All news with #agentic ai tag

CIO’s First Principles: A Reference Guide to Securing AI

🔐 Enterprises must redesign security as AI moves from experimentation to production, and CIOs need a prevention-first, unified approach. This guide reframes Confidentiality, Integrity and Availability for AI, stressing rigorous access controls, end-to-end data lineage, adversarial testing and a defensible supply chain to prevent poisoning, prompt injection and model hijacking. Palo Alto Networks advocates embedding security across MLOps, real-time visibility of models and agents, and executive accountability to eliminate shadow AI and ensure resilient, auditable AI deployments.

IDC: Major Shift in Cloud Security Investment Trends

🔍 IDC’s latest research finds organizations averaged nine cloud security incidents in 2024, with 89% reporting year-over-year increases. The study identifies CNAPP as a top-three investment for 2025, rising CISO ownership of cloud security, and persistent tool sprawl that increases cost and risk. It also documents practical uses of generative AI for detection and response and a move toward integrated, autonomous SecOps platforms. Microsoft positions its integrated CNAPP and AI-driven threat intelligence as a way to unify protection across the application lifecycle.

AWS launches regional service discovery in Builder Center

🔍 AWS announced AWS Capabilities by Region in Builder Center, a web-based tool to discover and compare service availability, features, APIs, and CloudFormation resources across AWS Regions. The interactive interface lets users explore Regions, run side-by-side comparisons, and view forward-looking roadmap details to support global deployment planning. AWS also enhanced the Knowledge MCP Server to expose regional capability data in an LLM-compatible format, enabling MCP clients and agentic frameworks to obtain real-time availability insights and suggested alternatives when features are unavailable.

Google Cloud Announces Ironwood TPUs and Axion VMs

🚀 Google Cloud announced general availability of Ironwood, its seventh-generation TPU, alongside a new family of Arm-based Axion VMs. Ironwood is optimized for large-scale training, reinforcement learning, and high-volume, low-latency inference, with claims of 10x peak performance over TPU v5p and multi-fold efficiency gains versus TPU v6e (Trillium). The architecture supports superpods up to 9,216 chips, 9.6 Tb/s inter‑chip interconnect, up to 1.77 PB shared HBM, and Optical Circuit Switching for dynamic fabric routing. Complementary software and orchestration updates — including Cluster Director, MaxText improvements, vLLM support, and GKE Inference Gateway — aim to reduce time-to-first-token and serving costs, while Axion N4A/C4A instances provide ARM-based CPU options for cost-sensitive inference and data-prep workloads.

Equipping Autonomous AI Agents with Cyber Hygiene Practices

🔐 This post demonstrates a proof-of-concept for teaching autonomous agents internet safety by integrating real-time threat intelligence. Using LangChain with OpenAI and the Cisco Umbrella API, the example shows how an agent can extract domains and query dispositions to decide whether to connect. The agent returns clear disposition reports and abstains when no domains are present. The approach emphasizes decision-making over hardblocking.

Forrester's 2026 Predictions: CIOs and CISOs on Alert

🔍 Forrester warns that 2026 will demand precision, resilience and strategic foresight from CIOs and CISOs as volatility persists and the AI hype phase gives way to a results-driven era. Leaders will face rising pressure to deliver measurable, secure outcomes from AI initiatives while managing vendor promises, postponements and tighter financial scrutiny. Neocloud growth, talent bottlenecks and accelerating quantum risk will further complicate planning and force cross-functional governance.

Azure AI Foundry and UiPath: Agentic Automation in Care

🏥 Microsoft and UiPath describe how integrated agents from Azure AI Foundry and UiPath, orchestrated by UiPath Maestro, can operationalize AI within clinical workflows to surface and act on incidental radiology findings. The workflow uses UiPath medical record summarization agents to flag findings, Azure AI Foundry imaging agents to analyze PACS images and prior results, and UiPath agents to aggregate and forward consolidated follow-up reports to ordering clinicians. Microsoft says this agentic approach accelerates decision-making, reduces physician workload, and improves outcomes while maintaining compliance with DICOMweb and FHIR standards.

Vertex AI Agent Builder: Build, Scale, Govern Agents

🚀 Vertex AI Agent Builder is Google Cloud's integrated platform to build, scale, and govern production AI agents. The update expands the Agent Development Kit (ADK) and Agent Engine with configurable context layers to reduce token usage, an adaptable plugins framework, and new language SDK support including Go. Production features include observability, evaluation tools, simplified deployment via the ADK CLI, and strengthened governance with native agent identities and Model Armor protections.

Building Collaborative AI with ADK: A Developer’s Guide

🧭 This guide summarizes Multi-Agent System (MAS) fundamentals and explains how Google’s Agent Development Kit (ADK) helps developers assemble cooperating agents to solve complex tasks. It outlines three agent roles — LLM Agents for reasoning, Workflow Agents for orchestration, and Custom Agents for bespoke logic — and describes hierarchical organization and orchestration patterns (sequential, parallel, loop). The post also reviews communication options (shared state, LLM delegation, explicit invocation) and points developers to samples and codelabs for rapid prototyping.

10 Promising Cybersecurity Startups CISOs Should Know

🔒 This roundup profiles ten cybersecurity startups founded in 2020 or later that CISOs should watch, chosen for funding, leadership, customer traction, and strategic clarity. It highlights diverse categories including non-human identity, software supply chain, data security posture, and AI agent security. Notable vendors such as Astrix, Chainguard, Cyera, and Drata have raised substantial capital and achieved rapid enterprise adoption. The list underscores investor enthusiasm and the rise of runtime‑focused and agentic defenses.

