Walmart has introduced usage limits on its internal AI assistant, Code Puppy, after employee demand exceeded expectations. Previously available without restrictions, the tool — designed to assist with tasks like spreadsheet analysis and presentation creation — is now subject to token-based usage caps per employee. The policy shift is a cost control measure driven by the transition of large language models (LLMs) from flat-rate subscriptions to pay-per-use pricing. With a workforce of approximately 2.1 million, even minimal per-employee AI usage can generate substantial costs for the retail giant. Walmart continues to encourage staff to leverage AI where it delivers genuine value.

E.ON is modernising its energy infrastructure by standardising grid data through SAP S/4HANA and migrating to cloud ERP. Managing operations across energy grids, customer solutions, and energy infrastructure solutions, the utility giant requires continuous IT investment to maintain stability and resilience. Leadership initially challenged large-scale technology spending, but the engineering team demonstrated that sustained financial commitment ensures long-term system performance and affordability. With growth, sustainability, and digitalisation as core corporate objectives, E.ON recognises that falling behind in technical capabilities carries significant financial risk. Infrastructure standardisation drives improved uptime and enables AI deployments, positioning E.ON to compete effectively in an increasingly digitised energy landscape.

Discover how GitHub Copilot's new token-based billing system, effective June 1, 2026, is impacting developers and organizations worldwide. While subscription prices remain unchanged, credits now determine access to AI models, with many users reporting significantly higher costs compared to the previous flat-rate model. Learn what these changes mean for your software development budget and how to manage your GitHub Copilot usage more efficiently.

Discover how artificial intelligence is reshaping news distribution and journalism's future. As AI-driven search and conversational interfaces become the new "front door" to information, publishers face growing challenges around visibility, trust, and sustainability. Newsweek CEO Dev Pragad explores how AI summarisation is reducing direct traffic to original sources, disrupting the referral patterns that digital journalism has long relied upon — and what media leaders must do to adapt.

Discover how AI is transforming video game development in 2025, with 90% of developers integrating AI tools and a 681% surge in AI-disclosed titles on Steam. Explore groundbreaking applications including Ubisoft's Ghostwriter for NPC dialogue generation, large language models enabling genuine character memory, and real-time adaptive gameplay systems. Learn how AI is revolutionizing smart NPCs, dynamic difficulty adjustment, and branching narratives, fundamentally restructuring the entire game development pipeline from concept to launch.

Discover how automation is transforming forex trading through advanced forex robots that execute trades based on pre-programmed rules. These increasingly refined tools allow traders to participate in financial markets without constant chart monitoring. Learn about the evolution of automated trading systems, their growing sophistication, and how they scan markets for opportunities. Explore the best forex robot reviews to understand current applications and future developments in automated forex trading technology that's making market participation more accessible and efficient for traders worldwide.

Urban Outfitters Inc. (URBN) is leveraging agentic AI to automate weekly performance reporting across its portfolio of brands, including Anthropologie and Free People. By deploying AI systems that analyze store-level data, the retailer generates consolidated weekly summaries for merchandising teams, replacing the manual review of over 20 separate reports every Sunday. This automation streamlines data collection and analysis, allowing staff to focus on decision-making rather than time-consuming data organization. The initiative highlights a growing trend of agentic AI entering everyday enterprise retail operations, offering a practical model for how brands can reduce operational workload while improving the speed and efficiency of business insights.

Debenhams is pioneering agentic AI commerce in the UK through a PayPal app integration, becoming the first UK retailer to test an automated checkout flow within a payment provider's ecosystem. The pilot targets mobile checkout abandonment by enabling shoppers to use natural language prompts to discover products from brands including boohoo, Karen Millen, and PrettyLittleThing. An AI assistant personalizes recommendations based on user profiles, budgets, and preferences, replacing traditional keyword search. The assistant refines options through follow-up questions, and purchases are completed entirely within the chat window — reducing friction and keeping users inside PayPal's ecosystem throughout the shopping journey.

Goldman Sachs is deploying Anthropic's Claude AI model to streamline trade accounting and client onboarding, signaling a broader shift among major banks toward using generative AI for back-office efficiency. Leading financial institutions including JPMorgan Chase, Bank of America, and Citi are already leveraging large language models for tasks such as information retrieval, HR queries, and developer coding assistance. The latest trend focuses on automating operational workflows like document review, reconciliation, compliance checks, and KYC processes — areas traditionally dependent on large human teams. As generative AI moves beyond knowledge work into core operational tasks, banks are finding new opportunities to reduce costs and improve accuracy across complex, high-volume processes.

