Future of work

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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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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Sony targets AI music copyright use

Sony Group has developed technology designed to identify the original sources of music generated by AI. The move comes amid growing concern over the unauthorised use of copyrighted works in AI training.

According to Sony Group, the system can extract data from an underlying AI model and compare generated tracks with original compositions. The process aims to quantify how much specific works contributed to the output.

Composers, songwriters and publishers could use the technology to seek compensation from AI developers if their material was used without permission. Sony said the goal is to help ensure creators are properly rewarded.

Efforts to safeguard intellectual property have intensified across the music industry. Sony Music Entertainment in the US previously filed a copyright infringement lawsuit in 2024 over AI-generated music, underscoring wider tensions around AI and creative rights.

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Enterprises rethink cloud amid digital sovereignty push

Digital sovereignty has moved to the boardroom as geopolitical tensions rise and cloud adoption accelerates. Organisations are reassessing infrastructure to protect autonomy, ensure compliance, and manage jurisdictional risk. Cloud strategy is increasingly shaped by data location, control, and resilience.

Regulations such as NIS2, DORA, and national data laws have intensified scrutiny of cross-border dependencies. Sovereignty concerns now extend beyond governments to sectors such as healthcare and finance. Vendor selection increasingly prioritises sovereign regions and stricter data controls.

Hybrid cloud remains dominant. Organisations place sensitive workloads on private platforms to strengthen oversight while retaining public cloud innovation. Large-scale repatriation is rare due to cost and complexity, though compliance pressures are driving broader multicloud diversification.

Government investment and oversight are reinforcing the shift. Sovereignty is becoming part of national resilience policy, prompting stricter audits and governance expectations. Enterprises face growing pressure to demonstrate control over critical systems, supply chains, and data flows.

A pragmatic approach, often described as minimum viable sovereignty, helps reduce exposure without unnecessary complexity. Organisations can identify critical workloads, secure enforceable vendor commitments, and plan for disruption. Early adaptation supports resilience and long-term flexibility.

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Commission delays high risk AI guidance

The European Commission has confirmed it will again delay publishing guidance on high-risk AI systems under the EU AI Act. The guidelines were due by 2 February 2026, but will now follow a revised timeline.

According to Euractiv, the document is intended to clarify which AI systems fall into the high-risk category and therefore face stricter obligations. Officials said more time is needed to incorporate significant stakeholder feedback.

The delay marks the second missed deadline and adds to broader implementation setbacks surrounding the EU AI Act. Several member states have yet to designate national enforcement bodies, complicating oversight preparations.

Brussels is also considering postponing the application of high-risk rules through a digital simplification package. Parliament and Council appear supportive of moving the August deadline back by more than a year, easing pressure on companies awaiting guidance.

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IQM puts Finland on Europe’s quantum computing map

Finland is emerging as a key hub in Europe’s quantum computing landscape as startup IQM prepares to become one of the continent’s first publicly listed quantum firms.

The company is developing full-stack, open-architecture quantum systems designed for on-premise deployment or cloud access. It aims to advance the practical use of quantum computing across research and industry.

Founded in 2018, IQM has already delivered 21 quantum systems to 13 customers, highlighting growing European interest in commercial quantum technologies.

Analysts note that while challenges remain, meaningful breakthroughs are now occurring, signalling that quantum computing is shifting from purely experimental science to an operational industry.

IQM’s technology could support advancements in medicine, science, and computational research, enabling the solution to complex problems far beyond the reach of classical computers.

The firm exemplifies Europe’s ambition to build quantum capabilities independently of larger players in the US and China, positioning Finland as a strategic hub for next-generation computing.

The company’s work aligns with broader European efforts to foster innovation in quantum technologies.

By combining domestic expertise with open-access systems, IQM demonstrates how Finland is contributing to the continent’s emerging quantum ecosystem, bridging academic research and industrial application.

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AI-driven physics speeds up industrial innovation

PhysicsX, a London-based startup founded by former F1 engineers and AI experts, is redefining engineering with its AI-driven physics platform.

Design and testing cycles are reduced from weeks or months to seconds. Engineers can now iterate rapidly and optimise systems across multiple industries, including aerospace, automotive, semiconductors, energy, and materials.

