Articles about agentic AI

Data insights platform WisdomAI is launching a new Proactive Agents feature that aims to supplement data analysis teams with the ability to proactively learn, monitor metrics, detect anomalies, prepare analysis, and execute decisions, allowing humans to focus on strategy and judgment.

“Data analysts have long been the gatekeepers to insights -- but they’re hard to scale, and no company can hire unlimited analysts,” says Soham Mazumdar, CEO and co-founder of WisdomAI. “Proactive Agents change that. They act as AI teammates that scale your data team’s capacity, increase productivity across the organization, and democratize access to analyst-grade work. Every employee can now benefit from the kind of monitoring and analysis that used to require dedicated headcount.”

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IT leaders are optimistic about the value AI can deliver, but readiness is low. Many organizations still lack the security, governance and alignment needed to deploy AI responsibly.

A new study by the Ponemon Institute for OpenText finds 57 percent of CIOs, CISOs, and other IT leaders rate AI adoption as a top priority, and 54 percent are confident they can demonstrate ROI from AI initiatives. However, 53 percent say it is ‘very difficult’ or ‘extremely difficult’ to reduce AI security and legal risks.

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New AI agents launched today by Druva, the company says, will fundamentally change the way customers secure, recover, and manage their data.

A major expansion to DruAI, the company’s suite of AI capabilities for customers, features intelligent agents that can interpret user intent, analyze data, and take meaningful action. This shift aims to move enterprises beyond traditional, query-based AI to agentic systems designed for action -- helping teams strengthen cyber resilience with greater speed, simplicity, and confidence.

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A new report reveals an increasing trust gap between businesses deploying agentic AI for external communications and consumers wary of sharing personal information due to security concerns.

The research, carried out by Censuswide for Salt Security, also warns that without proper API discovery, governance and security, the very technology meant to drive smarter customer engagement could open the door to cybersecurity issues including attacks or data leakage.

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The rise of generative and agentic AI is transforming how data is accessed and used, not just by humans but by non-human AI agents acting on their behalf. This shift is driving an unprecedented surge in data access demands, creating a governance challenge at a scale that traditional methods can’t handle.

If organizations can’t match the surge in access requests, innovation will stall, compliance risks will spike, and organizations will reach a breaking point. Joe Regensburger, VP of research at Immuta, argues that the solution isn’t more powerful AI models; it’s better governance. We talked to him to learn more.

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Security teams are often hampered by having to identify and fix issues while weeding out false positives. This is an area where AI can help and Sysdig has launched a new agentic platform designed to analyze cloud environments end-to-end and uncover hidden business risk so organizations can remediate crucial threats fast and deliver measurable improvements in their security posture.

Sysdig Sage, the company’s AI cloud security analyst, ultimately understands context from the entire business and provides clear, contextual remediation recommendations, reducing an organization’s exposure time to critical vulnerabilities.

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Cybersecurity exposure management company Intruder has introduced GregAI, an AI-powered security analyst that, unlike generic AI assistants, has full visibility into each user’s security environment.

Currently in beta, GregAI is available to free trial users and customers on Intruder’s Cloud, Pro, and Enterprise plans. The assistant is named after Intruder’s original mascot, following a design file mix-up involving a designer named Greg.

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According to Gartner 33 percent of enterprise applications are expected to incorporate agentic AI by 2028, but are their security teams equipped with the latest training and technology to protect this new attack surface?

We spoke with Ante Gojsalić, CTO and co-founder at SplxAI to uncover the hidden dangers in agentic AI systems and what enterprises can do to stay ahead of the malicious looking to exploit them.

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As data demands across organizations intensify they need to scale productivity and enable business users to explore data independently.

Cube is launching an agentic AI analytics platform built on a universal semantic layer which allows it to operate autonomously within enterprise frameworks, automating work while preserving trust, governance, and transparency.

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The use of AI in software development can save valuable time completing routine tasks. But what if it could autonomously respond to events, implement changes, and submit code through standard pull requests?

This is what Zencoder is doing with the launch today of Autonomous Zen Agents for CI/CD, bringing groundbreaking AI automation directly into the software development infrastructure.

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Nearly 80 percent of IT professionals responding to a new survey rank governance as 'extremely important,' underscoring the fact that while organizations are eager to innovate, they still want to do so responsibly

The study by API management firm Gravitee looks at the use of Agentic AI systems and Large Language Models (LLMs) by large and midsize companies and finds 72 percent of respondents report that their organizations are actively using agentic AI systems today.

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A new report from API and AI security solutions company Wallarm finds that of around 4,700 security issues analyzed in Agentic AI projects, 49 percent were API-related, underscoring the inseparable nature of agent and API security.

The report also finds that over 1,000 issues in Agentic AI repositories remain unaddressed. 22 percent of reported security issues remain open too, with some lingering for 1,200-plus days, highlighting a critical gap between vulnerability discovery and remediation.

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The latest buzzy concept in the world of AI is now transcending its initial hype. Advances in Agentic AI are accelerating the development of autonomous business systems, building upon progress in machine learning. Acting as an independent ‘agent’, the technology can make informed decisions based on the multimodal data and algorithms they’re built on and then ‘learn’ from its experiences.

But even more excitingly, Agentic AI aims to execute tasks independently. It’s this ability to adapt, plan, and execute complex tasks without direct human intervention is what differentiates Agentic AI from its predecessors.

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Current AI models can perform many tasks such as generating text, but these are 'prompted' -- that is the AI isn't acting by itself. But this is about to change with the arrival of agentic AI.

Gartner estimates that by 2028, 33 percent of enterprise software applications will include agentic AI, up from less than one percent in 2024, enabling 15 percent of day-to-day work decisions to be made autonomously.

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Agentic AI has been in the news quite a bit of late, but how should enterprises expect it to impact their organizations?

We spoke to Mike Finley, CTO of AnswerRocket, to discuss Agentic AI's benefits, use cases and more.

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