All news with #agentic ai tag

🔒 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.

🔌 At Google Cloud Next ’26, Google announced that more than 50 Google-managed MCP servers are generally available or in preview, enabling AI agents to connect securely to Google and Google Cloud services without local MCP deployments. The managed endpoints integrate with major agent runtimes and frameworks including Gemini CLI, LangChain, ADK, and others, supporting Resources and Prompts as protocol primitives in addition to Tools. The offering emphasizes enterprise-grade security, governance, and observability through native IAM controls, Model Armor content safety, OpenTelemetry tracing, and Cloud Audit Logs.

🚀 Amazon announced that Amazon Bedrock now provides access to the latest OpenAI models, Codex, and a Managed Agents offering in limited preview. OpenAI models and Codex integrate with Bedrock controls such as IAM, AWS PrivateLink, encryption, and CloudTrail, and usage can be applied toward existing AWS cloud commitments. Managed Agents run on Bedrock AgentCore, log actions per agent, and keep inference within the customer's AWS environment.

🚀 AWS announced the general availability of Amazon Connect Decisions, an agentic AI planning and intelligence solution that helps supply chain teams shift from firefighting to proactive operations. The service combines 30 years of Amazon operational science with 25+ specialized supply chain tools so persistent AI teammates can adapt to business rules, learn from human decisions, and continuously improve. These agents harmonize demand signals into consensus forecasts, generate constraint-aware supply plans, and run 24/7 monitoring that detects variances, performs automated root-cause analysis, and triages exceptions, surfacing only prioritized, actionable recommendations to help prevent stockouts and reduce working capital waste.

🛡️ Identity management is changing as AI agents introduce a new class of non‑human identities that can act, decide, and access resources at machine speed. Experts including Dustin Wilcox and Michael Adams recommend an identity-first security posture built on clean directories, enforced least privilege, and clear offboarding. They warn that legacy models and inventory processes won’t track proliferating tokens and agents, so organizations should catalog non‑human identities, assign ownership, and treat MFA as a baseline while moving toward phishing‑resistant methods and continuous verification.

🚀Google announced a broad expansion of AI infrastructure at Google Cloud Next, presenting the AI Hypercomputer — an integrated stack of dedicated hardware, software, and flexible consumption models. The release highlights new accelerators including TPU 8t and TPU 8i, A5X GPU instances, and Axion N4A CPUs, plus megascale Virgo networking and storage improvements. These changes target agentic workloads to improve latency, utilization, and cost-efficiency for enterprise and consumer AI.

⚙️ At Google Cloud Next '26, Google announced Fluid Compute and a broad set of compute, networking, and storage updates to support both traditional and agentic AI workloads with better performance and lower cost. Key moves include GA of the Arm-based Axion N4A, a GKE Agent Sandbox running on Axion, previews of bare-metal Axion C4A.metal and network-optimized C4N, and expanded Flexible Committed Use Discounts. The changes emphasize elastic scaling for spiky agent workloads, isolated runtime sandboxes, and higher I/O and VM-to-VM bandwidth to reduce contention and TCO.

🤖 AI agents are shifting the Tier 1 SOC analyst role from manual triage to oversight and decision-making. Instead of spending hours pivoting across logs and telemetry, analysts can delegate evidence collection to agentic AI that queries systems, correlates signals and builds evidence chains in real time. The human role becomes orchestration—reviewing outcomes, validating uncertainty and aligning actions with business risk. Trust is earned via transparency, staged deployments and practitioner-led adoption.

🔒Attackers are increasingly hijacking legitimate AI agents and compromised credentials to extract sensitive information, turning in-house assistants into active threats. These agents become 'agentic endpoints'—autonomous identities with broad privileges that often evade traditional controls by using plugins, extensions, and stolen API tokens. Organizations need a consolidated security platform, continuous verification through PAM and Zero Trust, and board-level governance to manage this accelerated, AI-driven risk.

🔗 Amazon Quick now integrates with Vee, the AI assistant from Visier, via the Model Context Protocol (MCP), enabling HR, finance, and operations leaders to access governed workforce intelligence directly inside the Quick workspace. After connecting to Visier’s remote MCP server, users can ask natural-language questions about headcount, attrition, tenure, and open requisitions and receive answers grounded in Visier’s governed data model. Vee can also be invoked from automated Quick Flows to run recurring reviews or draft documents, and Quick augments responses with enterprise knowledge from Quick Spaces—such as budgets, policies, and plans—so answers reflect the broader organizational context. The Visier integration is available in all AWS Regions where Amazon Quick is offered.

