered analytics and digital operations, serving Fortune 500 clients globally across various sectors including financial services and retail.

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This article argues that identity security for AI agents has become a critical board-level responsibility, transcending mere compliance to become a competitive liability. Despite 91% of enterprises running AI agents, only 32% govern them with the same rigor as human identities, creating significant security gaps. The text highlights the prevalence of 'shadow AI' deployed without oversight and outdated credential systems that fail to address the accelerating threat landscape. It posits that effective governance actually accelerates innovation by allowing organizations to deploy new capabilities confidently, whereas competitors lacking frameworks face bottlenecks. The author outlines a three-step strategy for boards: discover all agents including shadow AI, protect them with least-privilege permissions and automatic rotation, and govern them through a unified control plane like Okta. The core message is that speed in AI adoption comes from control, not recklessness, and organizations that integrate AI agents into existing identity frameworks as first-class identities will gain a distinct competitive advantage.

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This technical article outlines six fundamental SQL patterns used by data analysts to detect fraud in transaction logs, emphasizing that structured query language remains more effective than hyped machine learning or graph database solutions for many integrity tasks. The author, working in program integrity for government benefits, demonstrates how these methods apply universally to credit cards, healthcare claims, and e-commerce. The text details the first two patterns: Velocity and Impossible Travel. Velocity detection identifies rapid successive transactions, such as card-testing rings or benefit trafficking, by analyzing transaction counts within specific time windows like one minute or one hour. The author provides SQL code examples using window functions to flag anomalies while accounting for legitimate high-frequency users through whitelisting. The second pattern, Impossible Travel, detects physically impossible movement between transaction locations, such as a card being used in Chicago and Los Angeles within minutes, indicating cloning. The article serves as a practical guide for data professionals, offering executable code snippets compatible with major databases like Snowflake and BigQuery, aiming to help teams build robust, initial fraud detection layers on new datasets.

1 reports · 1 sources

This article analyzes the transformative shift from an exploratory web, where users navigate pages, to a resolutive web driven by AI agents that execute tasks directly. Citing 2024 Gartner predictions realized in 2026, it notes that traditional search engine traffic has declined significantly, with major retailers like Walmart, Etsy, and Target now receiving substantial traffic from AI platforms such as ChatGPT. This evolution introduces 'agentic commerce,' where AI agents compare prices, check reputations, and complete purchases without human browsing. Consequently, digital marketing strategies are pivoting from Search Engine Optimization (SEO) to AI Optimization (IAO). Unlike SEO, which focuses on keyword ranking, IAO prioritizes data integration, structured reputation, and API accessibility to ensure AI agents choose specific services. The article argues that this transition centralizes power, positioning AI interfaces as 'aggregators of aggregators' that control user journeys across sectors like retail, travel, and finance. This structural change challenges the traditional advertising model and redefines how businesses must optimize their online presence to remain visible and chosen in an automated digital ecosystem.

1 reports · 1 sources

Despite significant headwinds in AI infrastructure, including a 60% rise in memory prices, power grid constraints, and chip shortages lasting through 2026, investment in AI continues to offer unbeatable returns. The article distinguishes between the rapidly declining cost per token and the slower improvement in cost per useful task, noting that complex agentic workflows require more compute but deliver higher value. Multi-agent coordination is identified as a critical multiplier, potentially boosting productivity by 2-6x over two years compared to single-agent approaches. While physical scarcity in power, memory, and chips drives a projected 1.5-2x cost increase for cloud buyers relative to a no-scarcity scenario, the enhanced capabilities of AI systems ensure that every dollar spent yields 70-400% more useful work within two years. Major industry players like NVIDIA, AMD, Microsoft, and Anthropic are central to this shift, with enterprise adoption of task-specific agents expected to surge. Ultimately, while infrastructure costs are rising due to supply constraints, the efficiency gains from advanced AI workflows decisively favor continued investment.

1 reports · 1 sources

Adastra Corporation has been recognized as one of Canada’s Best Managed Companies for the 24th consecutive year, receiving the prestigious 2026 award. This program honors private Canadian-owned companies with revenues exceeding $50 million that demonstrate excellence in strategy, culture, innovation, governance, and financial performance. André Nadeau, CEO of Adastra North America, highlighted the transformative impact of Carlyle’s majority stake, which provides capital for organic growth and targeted mergers and acquisitions. The company also achieved significant milestones in artificial intelligence and cloud computing, including recognition as an Emerging Visionary in Gartner’s Generative AI Consulting quadrant. Adastra strengthened its partner ecosystem by attaining AWS Premier Partner Tier status and earning all Microsoft AI specializations. Additionally, the firm expanded its industry-specific practices in sectors such as Financial Services, Healthcare, and Manufacturing, while launching new agentic AI offerings. The award underscores Adastra’s adaptability, sustained growth, and commitment to helping clients leverage data and AI for operational efficiency and revenue generation in a rapidly evolving market.

