All news with #agentic ai tag

🤖 At Google Cloud Next '26, Google introduced the Gemini Enterprise Agent Platform to help teams build, deploy, scale, govern, and optimize autonomous AI agents in production. The series highlights long-running state management in Agent Runtime, a layered Agent Governance Stack, orchestration patterns in the Agent Development Kit (ADK), integration standards, and prebuilt blueprints in Agent Garden.

🤖 Join hands-on developer workshops across North America that teach secure, scalable deployment of agentic AI for enterprises. These sessions are practical, bring-your-laptop labs where Platform, Security, and Data practitioners build end-to-end solutions, including GKE cluster hardening, secure sandboxing, and governed data pipelines. Tracks cover GKE + Data and Data Engineering & Analytics, with guidance from Google experts. Attendees leave with runnable labs and operational best practices to accelerate production adoption.

🤖 Gemma 4, released by Google DeepMind, is a new family of open models optimized for local and mobile deployment. The family emphasizes intelligence per parameter, offering ultra-mobile E2B/E4B sizes, a 31B dense model for local GPUs, and a 26B Mixture-of-Experts variant. The shift to an Apache 2 license plus tools like the Agent Development Kit enables offline agentic workflows and commercial use by developers and startups.

🚀 At Google Cloud Next '26, Firestore introduced expanded agentic AI integrations, built-in full-text search, and deeper MongoDB compatibility aimed at accelerating agent-driven applications. The Enterprise edition’s reimagined query engine adds hundreds of expressive query features, JOINs via subqueries, and pipeline operations. Native connections to AI Studio and third-party coding agents plus preview tools like natural language console querying and Usage Insights simplify building agentic workflows. These capabilities are available now in Firestore Enterprise in both Native and MongoDB compatibility modes.

🤖 Amazon SageMaker AI introduces an agentic experience that dramatically shortens model customization from months to days or hours. Using SageMaker AI model customization agent skills, developers interact via natural language coding agents to prepare data, fine-tune models, evaluate quality with LLM-as-a-judge metrics, and generate reusable code artifacts. Skills can be installed into IDEs via the sagemaker-ai agent plugin or used pre-installed in SageMaker Studio Notebooks, and support deployment to Amazon Bedrock or SageMaker AI endpoints.

🔒 A joint advisory from CISA and international partners urges organizations to treat agentic AI cautiously, enforcing strong authentication, Secure by Design principles, and staged rollouts. The guidance stresses least privilege, inventories of agent capabilities, and protections against prompt injection and data exposure. It also recommends continuous monitoring with human-in-the-loop controls, DevSecOps practices, and regular incident-response testing to reduce privilege creep, tool misuse, and other emergent risks.

🔒 Microsoft announces Agent 365 is generally available, offering a unified control plane to observe, govern, and secure AI agents across endpoints, cloud, and SaaS. The release adds discovery of local and cloud agents (including OpenClaw, GitHub Copilot CLI, and Claude Code) and integrates with Intune and Defender for inventory, policy controls, runtime blocking, and alerting. Agent 365 also introduces Windows 365 for Agents, partner integrations, and licensing via Microsoft 365 E7 or standalone at USD 15 per user per month.

🛡️ CISA, in collaboration with the Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC) and other partners, released guidance to help organizations adopt agentic AI systems safely. The guide identifies key security challenges and risks and offers actionable steps for designing, deploying, and operating these systems. It emphasizes risk management, alignment with existing cybersecurity frameworks, and strengthened oversight to help security teams, developers, and decision-makers implement practical governance and controls.

🔒 CISA, the Australian Signals Directorate’s Australian Cyber Security Centre (ASD ACSC), and U.S. and international partners published Careful Adoption of Agentic Artificial Intelligence Services, a joint guide describing cybersecurity challenges and mitigations for agentic AI. The document warns that agentic AI can expand attack surface, cause privilege creep, produce behavioral misalignment, and obscure event records while offering automation benefits to critical infrastructure and defense sectors. It targets developers, vendors, and operators with actionable recommendations — including avoiding broad or unrestricted access to sensitive data and systems, beginning with low‑risk, non‑sensitive use cases, and explicitly accounting for agentic AI in organizational security models and risk posture.

🔒 Microsoft previewed new Microsoft Defender capabilities within the Agent 365 tooling gateway to give security teams near real-time visibility and control over agentic workflows, using webhook-based evaluation to detect, block, and investigate anomalous agent actions before execution. Separately, Microsoft Defender for Cloud now integrates with GitHub Advanced Security generally available to map code changes to production, prioritize alerts using runtime context, and enable coordinated remediation. A hands-on Microsoft Purview demo demonstrates AI-powered data security investigations across the data estate.

