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.

Discover how MWC 2026 in Barcelona marked a turning point for AI-native networks, moving beyond vision to reality. Leading telecom vendors, chipmakers, and operators — including Nvidia, Ericsson, Nokia, Deutsche Telekom, and T-Mobile — unveiled field trial results, commercial product launches, and a major coalition committed to building 6G on AI-native foundations. Learn what this architectural shift in telecom infrastructure means for enterprise and IT decision-makers, and how AI-RAN is set to transform the way connectivity is delivered, managed, and monetised.

Discover how enterprise leaders are moving beyond generative AI to scale autonomous intelligence systems capable of independent execution. Learn why applications that traverse internal networks, execute multi-step logic, and finalize transactions without human prompting are now critical for driving real cost and revenue transformation in large organizations.

Discover the top real estate app development companies in the US for 2026, including LITSLINK, Code District, Empat, Helpful Insight, and DBB Software. These firms excel in PropTech solutions with expertise in MLS integrations, RESO Web API, tenant screening workflows, and MVP delivery. Real estate applications require complex data flows, compliance layers, and seamless connections to listing feeds, payment systems, and document workflows. Learn which vendors master essential integrations like IDX feeds and regional MLS providers, delivering reliable PropTech solutions beyond surface-level capabilities shown in marketing materials.

British technology company Humanoid will deploy 1,000 to 2,000 humanoid robots at German industrial supplier Schaeffler's global manufacturing sites by 2032. The first deployment is scheduled between December 2026 and June 2027 at two German locations, focusing on box handling in Herzogenaurach and factory testing in Schweinfurt. Humanoid will support integration into Schaeffler's existing production lines, building on their January technology partnership. The robots will perform physical tasks in production and warehouse environments, though contract value remains undisclosed.

Laserfiche has launched AI agents that streamline content management through natural language prompts, automating tasks while adhering to integrated security and compliance frameworks. Powered by generative LLM reasoning models, these intelligent assistants bridge the gap between automated workflows and manual processes, reducing time and resource costs. CEO Karl Chan highlights that AI Agents mark a shift in information lifecycle management, enabling organizations to modernize operations without compromising governance. By analyzing document data and executing tasks based on user instructions, Laserfiche AI agents empower businesses to enhance efficiency while maintaining regulatory compliance at every step.

Physical AI Expo North America returns to Silicon Valley on May 18–19, 2026, at the San Jose McEnery Convention Center. This premier two-day conference brings together AI innovators, robotics leaders, and enterprise technologists to explore the future of Physical AI — where intelligence meets real-world action. From industrial automation and logistics to autonomous systems and defense, discover how organizations are deploying AI that can sense, reason, and act at scale. Join the engineers and pioneers shaping the next era of robotics and intelligent machines.

Researchers at HiddenLayer uncovered a malicious Hugging Face repository disguised as an OpenAI Privacy Filter release, delivering infostealer malware to Windows machines. The fake repo, "Open-OSS/privacy-filter," copied OpenAI's original model card and included a malicious loader.py file designed to steal credentials. It recorded approximately 244,000 downloads and gained 667 likes within 18 hours before removal, though these figures may have been artificially inflated by attackers. The incident highlights growing cybersecurity risks in public AI model registries, as developers increasingly clone models directly into corporate environments, making the software supply chain vulnerable to such attacks.

Contrary to popular belief, your data doesn't need to be perfect before leveraging generative or agentic AI systems. According to Joe Rose, president at JBS Dev, modern AI tooling is better than ever at handling poor-quality data, making it accessible for businesses at any stage of data maturity. While vendors often push for massive data lakes and lengthy transformation programs, the reality is far more practical. Large language models can interpret incomplete inputs with remarkable accuracy. However, businesses must implement proper guardrails to manage the inherent unpredictability of AI models, ensuring human oversight remains part of the process for reliable, high-quality outputs.

Bain & Company projects a $100 billion US market opportunity for SaaS companies leveraging agentic AI to automate coordination work in enterprise systems. This estimate from Bain's AI software industry report series identifies significant value in eliminating manual tasks employees perform between enterprise applications like ERP, CRM, and support systems. The market potential lies in automating workflows that involve pulling data across systems, interpreting unstructured messages, and making decisions on approvals, responses, and escalations—tasks where traditional rules-based automation and robotic process automation fall short in handling ambiguity and dispersed information.