Alibaba's latest Qwen 3.5 series is reshaping the AI landscape by delivering frontier-level performance on commodity hardware. Closing the gap with leading proprietary models like GPT-5.2 and Claude 4.5, Qwen 3.5 offers enterprises a compelling open-source alternative with lower inference costs and flexible deployment options. Benchmarks show it competing directly on output quality, excelling in browsing, reasoning, and instruction following — making it a serious contender in the global AI race.

Anthropic launches Claude Opus 4.8, an enhanced AI model offering improved performance in coding, agent work, reasoning, and knowledge tasks. Available via claude.ai, Claude Code, and API, the update introduces customizable effort levels that control token usage, dynamic workflows with parallel sub-agents for complex tasks, and live message array modifications in the API without disrupting prompt cache. Pricing remains at $5 per million input tokens and $25 per million output tokens in standard mode, making it a cost-effective solution for developers and enterprises seeking advanced AI capabilities.

Discover how OpenAI's Frontier Governance Framework provides enterprise leaders with a practical blueprint for scaling safe, compliant AI deployments. Aligned with the EU's General-Purpose AI Code of Practice and California's Transparency in Frontier AI Act (TFAIA), this framework outlines structured approaches to systemic risk assessment and mitigation for high-capability machine learning models. Learn how organizations can translate these regulatory requirements into actionable business strategies, ensuring secure and responsible AI deployment pipelines at a global scale.

The NBA is planning to introduce an automated officiating system using AI and court-mounted cameras to handle objective decisions such as out-of-bounds calls. Commissioner Adam Silver, drawing comparisons to tennis's Hawk-Eye tracking technology, announced the initiative following a controversial call in Game 5 of the Western Conference Finals between the Oklahoma City Thunder and San Antonio Spurs. A disputed out-of-bounds ruling involving Victor Wembanyama and Chet Holmgren highlighted the need for greater accuracy. Silver confirmed the league's long-term goal is to remove such objective calls from on-court officials entirely, leveraging advanced technology to improve fairness and consistency in NBA officiating.

Google Pay is undergoing a major infrastructure overhaul to support AI agent-driven transactions. The update introduces the Universal Commerce Protocol (UCP) and a new server architecture, enabling autonomous AI agents to execute purchases without navigating human-facing checkout pages. By replacing UI-dependent processes with a stable, API-driven backend, Google Pay aims to become the central payment hub for machine-initiated transactions — from booking flights to ordering supplies — streamlining how AI agents communicate with merchants and payment systems at scale.

Discover how automated trading systems are transforming the foreign exchange market by replacing intuition with speed, data, and precision. Unlike manual trading, these intelligent tools operate continuously across multiple time zones, processing vast economic data without fatigue or emotional bias. By following clear, rule-based strategies, traders can navigate volatile currency markets more effectively, identifying patterns and pricing gaps that human traders might miss. Explore how embracing intelligent automation can bring greater discipline and structure to your forex trading experience.

Google is retiring its long-standing Display Network Ads, merging them into its AI-powered Demand Gen platform. This shift moves marketers away from manual campaign controls, replacing traditional banner ad targeting with automated, AI-driven placements across YouTube, Discover, and Gmail. Designed to compete with TikTok and Instagram's immersive formats, Demand Gen focuses on generating customer interest before a search query occurs, signaling a major transformation in digital advertising strategy.

Discover how enterprise AI initiatives stall between pilot and production — and what separates successful deployments from the "AI graveyard." Day two of TechEx North America's Enterprise AI Implementation track explored the real challenges of scaling AI: poor data quality, weak process design, limited operating authority, and insufficient risk controls. Sessions covered agentic AI for business impact, the buy-vs-build decision, durable ROI measurement, and autonomous decisioning. The core message was clear — launching an AI pilot is easy; sustaining it requires governance, adoption strategy, and measurable outcomes. Learn what it truly takes to move enterprise AI from experimentation to lasting impact.

Autonomous AI systems are expanding from digital platforms into physical spaces like warehouses and delivery networks, raising questions about whether existing AI regulations adequately address embodied AI risks. Current frameworks primarily focus on online harms such as bias and misinformation, but physical AI systems pose unique safety concerns affecting infrastructure and human wellbeing. Singapore's IMDA released its Model AI Governance Framework v1.5 for Agentic AI in May 2024, providing guidance for organizations deploying AI agents capable of planning, decision-making, and multi-step actions. These agents can interact with tools, external systems, databases, devices, and perform transactions, highlighting the need for comprehensive governance addressing physical-world AI deployment challenges.

American International Group (AIG) reports accelerated benefits from generative AI implementation, surpassing initial expectations in underwriting capacity and operational efficiency. CEO Peter Zaffino revealed that early projections, once considered "aspirational," have been exceeded, with the technology demonstrating "much greater" capabilities than anticipated. The insurer highlights significant improvements in submission processing workflows without requiring additional human resources, marking what Zaffino calls "the biggest surprise." These developments have direct economic implications for underwriting operations and portfolio management. AIG's fourth-quarter earnings disclosures provide concrete evidence of generative AI's measurable impact on throughput and workflow redesign, offering valuable insights for AI decision-makers evaluating enterprise-scale artificial intelligence deployments in the insurance sector.

