Artificial intelligence

AI sparks worry over job loss and skill decline

A 2025 survey by Statistics Netherlands (CBS) shows that 41% of employees think AI could perform part of their job, while 4% fear full replacement. Higher-educated workers and young adults are most likely to believe their tasks could be automated.

Among those using AI at work, 56% expect it could partly or fully do their jobs, compared with 37% of non-users. Almost half of the workers who see AI as a potential replacement expressed concern, with women slightly more worried than men.

Most adults anticipate that AI will lead to job losses (75%), a decline in workforce skills (64%), and less interesting work (48%). Despite these concerns, 57% believe AI could boost productivity by speeding up tasks.

Fewer respondents think AI will solve labour shortages (46%) or replace unsafe jobs (41%). The findings highlight both the opportunities and anxieties surrounding AI adoption in the workplace.

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New AI tool predicts post-mortem time with precision

Researchers at Linköping University and the Swedish National Board of Forensic Medicine have developed an AI tool that estimates time of death from blood metabolites. The model, trained on thousands of samples, provides greater accuracy than traditional forensic methods.

Methods like body temperature, rigor mortis, or eye potassium become unreliable after a few days. AI analysis of blood metabolites estimates time of death with about one-day accuracy for up to 13 days post-mortem.

The project uses a unique data resource of over 45,000 autopsies, with 4,876 samples used to train the AI. Researchers say the method works globally, even in labs with smaller datasets, making it useful for forensic investigations.

Next steps aim to increase precision, allowing models to estimate not only the day but also the specific time of death. Experts say the tool can improve investigations by guiding law enforcement and aiding complex cases.

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OURA launches AI model tailored to women’s physiology with privacy-first design

Guidance for women’s health is entering a new phase as ŌURA introduces a proprietary large language model designed specifically for reproductive and hormonal wellbeing.

The model sits within Oura Advisor and is available for testing through Oura Labs, drawing on clinical standards, peer-reviewed evidence and biometric signals collected through the Oura Ring to create personalised and context-aware responses.

The system interprets questions through women’s physiology instead of depending on general-purpose models that miss critical hormonal and life-stage variables.

It supports the full spectrum of reproductive health, from the earliest menstrual patterns to menopause, and is intentionally tuned to be non-dismissive and emotionally supportive.

By combining longitudinal sleep, activity, stress, cycle and pregnancy data with clinician-reviewed research, the model aims to strengthen understanding and preparation ahead of medical appointments.

Privacy forms the centre of the architecture, with all processing hosted on infrastructure controlled entirely by the company. Conversations are neither shared nor sold, reflecting ŌURA’s broader push for private AI.

Oura Labs operates as an opt-in experimental environment where new features are tested in collaboration with members who can leave at any time.

Women who take part influence the model’s evolution by contributing feedback that informs future development.

These interactions help refine personalised insights across fertility, cycle irregularities, pregnancy changes and other hormonal shifts, marking a significant step in how the Finland-founded company advances preventive, data-guided care for its global community.

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NVIDIA healthcare survey shows surge in AI adoption and strong ROI

AI is reshaping healthcare as organisations shift from trial projects to large-scale deployment.

The latest industry survey from NVIDIA shows widespread adoption across digital healthcare, biotechnology, pharmaceuticals and medical technology, signalling a sector that is now executing rather than experimenting.

Uptake is expanding rapidly, with generative AI and large language models becoming central tools for clinical and operational tasks.

The report highlights how medical imaging, drug discovery and clinical decision support are among the most prominent applications. Radiologists are using AI to accelerate image analysis, while research teams apply advanced models to speed early-stage drug development.

Organisations benefit from workflow optimisation instead of relying on manual administrative routines, with many citing improvements in patient coordination, documentation and coding.

Open-source models are increasingly important, with most respondents considering them vital for domain-specific development.

Experts argue that open-source innovation will guide exploration, whereas deployment in clinical environments will demand rigorous validation and accountability rather than unrestricted experimentation.

Agentic AI is emerging as a new capability for knowledge retrieval and literature analysis.

Evidence of return on investment is clear, prompting 85% of organisations to expand their AI budgets. Many report higher revenue, reduced costs and significant gains in back-office productivity.

Evaluation is becoming a core operational requirement, ensuring AI continues to improve safety, quality and overall clinical performance over time.

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New Relic advances AI agents for enterprise observability

The expansion into enterprise AI comes with a no-code platform from New Relic that allows companies to build and supervise their own observability agents.

A system that assembles AI-driven monitors designed to detect bugs and performance problems before they affect users, instead of leaving teams to rely on manual tracking.

It also supports the Model Context Protocol so organisations can link external data sources to the agents and integrate them with existing New Relic tools.

The company stresses that the platform is intended to complement other agent systems rather than replace them.

As AI agent software spreads across the market, enterprises are searching for ways to manage risk when giving automated tools access to internal systems.

Industry players such as Salesforce and OpenAI have already introduced their own agent platforms, and assessments from Gartner describe these frameworks as essential infrastructure for wider AI adoption.

New Relic also introduced new tools for the OpenTelemetry framework to remove friction around observability standards.

Its application performance monitoring agents now support OTel data, allowing enterprises to manage these streams in one place instead of operating separate collectors.

The update aims to reduce fragmentation that has slowed OTel deployment across large organisations and to simplify how engineering teams handle diverse observability pipelines.

