AI is transforming software engineering, changing what software engineers do and the skills they need to succeed. A new survey from Uplevel, of over 100 senior engineering leaders at mid-to-large technology companies, looks at what they believe will be the most important skills for their teams.

It finds that validation of AI outputs and quality assurance (QA) is valued highest, cited by 66 percent of leaders, followed by performance monitoring and optimization (39 percent), and system architecture and integration skills (34 percent)

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Almost three-quarters of insurance underwriters say fragmented, siloed, and unstructured data -- not technology -- is the main barrier to AI transformation.

New research carried out by Reuters for technology transformation specialist CI&T shows that data fragmentation, unstructured formats, and siloed systems are the real roadblocks to delivering faster, more accurate underwriting and pricing.

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A new survey of 1,000 US HR and recruiting leaders shows teams are struggling to verify skills, assess culture fit, and find qualified candidates and that only 37 percent are prepared for an AI-driven future

The study from TestGorilla finds 58 percent struggle to verify skills on resumes, 47 percent find it difficult to identify candidates aligned with the company culture, and 43 percent cite a lack of skilled candidates in the market.

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A new report reveals that although 84 percent of IT leaders say a Configuration Management Database (CMDB) is essential to driving decision-making and operations, a majority feel their current systems lack the data quality, accuracy and completeness they need, hindering the ability to maximize enterprise AI implementations.

The study from Device42 polled IT leaders across industries including finance, healthcare, government, and technology, and finds that over 50 percent of respondents use CMDBs, monitoring tools, or manual discovery processes, to gain insights about their infrastructure, yet 58 percent report a lack of confidence in their visibility.

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The application security landscape has always been a complex one and can lead to teams spending too much time hunting down vulnerabilities. With AI becoming more popular there are even greater risks to consider.

We spoke to Yossi Pik, co-founder and CTO at Backslash Security, to discuss how AppSec needs to adapt to the greater use of AI.

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The agentic AI ecosystem, powered by large language models (LLMs), is creating a new class of cybersecurity risks according to a new report.

The study from Radware finds AI agents can act autonomously, access tools and private resources, and interoperate between one another. As enterprises turn to AI agents, there is a need to govern and secure this new emerging layer of digital infrastructure.

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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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A new report shows that 52 percent of UK SMEs are already using or plan to adopt AI tools within the next 12 months.

The study, from fintech company SumUp, is based on a survey of 750 business owners and decision makers within small UK businesses and finds that 27 percent see AI mostly as an opportunity, highlighting its potential to drive growth or increase efficiency.

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The Swiss have something of a reputation for being methodical -- particularly when it comes to things like banking -- so it’s no surprise that they take a similar approach to creating a large language model.

EPFL, ETH Zurich and the Swiss National Supercomputing Centre (CSCS) have today released Apertus, a large-scale, open, multilingual LLM. Apertus -- Latin for ‘open’ -- the name highlights its distinctive feature, that the entire development process, including its architecture, model weights, and training data and recipes, is openly accessible and fully documented.

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Artificial intelligence is making its way into more and more areas of our lives and it seems that includes our dreams.

New research from Amerisleep.com, shows that one in five Americans have dreamed about AI and 16 percent are doing so several times a month. While these dreams may reflect curiosity, some reveal anxieties about the role of technology.

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With cyber threats becoming more numerous and ever more sophisticated, it’s becoming more critical than ever for organizations to prioritize targeted threats, optimize their existing defensive capabilities and proactively reduce their exposure.

One-time security assessments are looking increasingly inadequate. We spoke to CyberProof CEO Tony Velleca to discuss how organizations can effectively implement a Continuous Threat Exposure Management (CTEM) strategy to improve their protection.

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The security operations center (SOC) has long relied on traditional SOAR platforms to manage incidents, but today’s threat landscape is moving too fast for rigid, static approaches. As attackers use AI to evolve their tactics, security teams need smarter, more adaptive systems to keep up.

We spoke to Tom Findling, co-founder and CEO of Conifers.ai, about how AI-powered SOC platforms are helping organizations scale their defenses, improve threat detection, and move from reactive alert management to proactive risk reduction.

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A survey of 800 senior developers has 75 percent of respondents saying they expect AI to significantly transform the industry within the next five years. What’s more 53 percent say they believe large language models can already code better than most humans.

The survey, from Clutch, reveals that AI has already become a daily tool for many software teams. 49 percent of senior developers and team leads say they use AI tools every day. Another 29 percent use them most days, meaning 78 percent rely on AI regularly.

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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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As students head back to university and college and engage with more digital platforms than ever, new research shows today’s tech-savvy demographic is sounding the alarm on digital identity protection as AI-generated scams surge.

The 2025 Online Identity Study from Jumio shows students globally are both early adopters of generative AI, with 70 percent using AI to create or modify images, but also the group most exposed to its risks.

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