1 reports · 1 sources

Adastra Corporation has been recognized as one of Canada’s Best Managed Companies for the 24th consecutive year, receiving the prestigious 2026 award. This program honors private Canadian-owned companies with revenues exceeding $50 million, evaluating them on strategy, culture, innovation, governance, and financial performance. André Nadeau, CEO of Adastra North America, highlighted the transformative impact of Carlyle’s majority stake, which provides capital for organic growth and targeted mergers and acquisitions. The company also achieved significant milestones in artificial intelligence and cloud computing, including recognition as an Emerging Visionary in Gartner’s quadrant for Generative AI Consulting. Adastra strengthened its partner ecosystem by attaining AWS Premier Partner Tier status and earning all Microsoft AI specializations. Additionally, the firm expanded its industry-specific practices in sectors such as Financial Services, Manufacturing, and Healthcare, while launching new agentic AI offerings. With a high consultant certification rate and a focus on helping clients improve efficiency through AI tools, Adastra continues to demonstrate sustained growth and adaptability in response to market changes, solidifying its position as a leader in data and AI solutions globally.

1 reports · 1 sources

Financial services companies face unique challenges in adopting agentic AI due to strict regulations and the need for real-time responsiveness. According to MIT Technology Review, the success of these autonomous systems depends less on model sophistication and more on the quality, security, and accessibility of underlying data. Steve Mayzak from Elastic emphasizes that agentic AI amplifies data weaknesses, requiring firms to establish trusted, centralized data stores. Regulatory compliance demands auditable and governable data processes, ensuring that AI decisions are transparent and explainable. Furthermore, financial institutions must handle both structured and unstructured data, such as natural language from customer interactions, which is often messy and difficult to organize. Without well-indexed and consolidated data, AI agents risk providing inconsistent answers or hallucinating, undermining trust among regulators and customers. The article highlights that while agentic AI offers significant potential for optimizing complex workflows, firms must first overcome data silos and ensure deterministic outcomes from non-deterministic models. This preparation is essential for maintaining speed, accuracy, and accountability in a high-stakes environment where market conditions shift rapidly.

1 reports · 1 sources

This article analyzes the current state of artificial intelligence adoption within the banking sector, arguing that while financial institutions have become proficient at launching AI initiatives, integrating them into core operations remains a significant challenge. Major banks like HSBC, Santander, and Bank of America, along with fintechs like Revolut and Starling, are actively deploying AI assistants and agents. However, the author contends that these launches often mask underlying operational inefficiencies, where AI tools are layered atop fragmented legacy systems governing product rules, pricing, and approvals. The piece highlights a critical distinction between treating AI as a superficial feature versus embedding it into the fundamental operating model. Citing Gartner research predicting that over 40% of agentic AI projects may be cancelled by 2027 due to high costs and weak value, the article warns against mistaking pilot successes for true transformation. The central argument is that the industry must move beyond the 'theatre' of launch announcements to address the complex realities of governance, risk control, and seamless workflow integration to achieve genuine operational capability.

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This financial analysis argues that while fears regarding generative and agentic AI have significantly compressed valuation multiples across the Information Services sector since mid-2025, the industry faces no total replacement. The author highlights that stable 2026 earnings per share estimates indicate AI has not yet materially impacted revenues, suggesting that recent stock declines are driven by sentiment rather than fundamental deterioration. Consequently, the article identifies a buying opportunity in Thomson Reuters (TRI), citing its exclusive data assets and deep regulatory integration as strong defenses against AI substitution risks. In contrast, the author recommends holding Gartner, positing that its research platforms are more vulnerable to disruption by AI synthesis tools. The piece serves as a strategic investment guide, urging investors to distinguish between companies with defensible proprietary data moats and those offering services easily replicated by artificial intelligence. It concludes that the market's bearish sentiment creates a disconnect with earnings stability, particularly for TRI, making it an attractive asset amidst broader sector underperformance compared to the S&P 500.