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CrowdStrike warns of faster AI driven threats

Cyber adversaries increasingly used AI to accelerate attacks and evade detection in 2025, according to CrowdStrike’s 2026 Global Threat Report. The company described the period as the year of the evasive adversary, marked by subtle and rapid intrusions.

The average time to a financially motivated online crime breakout fell to 29 minutes, with the fastest recorded at 27 seconds. CrowdStrike observed an 89 percent rise in attacks by AI-enabled threat actors compared with 2024.

Attackers also targeted AI systems themselves, exploiting GenAI tools at more than 90 organisations through malicious prompt injection. Supply chain compromises and the abuse of valid credentials enabled intrusions to blend into legitimate activity, with most detections classified as malware-free.

China linked activity rose by 38 percent across sectors, while North Korea linked incidents increased by 130 percent. CrowdStrike tracked more than 281 adversaries in total, warning that speed, credential abuse, and AI fluency now define the modern threat landscape.

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UK Justice Secretary pushes expanded AI use in courts to tackle backlogs

In a speech at the Microsoft AI Tour in London, Lammy outlined a vision for using AI to help address persistent backlogs in the criminal justice system, which currently stands at tens of thousands of unresolved cases, by automating and streamlining court administration and case progression tasks.

He described how pilot tools have already been used in the probation system to transcribe meetings and save over 25,000 hours of administrative time. He said similar AI transcription and summarisation systems are being tested in courts and tribunals to help judges, magistrates and legal advisers handle paperwork more efficiently.

Lammy also announced plans to invest more in an in-house Justice AI unit, with additional funding, to support pilot AI tools such as an intelligent listing assistant (J-AI) to help schedule and prioritise cases, and to strengthen partnerships with technology firms alongside funding programmes like LawtechUK to support law-tech innovation.

The Ministry of Justice will expand the use of AI tools to assist transcription, case summary generation and legal analysis, aiming to free up human judges and staff to focus on substantive decision-making.

The reforms come amid broader judicial changes, including lifting caps on court sitting days and proposals to reduce the number of jury trials for less serious offences, to alleviate bottlenecks that could otherwise take years to clear.

However, legal industry groups such as The Law Society of England and Wales have expressed reservations, saying AI may help with administrative tasks. Still, they should not replace critical human judgement in decisions with serious consequences.

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AI preparing kids for careers that don’t exist yet, say education leaders

Education leaders and industry stakeholders in South Africa say the rise of AI is transforming labour-market expectations to the point that tomorrow’s careers may not yet exist.

They argue that traditional curricula, centred on static knowledge and routine tasks, must evolve to prioritise adaptability, problem solving, creativity, ethical reasoning and digital fluency, competencies that complement AI rather than compete with it.

Speakers at recent education forums emphasised that AI will continue to automate routine cognitive and technical work, pushing demand toward roles that require higher-order thinking and human-centred skills.

They described a growing need to integrate AI literacy and data skills into schooling from an early age to reduce future workforce displacement and prepare students to harness AI as a productive partner.

Experts also highlighted equity concerns: without intentional policy and investment to support under-resourced schools and communities, the ‘AI skills gap’ could exacerbate inequality. Some educators recommended stronger partnerships between government, tech industry and educational institutions to co-develop curricula, teacher training and accessible AI tools.

They underscored that competencies such as empathetic communication, cultural awareness and ethical judgement, areas where AI lacks robust capabilities, will remain crucial.

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AI-powered electronic nose shows promise for early ovarian cancer screening

Researchers at Linköping University have developed an AI-powered electronic nose capable of detecting early signs of ovarian cancer in blood plasma samples. The pilot study, published in Advanced Intelligent Systems, reports 97 per cent accuracy using machine-learning models trained on biobank data.

Ovarian cancer is often diagnosed late because symptoms resemble those of more common conditions. In 2022, around 325,000 new cases and more than 200,000 deaths were recorded globally. Earlier detection could significantly improve survival rates and access to timely treatment.

The prototype device contains 32 commercially available sensors that detect volatile substances emitted by blood samples. Rather than targeting a single biomarker, the system analyses complex chemical patterns, with machine learning identifying signatures linked to ovarian cancer.

Unlike conventional blood tests, which can be slow and rely on specific biomarkers, the electronic nose evaluates a broad spectrum of compounds. Researchers say the approach offers greater precision and could reduce screening costs while improving accessibility.

Developers estimate the test takes around 10 minutes and could become part of cancer screening programmes within three years. Although currently focused on ovarian cancer, the team suggests the method could eventually be adapted to detect multiple cancer types.

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US tech giants eye Wales for major AI investment

American technology firms are increasingly looking to Wales as a destination for AI investment and data infrastructure. Strong inward investment figures and expanding growth zones are putting the nation firmly on the technology map.

Last year Wales secured £4.6bn in global investment across 65 foreign direct investment projects, marking a 23 per cent rise year on year. Thousands of jobs were created or safeguarded, outperforming many other UK regions.

Major projects underline the shift. US firm Vantage plans to transform the former Ford Bridgend plant into a large-scale data centre campus, while Microsoft is supporting another proposed scheme in Newport, both located within designated AI growth zones.

Beyond data centres, Wales offers land, connectivity and a supportive regulatory environment. Innovation clusters across Cardiff, Newport and North Wales, alongside strengths in life sciences, advanced manufacturing and renewable energy, are strengthening its appeal to global investors.

With expanding energy projects and a growing start-up pipeline, Wales is positioning itself as a competitive base for global business. Investors are increasingly encouraged to see it not as a regional outpost, but as an international platform rooted in strong economic foundations.

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