Infosys, a leading technology services provider, offers comprehensive AI consultation and implementation through its Topaz Fabric platform. Currently engaged with 90% of its top 200 clients, the company manages over 4,600 active AI projects across multiple industries. Infosys's AI implementation strategy encompasses six key areas, including AI strategy and engineering, which focuses on designing business-aligned AI architectures. Their approach integrates AI agents, proprietary platforms, and third-party tools on specialized infrastructure, leveraging strategic partnerships with AI technology providers to deliver both discrete and organization-wide solutions.

Discover how DBS Bank and Visa are pioneering AI-driven payments through the Visa Intelligent Commerce pilot, enabling AI agents to autonomously search, select, and complete purchases on behalf of customers. This groundbreaking trial has already processed real transactions, including food and beverage purchases via DBS and POSB cards, marking a significant shift from AI as an advisor to AI as an active participant in commerce. Learn how banks are preparing for the future of agent-driven commerce, where intelligent systems execute transactions within customer and institution-defined rules, reshaping the way we think about everyday payments.

Discover how Hitachi and Siemens are challenging the Physical AI hierarchy dominated by OpenAI, Google, and Nvidia. Unlike foundation model giants, these industrial manufacturers argue that deploying AI in real-world environments requires a deep, systematic understanding of the physical world before machines can be effectively trained. Hitachi's Kosuke Yanai emphasizes that Physical AI cannot be successfully implemented in society without grounded, structured knowledge of physical systems. As this strategy moves from boardrooms to factory floors, Hitachi's approach signals a critical shift in how industrial AI should be developed and deployed. Learn why understanding the physical world may be the missing link in making Physical AI truly viable.

Amul, the world's largest dairy cooperative, has launched Amul AI featuring Sarlaben, an AI assistant serving 3.6 million women milk producers across Gujarat villages. Built on five decades of cooperative data and backed by India's MeitY and EkStep Foundation, this platform delivers 24/7 personalized dairy farming guidance in local languages through the Amul Farmer mobile app. Launched before India's AI Impact Summit 2026, it represents a groundbreaking test of AI's potential to reach rural communities, demonstrating how advanced technology can be deployed beyond Silicon Valley to serve grassroots agricultural networks and empower small-scale farmers with data-driven insights.

Discover how China has developed the world's first complete AI-generated energy grid mapping system to address surging electricity demands from artificial intelligence and data centers. As global data-center consumption approaches 1,000 TWh by 2030, major economies face unprecedented infrastructure challenges. US grid operator PJM has seen capacity prices surge tenfold in two years, while European utilities struggle to upgrade transmission networks. This groundbreaking Nature study from Peking University and Alibaba's DAMO Academy reveals China's solution: high-resolution AI mapping that coordinates renewable energy at national scale, potentially transforming how countries manage AI's massive power requirements and grid modernization challenges.

OpenAI announces its first Applied AI Lab outside the United States, launching in Singapore through a partnership with the Ministry of Digital Development and Information. The OpenAI for Singapore initiative, unveiled at the ATx Summit, includes over S$300 million in funding and will create 200+ technical roles. Singapore becomes a global hub for forward-deployed engineers working on AI deployment with organizations. The lab focuses on Singapore's AI Mission priorities including public service, finance, and digital infrastructure. OpenAI will collaborate with government agencies on education and workforce programs through the Ministry of Education and GovTech, while supporting educators via the Singapore chapter of OpenAI Academy.

Discover how AI is disrupting legacy financial systems as Anthropic's Claude Code tool threatens to automate COBOL modernization — work that once required years of expensive consulting. IBM shares suffered their worst single-day drop in over 25 years, plunging 13% after Anthropic claimed its AI can accelerate the painstaking process of updating ancient banking code. Learn what this means for the future of enterprise IT consulting and the global financial infrastructure that still runs on decades-old programming languages.

Nvidia's Q1 revenue surpassed expectations at US$81.62 billion, with Q2 guidance set at US$91 billion, outpacing Wall Street forecasts. But beyond the headline numbers, CEO Jensen Huang revealed a major strategic move: Nvidia's new Vera central processor targets a US$200 billion market entirely separate from its AI GPU lineup. Huang projects Vera chip revenue to reach US$20 billion by fiscal year-end, positioning it as Nvidia's second-largest revenue contributor. This signals a bold expansion beyond GPUs into CPU-driven inference computing, opening a powerful new growth front for the company.