Falcon for XIoT Enhances OT Visibility and Speed at Scale

🔍 Falcon for XIoT introduces zero-touch asset discovery, native segmentation visibility, and a unified OT/XIoT view to reduce blind spots across industrial networks. The solution leverages DHCP data and the existing Falcon sensor to build continuous, agentless inventories and to monitor inter-device traffic without manual scan configuration. These enhancements aim to accelerate detection, simplify operations, and provide richer context for faster security decisions across IT, OT, and XIoT environments.

CrowdStrike Advances Security Automation with Charlotte

🚀 CrowdStrike introduces Charlotte Agentic SOAR, an orchestration layer that integrates Falcon Fusion SOAR, Falcon Next‑Gen SIEM, Charlotte AI and AgentWorks to enable intelligent, no‑code agents. The offering includes an Agentic Security Workforce of purpose-built AI agents, an Agent Builder for plain-language agent creation, a visual workflow orchestrator with hundreds of connectors, and unified case management. Together these elements let analysts set guardrails while agents reason, decide, and act at machine speed to accelerate detection and response and reduce repetitive analyst tasks.

CrowdStrike Expands Agentic Security Workforce With Agents

🤖 CrowdStrike announced new specialized agents and an orchestration layer designed to accelerate SOC operations and automation. The launch includes a Data Onboarding Agent, a Foundry App Creation Agent, and an updated Exposure Prioritization Agent to simplify pipeline creation, app development, and continuous authenticated scanning. Integrated with Charlotte Agentic SOAR and Charlotte AI, these agents enable coordinated, machine-speed workflows while keeping analysts in control.

Cybersecurity Forecast 2026: AI, Cybercrime, Nation-State

🔒 The Cybersecurity Forecast 2026 synthesizes frontline telemetry and expert analysis from Google Cloud security teams to outline the most significant threats and defensive shifts for the coming year. The report emphasizes how adversaries will broadly adopt AI to scale attacks, with specific risks including prompt injection and AI-enabled social engineering. It also highlights persistent cybercrime trends—ransomware, extortion, and on-chain resiliency—and evolving nation‑state campaigns. Organizations are urged to adapt IAM, secure AI agents, and harden virtualization controls to stay ahead.

CISO Predictions 2026: Resilience, AI, and Threats

🔐 Fortinet’s CISO Collective outlines priorities and risks CISOs will face in 2026. The briefing warns that AI will accelerate innovation while expanding attack surfaces, increasing LLM breaches, adversarial model attacks, and deepfake-enabled BEC. It highlights geopolitical and space-related threats such as GPS jamming and satellite interception, persistent regulatory pressure including NIS2 and DORA, and a chronic cybersecurity skills gap. Recommendations emphasize governed AI, identity hardening, quantum readiness, and resilience-driven leadership.

Building an AI Champions Network for Enterprise Adoption

🤝 Getting an enterprise-grade generative AI platform in place is a milestone, not the finish line. Sustained, distributed adoption comes from embedding AI into everyday processes through an organized AI champions network that brings enablement close to the work. Champions act as multipliers — translating strategy into team behaviors, surfacing blockers and use cases, and accelerating normalized use. With structured onboarding, rotating membership, monthly working sessions, and direct ties to the core AI program, the network converts tool access into measurable business impact.

BigQuery's Data Engineering Agent: Automating Pipelines

🔧 The preview of the Data Engineering Agent in BigQuery introduces a Gemini-powered assistant that automates pipeline development, maintenance, and migrations. The agent converts natural-language requirements into SQL, enforces engineering best practices, and supports custom instructions and UDFs to reflect organizational logic. Integrated with Dataplex, it uses governance metadata to improve table descriptions, data quality assertions, and PII-aware handling, and it also generates documentation and troubleshooting guidance. The feature is available in preview via BigQuery Pipelines and the Dataform UI.

OpenAI Aardvark: Autonomous GPT-5 Agent for Code Security

🛡️ OpenAI Aardvark is an autonomous GPT-5-based agent that scans, analyzes and patches code by emulating a human security researcher. Rather than only flagging suspicious patterns, it maps repositories, builds contextual threat models, validates findings in sandboxes and proposes fixes via Codex, then rechecks changes to prevent regressions. OpenAI reports it found 92% of benchmark vulnerabilities and has already identified real issues in open-source projects, offering free coordinated scanning for selected non-commercial repositories.

OpenAI Unveils Aardvark: GPT-5 Agent for Code Security

🔍 OpenAI has introduced Aardvark, an agentic security researcher powered by GPT-5 that autonomously scans source code repositories to identify vulnerabilities, assess exploitability, and propose targeted patches that can be reviewed by humans. Embedded in development pipelines, the agent monitors commits and incoming changes continuously, prioritizes threats by severity and likely impact, and attempts controlled exploit verification in sandboxed environments. Using OpenAI Codex for patch generation, Aardvark is in private beta and has already contributed to the discovery of multiple CVEs in open-source projects.

GKE and Gemini CLI Integration Enhances Developer Workflows

🚀 Google has open-sourced the GKE Gemini CLI extension, bringing Google Kubernetes Engine directly into the Gemini CLI ecosystem while also functioning as an MCP server for other MCP clients. The extension injects GKE-specific context, tools, and tailored prompts so developers can use shorter, more natural language interactions and integrated slash commands to complete complex workflows. It simplifies common operations—like selecting models and accelerators or generating Kubernetes manifests for inference—while improving compatibility with Cloud Observability. The project is actively maintained with regular releases and community contributions.