Articles about Enterprise

Vibe coding has surged in popularity in the last year. Tools like Lovable, Replit, and v0 are giving anyone the ability to generate apps without writing a single line of code. The experience is fast, intuitive, and surprisingly powerful, fueling a wave of innovation across both consumer and enterprise settings.

But as companies rush to adopt these tools, a new challenge has emerged. Employees are beginning to build their own AI-powered applications using whatever platforms they can find, often connecting them to live business data. It is a trend some experts are calling the rise of “shadow AI,” where software is created outside of established security and governance frameworks.

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Agentic AI is rapidly moving from concept to reality, prompting organizations globally to rethink how they integrate these technologies into their business operations. The use of AI agents in daily workflows is set to rise dramatically in the coming years, raising questions over what organizations need to do to manage them effectively, and what might happen if they fail to do so.

We spoke with Ann Maya, EMEA CTO at Boomi, about the evolution of AI agents, the steps businesses should be taking ahead of deployment, and why the principles of human workforce management may hold the key to responsible use.

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Although 74 percent of IT leaders expect budgets to rise in 2026 more than half say they still lack the internal resources to fix issues quickly or drive innovation.

A new report from DataStrike also finds 60 percent of organizations now rely on MSPs to manage data infrastructure, more than double the rate reported last year. This highlights a growing dependence on external expertise as teams tackle modernization and technical debt.

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In October, one in every 44 GenAI prompts submitted from enterprise networks posed a high risk of data leakage, impacting 87 percent of organizations that use GenAI regularly.

A study from Check Point Research finds an additional 19 percent of prompts contained potentially sensitive information such as internal communications, customer data, or proprietary code. These risks coincide with an eight percent increase in average daily GenAI usage among corporate users.

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Businesses are keen to deploy AI but doing so across hybrid and regulated environments, and managing the resulting workloads, remains deeply complex.

This is why Gcore is launching Everywhere AI, a deployment platform that allows enterprises to deploy, scale, and optimize AI workloads flexibly across on-premises, hybrid, and cloud environments while maximizing performance, efficiency, and revenue.

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There’s been a boom in AI in recent years and the technology has found its way into more and more areas of commercial enterprise.

But in the rush to adopt AI is the quality of the underlying data being ignored? We spoke to Krishna Subramanian, co-founder and COO of Komprise to find out why good data governance is key to implementing AI successfully.

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It’s known as an ‘ohno-second’ that moment in time when you realize you’ve clicked send on something you shouldn’t have. But it’s no laughing matter, a new survey of more than 300 security and IT professionals from Abnormal AI highlights the growing threat and business impact of legitimate email messages sent to the wrong recipient.

These misdirected emails can result in data breaches, regulatory violations, remediation costs, and reputational damage. The research shows 98 percent percent of security leaders consider misdirected email as a significant risk when compared to other data loss risks like malware and insider threats.

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New research finds that business trust in autonomous AI is growing, with 57 percent of organizations saying they’re ‘very confident’ in the technology’s reliability in core business processes.

Yet, despite this increasing trust, implementation is lagging. The survey from Insight Enterprises shows that six in 10 organizations are stuck in pilot or experimental phases. Most are deploying AI in low-risk, narrowly defined areas, with only 24 percent using it in production for clearly scoped use cases.

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SUSE has released SUSE Linux Enterprise 16, which it describes as the first enterprise Linux distribution to integrate agentic AI through the Model Context Protocol (MCP). The update aims to let operating systems interact more directly with AI models and external data sources.

The Model Context Protocol, introduced in 2024 by Anthropic, is an open standard for connecting large language models to tools and data. It defines a simple client-server structure that allows AI systems to request information or perform tasks across different applications in a consistent way. SUSE’s adoption of MCP is meant to make those capabilities available at the operating system level, without depending on a single AI provider.

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With hyperscalers better able to attract the best talent and headcount tight across the board, most enterprises are leaning heavily on generalist IT teams to manage their environments.

But in many cases the tools they’re expected to use were designed for specialists. Legacy tools like ConnectWise, Device42, or ServiceNow often require deep expertise, complex integrations, or expensive customization making them unsuitable for generalist teams.

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Security leaders estimate that, on average, cyber incidents cost their organization $3.7 million, with 46 percent suffering from an outage or disruption to their services as a consequence of attacks.

A new survey from Red Canary of 550 security leaders, from the US, UK, New Zealand, Australia, and the Nordic countries, finds that SOC teams continue to struggle with the challenges of securing cloud environments, identities, and AI technologies amid evolving threats.

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Across large organizations, developers and DevOps teams rely on an ever-growing collection of specialized tools. But while these offer valuable flexibility, they can also create significant pain points.

We spoke to Chintana Wilamuna, VP of solutions architecture at WSO2, about how the landscape is changing from fragmented, purpose-built development tools toward comprehensive, unified platforms.

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The latest AI Readiness Index from Cisco is based on a study of over 8,000 AI leaders across 30 markets and 26 industries. It finds that what it calls ‘Pacesetters,’ about 13 percent of organizations for the last three years, outperform their peers across every measure of AI value.

Of these Pacesetters 98 percent are designing their networks for the growth, scale and complexity of AI compared to 46 percent overall.

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Cybercrime has become a global epidemic, with costs soaring across sectors and borders. But who’s paying the price and how has that changed since the turn of the century?

Researchers from vpnMentor have analyzed 25 years of FBI Internet Crime Complaint Center (IC3) data along with a review of major global incidents to discover the cost of cybercrime and how it’s evolving.

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A report released today finds that approximately 60 percent of businesses are using three
or more secure sockets layer (SSL) providers and suggests a lack of centralized processes for SSL certificate management.

The study from domain security company CSC analyzed usage trends and patterns for more than 802,000 digital certificates linked to 2.4 million domains. It finds domain validated (DV) certificates account for three-quarters (73.4 percent) of certificates while organization validation (OV) certificates represent nearly a quarter (24.6 percent). Extended validation (EV) certificates account for less than two percent (1.9 percent).

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