Day two of TechEx North America focused on the critical challenges of AI adoption in enterprise environments. Sessions explored the concept of the "AI graveyard" — projects that succeed in pilot stages but fail in real-world deployment. Experts across multiple tracks offered actionable strategies to help businesses avoid stalled AI initiatives, including focusing agentic AI on specific business areas and building robust, agent-ready data foundations. The Enterprise AI Implementation, ROI, and Adoption tracks provided valuable insights into why AI projects falter and how organizations can drive successful, scalable deployments. Despite the sobering topic, the overall tone remained optimistic, equipping forward-thinking businesses with the tools and knowledge to navigate AI implementation challenges effectively.

Alibaba has launched the Zhenwu M890, a new AI processor developed by its semiconductor subsidiary T-Head, purpose-built for AI agent workloads. Delivering three times the performance of its predecessor, the M890 is designed to handle the unique demands of AI agents, including long-context retention, real-time model coordination, and complex multi-step task execution with minimal human intervention. Unlike standard inference chips, the M890 prioritizes memory bandwidth and inter-model communication. Paired with a multi-year silicon roadmap and a new large language model, Alibaba signals its ambition to build a fully integrated AI stack, going beyond simply addressing gaps created by US export controls.

Discover how TechEx North America explores the critical infrastructure needed around AI for enterprise success. Learn about edge computing's role in reducing latency, enhancing cybersecurity for IIoT/IT systems, and reassessing data asset value. Sessions cover scaling edge deployments across multi-site businesses, autonomous equipment decision-making, and processing speed requirements across Edge Computing, IoT, Data Centre Congress, and Cyber Security tracks.

AI applications depend on the quality and timeliness of their underlying data. Even well-tuned models and carefully designed systems lose effectiveness when business data arrives late or updates inconsistently. Real-time data pipelines have become essential to modern AI architecture, bridging the gap between source system changes and what AI systems can access and act upon. Unlike earlier offline experiments, today's AI workloads power copilots, recommendation engines, fraud detection, and retrieval-driven applications requiring live business context. Delayed data significantly impacts answer quality and decision-making speed, making real-time data infrastructure critical for maintaining AI system relevance and performance in production environments.

Amazon launches Alexa for Shopping, merging its Rufus chatbot with Alexa+ across its app, website, and Echo Show devices. The AI assistant answers product questions, compares items, tracks prices, manages shopping reminders, and handles automated purchases. Combining Rufus' product expertise with Alexa+'s personalized context, it helped over 300 million customers in 2025. While the Rufus name is being retired from the interface, it continues powering backend features. CEO Andy Jassy reports Rufus monthly active users increased 115% with engagement up nearly 400% year-over-year, demonstrating significant growth in AI-powered shopping assistance.

Basware launches AI agents for invoice lifecycle management, advancing toward "Agentic Finance" where AI systems autonomously handle finance tasks within controlled parameters. CEO Jason Kurtz envisions near-perfect touchless invoice processing, targeting 100% automation, compliance, and protection. The AI agents focus on accounts payable operations, working within existing invoice workflows. The AP Business Agent offers contextual guidance and recommends next steps based on transaction status, enhancing InvoiceAI platform capabilities for smarter, faster financial decisions and improved business outcomes.

Agentic finance AI can significantly improve business efficiency and ROI when implemented with proper governance and clear investment targets. However, an FT Longitude survey reveals 61% of finance leaders across the US, UK, France, and Germany have only deployed AI agents experimentally, while 25% lack full understanding of practical applications. To move beyond experimentation, finance departments require governed systems combining language processing with business logic. Invoice Lifecycle Management platforms now feature AI agents using generative AI, deep learning, and natural language processing to automate invoice processing and accounts payable workflows, from data ingestion to reconciliation, enabling human employees to focus on strategic tasks.

Discover how ASML's High-NA EUV machines are now production-ready, marking a major breakthrough in AI chip manufacturing. These next-generation extreme ultraviolet lithography tools enable chipmakers to print finer, denser circuit patterns, overcoming the physical limitations of current EUV technology. Learn how this advancement will power more efficient AI accelerators and large language models, shaping the future of semiconductor innovation.

AI adoption in financial services has reached near-universal status, with only 2% of institutions reporting no AI use, according to Finastra's 2026 report surveying 1,509 senior executives across 11 markets. Sixty percent of institutions enhanced their AI capabilities in the past year, with 43% identifying AI as their most critical innovation lever. AI now permeates the entire financial value chain, from fraud detection and document intelligence to compliance automation and customer engagement. However, as adoption becomes standard, mere deployment no longer provides competitive differentiation. Financial institutions face mounting pressure to move beyond experimental pilots and demonstrate tangible business value from their AI investments.