The technology enables teams to evaluate thousands of design variations simultaneously. Semiconductor firms speed up prototype development, electronics improve thermal performance, and mining boosts copper recovery for renewable energy and AI data centres.

PhysicsX achieves this using Large Physics Models and Large Geometry Models that base design evaluation on real-world physics rather than assumptions.

Predictive reasoning lets engineers simulate multiple parameter changes before acting. The approach shifts control from reactive adjustments to proactive optimisation, helping teams make faster, better-informed decisions.

PhysicsX also bridges disciplinary divides, enabling aerodynamics, structural, and thermal considerations to be optimised together rather than in isolation.

By combining speed, system-level insight, and predictive control, PhysicsX is shrinking the gap between cutting-edge research and practical industrial impact. The platform uses physics-based AI to improve efficiency, drive innovation, and support sustainable growth.

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AI drives faster modernisation of legacy COBOL systems

Critical to finance, airlines, and government, COBOL handles about 95% of US ATM transactions. Despite its ubiquity, the pool of developers able to read and maintain COBOL is shrinking as seasoned engineers retire and universities offer limited instruction.

Institutional knowledge is now embedded in decades-old code, and documentation often lags.

Modernising COBOL differs from typical software updates. It requires untangling intricate dependencies and reverse-engineering business logic that has evolved over decades.

Traditional modernisation efforts involved large teams of consultants over the years, resulting in high costs and lengthy timelines. AI tools are changing that paradigm by automating the most labour-intensive tasks.

AI-driven solutions like Claude Code map code dependencies, trace execution paths, document workflows, and identify risks. They provide teams with actionable insights for prioritisation, risk management, and refactoring, dramatically shortening modernisation timelines from years to months.

Human experts remain essential to reviewing AI recommendations, ensuring regulatory compliance, and making strategic decisions about which components to modernise first.

Implementation follows an incremental approach. AI translates COBOL logic into modern languages, creates integration scaffolding, and supports side-by-side operation with legacy components.

Continuous validation at each step reduces risk, allowing teams to build confidence as complex parts of the system are modernised. AI automation combined with expert oversight makes large-scale COBOL modernisation feasible.

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AI data centre surge pushes electricity demand in the UK to new heights

The UK faces rising pressure on its electricity system as about 140 new data centre projects could demand more power than the country’s current peak consumption, according to Ofgem.

The regulator said developers are seeking about 50 gigawatts of capacity, a level driven by rapid growth in AI and far beyond earlier forecasts.

Connection requests have surged since late 2024, placing strain on a grid already struggling to support vital renewable projects that are key to national climate targets.

Work needed to connect expanding data centre capacity could delay schemes considered essential for decarbonisation and economic growth, instead of supporting the transition at the required pace.

The growing electricity footprint of AI infrastructure also threatens the aim of creating a virtually carbon-free power system by 2030, particularly as high costs and slow grid integration continue to hinder progress.

A proposed data centre in Lincolnshire has already raised concerns by projecting emissions greater than those of several international airports combined.

Ofgem now warns that speculative grid applications are blocking more viable projects, including those tied to government AI growth zones.

The regulator is considering more stringent financial requirements and new fees for access to grid connections, arguing that developers may need to build their own routes to the network rather than rely entirely on existing infrastructure.

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AWS warns of AI powered cybercrime

Amazon Web Services has revealed that a Russian-speaking threat actor used commercial AI tools to compromise more than 600 FortiGate firewalls across 55 countries. AWS described the campaign as an AI-powered assembly line for cybercrime.

According to AWS, the attacker relied on exposed management ports and weak single-factor credentials rather than exploiting software vulnerabilities. The campaign targeted FortiGate devices globally and focused on harvesting credentials and configuration data.

AWS said the potentially Russian group appeared unsophisticated but achieved scale through AI-assisted mass scanning and automation. When encountering stronger defences, the attackers reportedly shifted to easier targets rather than persist.

The company advised organisations using FortiGate appliances to secure management interfaces, change default credentials and enforce complex passwords. Amazon said it was not compromised during the campaign.

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