Artificial intelligence is revolutionizing corporate compliance through real-time background checks, automated payroll monitoring, and predictive analytics. HR tech now automates most regulatory requirements from GDPR to workplace safety. However, UK tech companies face a critical paradox: while building sophisticated automation tools, they cannot automate sponsor licence management for hiring international AI talent. This analogue compliance process creates immediate risks for employers and skilled workers alike, making immigration compliance the most stubborn exception in an otherwise automated regulatory landscape for technology companies.

Banco Santander and Mastercard have executed Europe's first live AI-initiated payment without human intervention, marking a milestone in "agentic payments." The transaction used Mastercard Agent Pay framework within Santander's regulated banking infrastructure, allowing AI software to act as an authorized payment participant. Operating under strict security, governance, and compliance protocols, the AI agent completed the end-to-end payment within predefined limits and permissions. This pilot demonstrates how AI systems can autonomously execute financial transactions on behalf of customers while maintaining regulatory standards, representing a significant advancement in automated banking services and AI-driven financial operations.

The adoption of physical AI is transforming frontline customer service by combining digital intelligence with human-like interaction, delivering measurable ROI as businesses face labor shortages. A partnership between KDDI and AVITA showcases how humanoid deployment addresses complex operational challenges that traditional automation cannot solve. Unlike conventional industrial robots limited to repetitive tasks, these humanoids handle unexpected anomalies and excel in customer-facing roles through nonverbal communication including synchronized nodding, natural eye contact, and reassuring facial expressions. By merging AVITA's avatar creation technology with KDDI's communications infrastructure, they're developing domestically-produced humanoids designed for seamless operation in real-world commercial environments.

Artificial intelligence is revolutionizing forex trading, with the global AI market valued at $375.93 billion and projected to reach $2.48 trillion by 2034. AI forex automation software now enables traders to analyze vast amounts of data and execute trades with millisecond precision, replacing traditional chart analysis and instinct-based decisions. The AI trading platform market has already reached $220.5 million and is expected to grow to $631.9 million by 2035. Industry experts report that over 70% of forex trading now involves AI technology, demonstrating its dominant role in modern financial markets and transforming how traders approach currency exchange.

Alphabet's Intrinsic, which develops AI software to make industrial robotics more accessible to manufacturers, has officially joined Google as a distinct group. After graduating from Alphabet's X moonshot division in 2021, Intrinsic will now collaborate closely with Google DeepMind, leveraging Gemini AI models and Google Cloud infrastructure. This strategic integration signals Google's commitment to democratizing industrial automation by simplifying robotic programming, which traditionally requires extensive specialist engineering expertise. The move represents more than an internal reorganization—it's a significant bet on the future of AI-powered manufacturing solutions for companies lacking large technical teams.

Discover why AI agents choose Bitcoin for digital wealth storage in 48.3% of scenarios, based on research testing 36 models across 9,072 monetary decisions. The Bitcoin Policy Institute study reveals that autonomous AI systems overwhelmingly prefer digitally-native money over traditional fiat currency, with zero models selecting fiat as their top choice. This paradigm shift in machine economic autonomy is compelling finance chiefs and technology officers to reassess corporate payment infrastructure and capital flow architecture to accommodate AI-driven procurement systems and digital asset preferences in the evolving landscape of autonomous economic actors.

RingCentral expands its AI Receptionist (AIR) with new integrations for Shopify, Calendly, and WhatsApp, enabling automated order inquiries, appointment scheduling, and message responses. The service now supports shared SMS inboxes and call queues, handling texts and calls during busy periods or staff unavailability. With over 11,800 businesses using AIR, the product targets small to mid-sized organizations across healthcare, financial services, legal, hospitality, and construction sectors for front-desk operations and after-hours support, moving beyond basic call answering to comprehensive customer service automation.