🤖 Google Cloud Next '26 in Las Vegas showcased a broad enterprise push into the agentic era, with over 32,000 attendees and 260 product, partner, and customer announcements. Highlights include the new Gemini Enterprise Agent Platform, the Gemini Enterprise app, 8th-generation TPUs, and a host of agent-focused capabilities for development, runtime, memory, observability, and governance. The week emphasized production readiness, cross-cloud data integration, and strengthened security through the Wiz acquisition and Model Armor integrations.

📊 Amazon Connect now exposes eight new metrics to evaluate AI agent outcomes, including goal success rate, faithfulness score, and tool selection accuracy. These metrics give contact center teams visibility into whether AI-driven interactions resolve customer requests and where contextual hallucinations occur. Metrics are accessible from the AI Agent Performance dashboard, the GetMetricDataV2 API, or a zero-ETL data lake for custom reporting. This capability is available in all Regions that support Amazon Connect AI Agents.

🚀 GPT-5.5 is being made generally available in Microsoft Foundry, enabling enterprises to run OpenAI's latest frontier model for production agentic workflows. The model brings deeper long-context reasoning, improved agentic execution, higher computer-use accuracy, and better token efficiency. Foundry supplies governance, identity isolation, persistent sandboxes, and integrations to evaluate and scale agents securely.

🔒 AWS has announced general availability of the AWS for SAP MCP Server on Amazon Bedrock AgentCore, enabling AI agents to connect directly and securely to SAP ERP systems at scale. Built on Model Context Protocol (MCP) and SAP OData standards, the server supports CRUD access to sales orders, purchase orders, materials, and finance documents. The managed AgentCore Runtime provides session isolation, private connectivity, and dual-layer authentication with CloudWatch telemetry and CloudFormation templates for rapid, no-infrastructure deployment.

🤖 At Google Cloud Next day 2, the developer keynote focused on the Gemini Enterprise Agent Platform, demonstrating tools to build, simulate, evaluate, and scale autonomous agents. Presentations covered the Agent Development Kit (ADK), Model Context Protocol (MCP) servers, Agent Runtime, Memory Bank, Agent Registry, A2UI/A2A standards, and debugging with Gemini Cloud Assist. Speakers also addressed security and governance with Agent Identity, Agent Gateway, and partner demos from Wiz, and released source code and codelabs to help teams adopt agentic development.

🛡️ Google unveiled a suite of agentic AI defenses at Google Cloud Next '26 to help SOC teams manage a surge of vulnerabilities tied to Anthropic Mythos. The launch includes three new agents in Google Security Operations — threat hunting, detection engineering, and third-party context — plus expanded Wiz integrations and an AI-BOM to inventory AI components. Additional controls like Agent Identity, Agent Gateway, and Model Armor aim to govern the emerging 'agentic web' and mitigate prompt injection, data leakage, and shadow AI risks.

🔐 Google announced a shift to agent-centric security at Google Cloud Next '26, positioning AI agents to help SOC teams respond to the potential surge of vulnerabilities tied to Anthropic's Mythos. It introduced three new agents in Google Security Operations — a threat hunting agent, a detection engineering agent and a third-party context agent — and said its existing triage agent has processed over five million alerts, reducing analysis from about 30 minutes to roughly a minute with Gemini. Additional moves include expanded Wiz integrations, an AI-BOM to inventory AI components, agentic automation features, Model Armor protections, Agent Identity and Agent Gateway controls, and modern IAM simplifications to streamline permissions.

🛡️ Google has launched the Gemini Enterprise Agent Platform, a hub for managing agentic AI that assigns each agent a unique cryptographic ID to enable traceable, auditable actions and map to authorization policies. The platform centralizes agents, tools and skills in an Agent Registry and offers an Agent Gateway to enforce agent-to-agent and agent-to-tool policies, apply Model Armor protections, and support MCP and A2A protocols. New detection and security features include real-time Agent Anomaly Detection, an Agent Security dashboard integrated with Security Command Center, and specialized security agents for threat hunting, detection engineering and third-party context enrichment.