🔒 At Next '26 Francis deSouza framed Google Cloud's direction as preparing enterprises for an agentic future, positioning the platform as AI‑native, open, and secure. He argued that multicloud and multi‑AI are essential for resilience and highlighted AI-driven SOC automation outcomes including a 90% reduction in mitigation time and Triage and Investigation tasks collapsed from 30 minutes to 60 seconds using Gemini. The integration of Wiz was presented as a way to secure self‑hosted and multicloud AI lifecycles, while a new whitepaper and the Gemini Enterprise Agent Platform outline governance, prompt sanitization, and agent identity controls.

🔧 AWS announced Neuron Agentic Development, an open-source set of agents and skills that bring agentic coding capabilities to development on AWS Trainium and AWS Inferentia. The initial release focuses on Neuron Kernel Interface (NKI) kernel development, enabling an agentic IDE to author, debug, profile, and analyze custom kernels. Developers can request kernels from natural-language descriptions, get automated fixes for compilation errors, and receive performance reports identifying bottleneck lines of code.

🤖 Agents can now provision Cloudflare resources and complete billing through Stripe Projects, enabling end-to-end deployment without manual dashboard steps. Using a co-designed protocol, an agent can discover available services, create or link a Cloudflare account, and receive API credentials to deploy code and register domains. Stripe supplies a payment token (not raw card data) with a default $100/month cap, and human approval can be requested when needed. Any platform with signed-in users can adopt the same orchestration flow.

🧩 Amazon Quick has introduced preview Microsoft 365 extensions for Excel, PowerPoint, and Word that let the service perform tasks directly inside users’ Microsoft 365 environments. The Excel extension supports complex spreadsheet analysis including pivot tables, charts, and data import/cleaning. PowerPoint enables template-driven deck creation and refinement from Quick data, while Word gains formatted document generation, sweeping edits with track changes, and reviewer participation in comments. The extensions are available in multiple AWS regions for early access.

⚖️ Re-permissioning aligns AI agents' access with clear operational needs so they execute tasks safely rather than accumulate unnecessary powers that enable unauthorized actions. As agents evolve from responders into execution engines, interoperability standards like MCP and agent-to-agent flows expand reach but also multiply where things can go wrong. Organizations should enforce continuous permission audits, mandatory human-in-the-loop checks for sensitive operations, strict least-privilege context sharing, and vet integrations, libraries and third parties while running tabletop prompt-injection exercises to validate controls and prevent data exposure or integrity-impacting changes.

🔒 Palo Alto Networks announced its intent to acquire Portkey and integrate Portkey’s AI Gateway into Prisma AIRS to provide a centralized control plane for agentic AI. The combined platform will offer a unified API to thousands of LLMs, an agent registry, semantic routing, caching and runtime protections such as Agent Artifact scanning and automated red teaming. Integration with CyberArk is intended to enforce agent identity and least‑privilege controls. The goal is to enable enterprises to move autonomous workloads from development to production with consistent governance and minimal performance tradeoffs.

🚀 Google Cloud Next ’26 introduced an integrated AI stack for startups centered on Gemini Enterprise, an end‑to‑end agent lifecycle platform with an Agent Development Kit, Agent Studio, and production runtimes that support sub‑second starts and persistent memory. The Agentic Data Cloud and zero‑ETL features enable cross‑cloud data access and high‑accuracy text‑to‑SQL to avoid costly migrations. Infrastructure updates (TPU 8t/8i, Axion N4A, new networking machines, and GKE sandboxes) plus agentic security integrations and a $750M partner fund aim to accelerate prototyping, secure production deployments, and enterprise go‑to‑market.

🔒 In February 2026 researchers flagged a major shift: threat actors now deploy custom AI agents that automate attacks through the kill chain, from Active Directory mapping to rapid Domain Admin takeover. Join a technical webinar with Picus Security leaders Kevin Cole and Gursel Arici for a deep dive into Autonomous Exposure Validation. Learn how to safely ingest threat intelligence, simulate attacks, and close the gap between CTI, Red, and Blue teams to speed detection and remediation.

🛡️ Generative AI enables defenders to deploy large numbers of convincing, adaptive honeypots — from Linux shells to IoT devices — using simple text prompts. These AI-driven decoys are particularly effective against automated attackers that favor speed over stealth, allowing analysts to observe tactics and tooling in real time within a controlled environment. By exploiting the lack of awareness in AI agents, organizations can shift from passive detection to active manipulation, turning attacker automation into a defensive liability. Prototype implementations show how a listener, simulated vulnerability, and an AI responder combine to emulate targeted systems at scale.

🤖 At Google Cloud Next, public sector leaders showcased how they are using AI agents to boost productivity and mission impact across government and research organizations. Google introduced the Gemini Enterprise Agent Platform—an evolution of Vertex AI—plus the Gemini Enterprise App with Gemini 3.1 Pro and an Agent Designer for inspectable, schedule‑based workflows. The announcement also covered AI infrastructure (TPU 8 series), an Agentic Data Cloud, enhanced security and Agentic Defense, partner initiatives, and upskilling through the GEAR program.