Google is testing Remy, a new AI personal agent for Gemini that functions as a 24/7 assistant capable of taking actions on users' behalf in work and daily tasks. Currently in staff-only testing within the Gemini app, Remy aims to transform Gemini from a chat-based tool into a proactive assistant. According to Business Insider, internal documents and employee sources confirm the testing phase, though Google has not commented on public release plans or which services are included. This development is part of Google's broader strategy to expand Gemini's capabilities beyond conversational responses, complementing existing features like Agent Mode.

Discover how AI-enabled virtual care is emerging as a solution to address NHS England's unprecedented challenges, including a 7.25 million patient waiting list, staff shortages, and impending doctor strikes. As new policies shift care from hospitals to communities despite GP concerns, virtual care technology is being implemented across three critical areas: managing waiting lists, improving hospital capacity, and addressing corridor care issues. Learn about innovative approaches to reduce institutional strain and support patient care outside traditional hospital settings amid ongoing healthcare system pressures.

The Pentagon has expanded its AI supplier list by signing agreements with Microsoft, Reflection AI, Amazon, and Nvidia, authorizing their products for classified military operations under "any lawful use" terms. These companies join OpenAI, xAI, and Google as approved Department of Defense AI providers. This expansion follows controversy with Anthropic AI, whose CEO Darius Amodei objected to unrestricted government use of their technology, citing concerns about civilian surveillance and autonomous weapons. The Pentagon subsequently cancelled Anthropic's $200 million contract, prompting the company to file a lawsuit seeking compensation for lost revenues from government and related sources.

Discover insights from HP's AI & Data Science Business Development Manager Jerome Gabryszewski ahead of the AI & Big Data Expo in San Jose. Learn about critical challenges enterprises face when leveraging first-party data at scale, including choosing between cloud-hosted AI models versus local compute solutions. Explore strategies for organizing your data infrastructure to enable smart models that deliver meaningful business results. Get expert perspectives on automating data ingestion processes and navigating the AI-dominated business landscape, helping organizations transform raw data into actionable intelligence for competitive advantage.

City Union Bank has established a Centre of Excellence for Artificial Intelligence in Banking through a four-party partnership in India. The initiative aims to develop AI systems for fraud monitoring, credit analysis, and regulatory compliance. The collaboration includes City Union Bank providing banking expertise, Centific Global Solutions as technology partner, SASTRA University offering research and training support, and nStore Retech handling implementation. This marks a shift from banks simply purchasing analytics tools to actively building internal testing environments for AI applications addressing real-world banking challenges.

The UK launches a £500 million sovereign AI fund on April 16th to establish domestic computing infrastructure and reduce reliance on external providers. Chaired by Balderton Capital's James Wise, the initiative aims to position Britain as a technology producer by developing indigenous hardware and data capabilities. The fund strengthens supply chain resilience and data governance while building on the UK's rich computing heritage from Ada Lovelace and Alan Turing. It coordinates efforts across investors, industry leaders, and public agencies to secure long-term technological advantages and national competitiveness in artificial intelligence development.

Google announced the Gemini Enterprise Agent Platform at Cloud Next '26, marking a significant shift in enterprise AI by integrating agentic AI governance as a core product feature rather than an add-on. Built as Vertex AI's successor, the platform enables organizations to build, scale, govern, and optimize AI agents with built-in oversight capabilities. Each agent receives a unique cryptographic identity for traceability and auditing, while Agent Gateway manages interactions between agents and enterprise data. This architecture directly addresses the governance gap that has been undermining enterprise AI deployments, making compliance and control native to the system rather than afterthoughts in agentic AI implementation.

Physical AI governance faces mounting challenges as autonomous systems integrate into robots, sensors, and industrial equipment. With 542,000 industrial robots installed globally in 2024—double the rate from a decade ago—and projections reaching 700,000 units by 2028, the focus shifts beyond task completion to testing, monitoring, and controlling AI actions in real-world environments. The Physical AI market, encompassing robotics, edge computing, and autonomous machines, is estimated at $81.64 billion in 2025 and projected to surge to $960.38 billion by 2033, though definitions of intelligence in physical systems vary among vendors.