1 reports · 1 sources

The global logistics software market is projected to reach USD 35.84 billion by 2033, with a significant shift toward using Flutter for application development. Supply chain leaders are increasingly adopting Flutter to address critical operational challenges, particularly the lack of end-to-end visibility affecting 76% of businesses. By utilizing a single codebase for iOS, Android, and web platforms, companies can deploy driver, dispatcher, and customer tracking apps simultaneously, reducing engineering headcount requirements. This approach leverages Flutter’s Impeller rendering engine for smooth real-time GPS tracking and map updates. Furthermore, Flutter significantly cuts time-to-market, with logistics teams halving release timelines compared to native development. The framework’s large talent pool, representing 46% of cross-platform developers globally, facilitates faster staffing. Case studies from Google Pay and eBay demonstrate substantial reductions in engineering effort and code redundancy. Additionally, Flutter supports robust offline-first architectures using libraries like Drift and Hive, ensuring continuity in connectivity-challenged environments such as cold-storage warehouses and rural delivery routes. This strategic adoption enhances operational efficiency, reduces last-mile delivery costs, and improves service level agreement compliance across the logistics industry.

1 reports · 1 sources

This financial analysis highlights three technology stocks—Rubrik, Nice, and Nebius—as high-growth investment opportunities with the potential to generate significant wealth. Rubrik, a cybersecurity firm founded in 2014, is praised for its AI-driven data protection and rapid recovery solutions, boasting a 53% revenue increase and a projected shift to profitability amidst a growing cyber threat landscape. Nice, established in 1986, is leveraging agentic AI to automate customer service interactions for major clients like Toyota and Lowe's. With $3 billion in annual revenue and strong positioning in the rapidly expanding contact center market, Nice is expected to benefit from the 44% annual growth predicted for the agentic AI industry. Finally, Nebius is identified as a specialized cloud computing provider for AI innovators. Its selection by Microsoft to provide critical infrastructure underscores its emerging prominence in democratizing AI capabilities. The article argues that while many tech stocks are stable, these three companies possess unrealized competitiveness and operate in high-growth sectors like cybersecurity and AI infrastructure, offering substantial upside for investors willing to accept associated risks.

1 reports · 1 sources

A recent study by Globalization Partners reveals a significant shift in executive attitudes toward human labor following the adoption of artificial intelligence. The survey of 2,850 senior executives found that 82% are less likely to value human employees after using AI tools, viewing them as secondary to automated systems. Despite this sentiment, 60% acknowledge that humans currently lead work operations, with AI serving primarily as a productivity booster. However, the transition is fraught with challenges; 69% of executives now spend more time monitoring AI outputs due to lingering trust issues, with only 23% expressing total confidence in AI accuracy. Furthermore, financial returns have been underwhelming, with 73% reporting that ROI fell short of expectations and 16% experiencing negative ROI. Consequently, approximately 70% of leaders are prepared to cut AI budgets if goals are not met. This trend highlights a growing tension where executives increasingly perceive human workers as replaceable, even as they struggle with the reliability and profitability of the very technology intended to supplant them.

1 reports · 1 sources

This commentary argues that true workplace equity in the era of artificial intelligence depends on ensuring frontline employees have equal access to AI solutions, similar to those provided to desk-based workers. The author, Jeff Corbin, draws parallels between current AI deployment and the historical digital divide seen with corporate intranets, where non-desk employees in warehouses, retail, and healthcare were often excluded from essential communication tools. As organizations rapidly adopt AI to boost productivity and automate workflows, there is a significant risk that these technologies will primarily benefit office staff, thereby widening the existing equity gap. The article highlights that major technology providers and consulting firms often design AI tools and licensing models with desk-based users in mind, inadvertently marginalizing the frontline workforce. To prevent this recurring pattern of technological inequity, businesses must intentionally extend AI access to all employees, regardless of their work environment. The core message emphasizes that access to information and tools defines workplace equity, and without inclusive deployment strategies, frontline workers will remain disadvantaged in the evolving digital workplace.

1 reports · 1 sources

Google Cloud has been recognized as a Leader in the mid-cycle update of the Gartner Magic Quadrant for AI Application Development Platforms, maintaining its position highest in Ability to Execute. The company also achieved the number one ranking across three use cases in the associated Critical Capabilities report. This recognition follows significant platform evolution since the initial report last November, highlighted by the launch of the Gemini Enterprise Agent Platform at Google Cloud Next ‘26. This new platform unifies Vertex AI capabilities with breakthroughs from Google DeepMind to help enterprises build, scale, govern, and optimize production-ready AI agents. A core strategic principle emphasized is governance as a default feature, utilizing a unified trust framework that includes verifiable agent identities and secure gateways. By integrating Model Armor and leveraging the recent acquisition of Wiz, Google aims to connect code, cloud, and runtime for comprehensive risk management. The article cites L’Oréal as a key customer benefiting from this architecture, enabling a shift from scripted automation to autonomous agent orchestration while maintaining human oversight and global scalability.

