Articles about Artificial Intelligence (AI)

The latest Enterprise Cloud Index (ECI) survey from Nutanix shows that that while 80 percent of organizations have already implemented a GenAI strategy, implementation targets vary significantly.

Organizations are eager to leverage GenAI for productivity, automation, and innovation, but they also face critical hurdles in the form of data security, compliance, and IT infrastructure modernization. 95 percent of respondents agree that GenAI is changing their organization’s priorities

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The latest Phishing Trends Report from Hoxhunt -- based on a global sample size of 2.5 million email users, 50 million phishing simulations, and millions of real phishing attacks -- shows a 49 percent increase in phishing since 2021, driven partly by the rise of blackhat AI.

Among the findings are that between 0.7 percent and 4.7 percent of reported phishing attempts are written by AI. This may seem low but to put it into context numbers of AI phishing attempts were negligible six months earlier. Highly targeted, AI-enabled spear phishing attacks with multiple links in the kill chain are on the rise.

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According to a new report, 60 percent of respondents claim that their organization is failing to keep pace with data changes resulting from AI demands.

In addition, the study from Immuta shows that traditional data architecture challenges persist, with nearly half of organizations identifying compliance and privacy as primary data concerns, and 64 percent citing significant challenges in providing timely and secure access to data for authorized users.

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It's an increasingly rare system these days that doesn't claim to have incorporated artificial intelligence in some form or another.

But when implementing AI it's important to look beyond the hype and ensure that it can deliver real value for the business. We spoke to Ajay Kumar, CEO of SLK Software, about the need for a holistic approach to allow enterprises to leverage AI for solving complex business challenges.

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Non-human identities (NHIs) outnumber human identities by between 10 and 50 times, but the industry lacks solutions to properly address this hole in the security perimeter.

Traditional IAM solutions and best practices aren't sufficient when it comes to managing NHIs, as evidenced by some recent breaches that have stemmed from exploitation of NHIs.

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Half of businesses have reported a growth in deepfake and AI-generated fraud, alongside rising biometric spoofs and counterfeit ID fraud attempts, according to the 2025 State of Identity Fraud Report, released today by AuthenticID.

The report analyzes internal proprietary data anonymized from AuthenticID's identity verification and fraud detection technology. When paired with insights from annual fraud surveys of both fraud and technology professionals as well as consumers in North America, the report offers a comprehensive view of the fraud landscape.

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It's not exactly Big Brother, but a new analysis of Chrome extensions from Incogni reveals that 67 percent collect user data, and 41 percent collect personally identifiable information (PII), including sensitive details like credit card numbers, passwords, and location data.

Extensions like Grammarly, which make writing almost anything effortless, or Vetted, which act as online shopping assistants, are quickly becoming essentials of everyday life. But because many users trust Google's ecosystem, they also assume that third-party extensions vetted through the Chrome Web Store are equally safe.

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A new report reveals that APIs have emerged as the predominant attack surface over the past year, with AI being the biggest driver of API security risks.

The survey from Wallarm, of 200 US-based enterprise leaders on AI and API security, finds over 53 percent report engaging in multiple AI deployments. These deployments are primarily enabled by API technology, cementing APIs as the foundation of enterprise AI adoption. However, while AI integration drives rapid API adoption across industries, it also introduces unique risks.

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While 51 percent of organizations rely on their security teams to manage AI risks, 33 percent say that they either lack a dedicated role or are unsure who holds responsibility for AI risk management.

A new report from Wing Security and the Cloud Security Alliance also highlights that only 44 percent of organizations prioritize protecting all their sanctioned applications, while a mere 17 percent include unsanctioned ones as a priority.

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Today has seen millions of dollars wiped off US market tech stocks by the launch of DeepSeek, the latest Chinese AI that threatens US dominance in the sector.

This is partly because DeepSeek can run on much less powerful hardware than rivals such as OpenAI's o1. DeepSeek also says that its v3 model, released in December, cost less than $6 million to train, less than a tenth of what Meta spent on its most recent system.

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Repetitive UI development tasks often don't involve coding and in order to free up developer time from these, Qt Group is launching Qt AI Assistant, an experimental tool for streamlining cross-platform user interface (UI) development.

It gives advice on building application UIs with Qt Framework and automates manual tasks like writing unit test cases, code documentation, and repetitive code. Users request this advice with a prompt window and quick-access commands inside the code editor of Qt Creator (used for creating and modifying cross-platform apps).

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A new report shows 82 percent of organizations fear 'digital chaos' due to increasingly complex, interconnected, and automated processes. According to the report, a lack of control has increased compliance risks for 82 percent of organizations, while 77 percent report higher risks of core business processes failing.

The study from Camunda highlights that organizations now manage an average of 50 endpoints to execute tasks that are part of a process in their business. This is an increase of 19 percent over the past five years, and is contributing to growing business risk.

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Lots of organizations are rushing to embrace AI and hoping to deliver business value. But AI is only as good as the data that underpins it.

We spoke to Julian LaNeve, chief technology officer of Astronomer, to discuss why it's important to fix the foundations before implementing AI solutions.

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Large language models (LLMs) have undergone rapid evolution in recent years, but can often be viewed as something of a 'black-box' as a lack of transparency makes it difficult to identify how decisions are made, trace errors, or understand biases within the model.

We spoke to Pramod Beligere, vice president -- generative AI practice head at Hexaware, to discuss this along with the tools that are being developed, such as explainable AI and interpretable models, to make AI systems more understandable, trustworthy and accountable.

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According to new research only 13 percent of businesses are monitoring their AI’s energy consumption despite escalating power demands.

The study from SambaNova Systems gathered responses from 2,012 business leaders (1,004 in Europe and 1,008 in the US) finds that 49.8 percent are concerned about the energy and efficiency challenges posed by AI.

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