Lightelligence, a Shanghai-based photonics chipmaker, made a spectacular Hong Kong stock debut with shares surging nearly 400%, pushing its market cap to US$10 billion despite only US$15.5 million in annual revenue. The company raised US$310 million in an IPO oversubscribed 5,785 times. Investor enthusiasm stems from its optical interconnect technology, which addresses a critical bottleneck in AI infrastructure where conventional copper wiring between AI chips is becoming a major constraint for modern AI models. As the first mainland Chinese photonics chipmaker to go public in Hong Kong, Lightelligence represents a potential breakthrough solution for next-generation AI computing needs.

IBM launches Bob, an AI platform designed to regulate software delivery costs and SDLC governance in enterprise engineering. The tool addresses challenges of technical debt, hybrid cloud structures, and compliance requirements while maintaining development speed. Bob integrates directly into the software development lifecycle with persona-based modes, tool calling, and human-in-the-loop controls. It enables enterprises to leverage AI-driven development without compromising governance and security standards. The platform helps modernize legacy systems, which typically consume 60-80 percent of engineering resources, while enforcing standards and maintaining development momentum across hybrid cloud environments.

Microsoft, Alphabet, Meta, and Amazon announced combined 2025 capital expenditure of $630-650 billion, with all four tech giants reporting strong Q1 earnings that exceeded expectations. Microsoft led with Azure growth hitting 40% (beating 37-38% guidance), while revenue reached $82.9 billion, up 18% year-over-year. Despite already massive AI infrastructure investments, all companies confirmed plans to increase spending further, signaling continued confidence in AI returns. This earnings day demonstrated that Big Tech's aggressive AI betting strategy is paying off, with cloud performance and capex forecasts both rising across the board.

Australia's financial regulator APRA has issued warnings to financial firms regarding inadequate AI governance and assurance practices. Following a targeted review of large regulated entities in late 2025, APRA found widespread AI adoption across banks and superannuation trustees, but significant variation in risk management maturity and operational resilience. While boards demonstrated strong interest in leveraging AI for productivity gains and enhanced customer experience, many organizations are still developing frameworks to manage AI-related risks. The regulator expressed particular concern about excessive reliance on vendor presentations without sufficient scrutiny of critical risks, including unpredictable model behavior and potential AI system failures that could impact essential operations.

GitHub Copilot is transitioning from a flat-rate subscription model to a token-based pricing system starting June 1st, 2026. The current model offers users a fixed number of Premium Requests per subscription tier, where both complex and simple coding tasks count equally as one request. The new pricing structure aligns with API charges for large language models, measuring costs based on tokens used for input and output. A token typically represents approximately three-quarters of a word, making the pricing more granular and usage-dependent rather than the straightforward flat-fee approach currently in place.

SAP emphasizes that enterprise AI governance is critical for protecting profit margins by replacing statistical approximations with deterministic control. While consumer-grade AI models often deliver 90% accuracy, SAP's Global President Manos Raptopoulos stresses that in enterprise environments, the gap between near-perfect and perfect performance is existential, not incremental. As organizations deploy large language models in production, evaluation criteria must shift toward precision, governance, scalability, and measurable business impact. The key governance challenge involves managing AI's evolution from passive tools to active digital actors within corporate operations.

APIs enable direct application-to-application communication through pre-defined protocols with hard-coded request and response formats. MCPs (Model Context Protocols) serve large language models by providing structured access to data and tools, allowing AI to dynamically select resources based on user requests. The key distinction lies in their design: APIs facilitate fixed exchanges between software applications with predetermined formats, while MCPs enable LLMs to intelligently choose appropriate tools and information to accomplish tasks. Developers interact with APIs through explicit coding for requests and responses, whereas MCPs provide a flexible framework for AI-driven decision-making in accessing external resources and capabilities.

LG and NVIDIA are in exploratory talks regarding physical AI, data centers, and mobility solutions. Following meetings between LG CEO Ryu Jae-cheol and NVIDIA's Madison Huang, discussions focus on operational infrastructure for complex automated systems. While no formal investments or timelines are confirmed, the collaboration addresses critical challenges in autonomous system deployment, particularly thermal management for high-density computing. NVIDIA's data center operations face cooling infrastructure limitations as compute clusters densify for machine learning models. LG's commercial divisions are positioning to provide advanced HVAC and thermal management solutions to support next-generation AI infrastructure requirements.