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In 2026, the semiconductor sector is experiencing a significant rally, driven largely by artificial intelligence demand, with the PHLX Semiconductor Sector index rising 70%. While Nvidia maintains market dominance with an 81% share and record fiscal 2026 revenue of $215.9 billion, its stock has underperformed relative to AMD this year. AMD shares have surged 114%, fueled by strong Q1 revenue growth of 38% and lucrative contracts with OpenAI and Meta Platforms for 12 gigawatts of AI data center chips. Analysts project AMD's earnings to increase by 76% in 2026, matching Nvidia's projected 75% growth. However, Nvidia faces anticipated slowing growth to 35% in 2027, despite a massive $1 trillion order pipeline for its Blackwell and Vera Rubin processors. With AMD forecasting accelerated revenue growth and improved gross margins, it is positioned as a potentially better investment choice for 2026 compared to the established giant Nvidia, which continues to lead in market share but shows signs of growth deceleration in the near future.

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On May 4, 2026, Gartner published its Magic Quadrant for Cyberthreat Intelligence Technologies, positioning NSFOCUS in the Visionaries quadrant. This recognition highlights the company's technical expertise, comprehensive product portfolio, and mature solutions in the threat intelligence domain. The report notes that market growth is driven by increasing threat sophistication and the integration of generative AI into security operations. NSFOCUS leverages its Threat Intelligence (NTI) platform to integrate large language models and machine learning across the intelligence lifecycle, enabling automated collection, correlation, and actionable remediation recommendations. The company also emphasizes its advanced threat monitoring capabilities, backed by security laboratories that have identified nine APT groups. Furthermore, NSFOCUS addresses the gap between intelligence and business operations through its Threat Lens solution, which offers a closed-loop approach to risk visibility and control. By embedding threat intelligence into specific business contexts, NSFOCUS aims to help enterprises transition from reactive responses to proactive security postures. This inclusion underscores the growing importance of AI-driven threat intelligence and contextualized security solutions in the global cybersecurity landscape.

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CrowdStrike has announced a significant enhancement to its cybersecurity portfolio with the introduction of Falcon AIDR capabilities specifically designed to detect threats at the prompt layer within Kubernetes-based AI applications. Published on May 13, 2026, this update addresses the growing security challenges associated with generative AI and large language models deployed in cloud-native environments. As organizations increasingly integrate AI into their operational workflows, the prompt layer has emerged as a critical attack surface for adversaries seeking to manipulate model outputs or extract sensitive data. Falcon AIDR provides real-time visibility and protection against these sophisticated threats, ensuring the integrity of AI-driven processes. This development underscores CrowdStrike's continued focus on expanding its cloud and application security offerings, particularly in the realm of Agentic SOC and AI security. By securing the interaction between users and AI models within Kubernetes clusters, the solution helps enterprises mitigate risks such as prompt injection attacks and data leakage. This announcement aligns with CrowdStrike's broader strategy to lead in cyberthreat intelligence and cloud-native application protection, reinforcing its position as a key player in modernizing security operations for the AI era.

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Major technology companies are moving away from using token consumption as a primary metric for measuring artificial intelligence adoption and value. Reports indicate that Amazon and Meta employees engaged in "tokenmaxxing," artificially inflating usage scores by delegating unnecessary tasks to AI agents to meet internal leaderboard targets. This behavior highlights the flaws of volume-based metrics, which often reflect inefficiency rather than business value and create unpredictable costs for finance teams. In response, Salesforce has introduced the Agentic Work Unit (AWU), a pricing and measurement model based on discrete tasks completed by AI agents, such as resolving customer inquiries or executing workflows. This shift aims to provide greater cost predictability for enterprises and align AI usage with tangible outcomes. As agentic AI is forecasted to account for 30% of enterprise software revenue by 2035, the industry is prioritizing metrics that measure actual work done over raw data processing volume. This transition addresses the growing disconnect between technical activity and financial visibility, offering a more honest assessment of AI productivity while mitigating the perverse incentives created by traditional token-based tracking systems.

1 reports · 1 sources