Future of work

India expands job access with AI-powered worker platforms

India is reshaping support for its vast informal workforce through e-Shram, a national database built to connect millions of people to social security and better job prospects.

The database works together with the National Career Service portal, and both systems run on Microsoft Azure.

AI tools are now improving access to stable employment by offering skills analysis, resume generation and personalised career pathways.

The original aim of e-Shram was to create a reliable record of informal workers after the pandemic exposed major gaps in welfare coverage. Engineers had to build a platform capable of registering hundreds of millions of people while safeguarding sensitive data.

Azure’s scalable infrastructure allowed the system to process high transaction volumes and maintain strong security protocols. Support reached remote areas through a network of service centres, helped further by Bhashini, an AI language service offering real-time translation in 22 Indian languages.

More than 310 million workers are now registered and linked to programmes providing accident insurance, medical subsidies and housing assistance. The integration with NCS has opened paths to regulated work, often with health insurance or retirement savings.

Workers receive guidance on improving employability, while new features such as AI chatbots and location-focused job searches aim to help those in smaller cities gain equal access to opportunities.

India is using the combined platforms to plan future labour policies, manage skill development and support international mobility for trained workers.

Officials also hope the digital systems will reduce reliance on job brokers and strengthen safe recruitment, including abroad through links with the eMigrate portal.

The government has already presented the platforms to international partners and is preparing to offer them as digital public infrastructure for other countries seeking similar reforms.

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AI teachers and deepfakes tested to ease UK teacher shortages

Amid a worsening recruitment and retention crisis in UK education, some schools are trialling AI-based teaching solutions, including remote teachers delivered via video links and even proposals for deepfake avatars to give lessons.

These pilots are part of efforts to maintain educational provision where qualified staff are scarce, with proponents arguing that technology can help reduce teacher workload and address gaps in core subjects, such as mathematics.

However, many teachers and unions remain sceptical or critical. Some educators argue that remote or AI-led instruction cannot replace the human presence, interpersonal support and contextual knowledge provided by in-room teachers.

Union activity and petitions opposing virtual teaching arrangements reflect broader concerns about the implications for job security, education quality and the potential de-professionalisation of teaching.

The BBC’s reporting highlighted specific examples, such as a Lancashire secondary school bringing in a remote maths teacher based hundreds of miles away, a move that sparked debate among local teachers who emphasise the irreplaceable role of in-person interaction in effective teaching.

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DeVry improves student support with AI

In the US, DeVry University has upgraded its student support system by deploying Salesforce Agentforce 360, aiming to offer faster and more personalised assistance to its 32,000 learners.

The new AI agents provide round-the-clock support for DeVryPro, the university’s online learning programme, ensuring students receive timely guidance.

The platform also simplifies course enrolment through a self-service website, allowing learners to manage enrolment and payments efficiently. Real-time guidance replaces the previous chatbot, helping students access course information and support outside regular hours.

With Data 360 integrating information from multiple systems, DeVry can deliver personalised recommendations while automating time-consuming tasks such as weekly onboarding.

Advisors can now focus on building stronger connections with students and supporting the development of workforce skills.

University leaders emphasise that these advancements reflect a commitment to preparing learners for an AI-driven workforce, combining innovative technology with personalised academic experiences. The initiative positions DeVry as a leader in integrating AI into higher education.

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Seven teams advance in XPRIZE contest backed by Google

XPRIZE has named seven finalist teams in its three-year, $5 million Quantum Applications competition, a global challenge backed by Google Quantum AI, Google.org, and GESDA to accelerate real-world quantum computing use cases.

Selected from 133 submissions, the finalists are developing quantum algorithms that could outperform classical systems on practical tasks linked to sustainability, science, and industry. They will share a $1 million prize at this stage, ahead of a $4 million award pool in 2027.

Google says the competition supports its goal of finding concrete problems where quantum systems can beat leading classical methods. The finalists span materials science, chemistry, optimisation, and biomedical modelling, showing growing momentum behind application-driven research.

The teams include Calbee Quantum, Gibbs Samplers, Phasecraft’s materials group, QuMIT, Xanadu, Q4Proteins, and QuantumForGraphproblem, each proposing algorithms with potential impact ranging from clean-energy materials and advanced semiconductors to drug discovery and molecular analysis.

Finalists now proceed to Phase II, which focuses on benchmarking against classical tools, assessing feasibility, and demonstrating pathways to real-world advantage. A wildcard round in 2026 will offer re-entry for other teams.

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AI model predicts prediabetes with high accuracy

Researchers have developed an AI model that enhances prediabetes prediction by integrating oxidative stress markers with traditional clinical indicators. The Pattern Neural Network model achieved 98.3% accuracy in Indian adults, outperforming other machine learning methods.

Total antioxidant status emerged as a key predictor, with lower antioxidant capacity observed in individuals with prediabetes. Waist circumference and BMI were also highly informative, alongside glucose markers such as HbA1c and OGTT.

The inclusion of oxidative stress measures provides a deeper understanding of the mechanisms underlying metabolic risk.

The study used clinical and biochemical data from 199 adults, with the PNN trained on 14 features, including demographic and biochemical variables. High accuracy across all sets indicates strong potential for quick, low-cost screening and personalised early interventions.

While the results are promising, the single-centre design and limited sample size indicate that external validation is needed. Future studies should test the model in larger, multi-site cohorts and integrate longitudinal data to enhance its real-world applicability and public health impact.

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EU proposes easing environmental rules for datacentres and housing

The European Commission has proposed a significant overhaul of environmental rules, potentially exempting datacentres, AI facilities, and affordable housing from mandatory impact assessments.

Member states would retain discretion over whether such projects require full environmental scrutiny, as part of a broader plan to expedite permitting and reduce reporting obligations for businesses.

The package also repeals a hazardous chemical database, eases polluter obligations, and moves environmental management rules from individual plants to whole companies. The commission states that the changes could save firms €1 billion annually, but green groups warn of potential costs to health and biodiversity.

The proposals align with plans to modernise the EU electricity grid and new climate targets to reduce emissions by 90% compared to 1990. Experts have cautioned that loopholes allowing international carbon credits could weaken domestic emissions reductions.

Corporate sustainability laws are also being scaled back. The revised rules limit the number of companies covered, postpone compliance deadlines to 2029, and remove obligations to implement climate transition plans.

Business lobby groups have welcomed the changes as a more realistic approach to corporate social responsibility and due diligence.

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UK partners with DeepMind to boost AI innovation

The UK Department for Science, Innovation and Technology (DSIT) has entered a strategic partnership with Google DeepMind to advance AI across public services, research, and security.

The non-legally binding memorandum of understanding outlines a shared commitment to responsible AI development, while enhancing national readiness for transformative technologies.

The collaboration will explore AI solutions for public services, including education, government departments, and the Incubator for AI (i.AI). Google DeepMind may provide engineering support and develop AI tools, including a government-focused version of Gemini aligned with the national curriculum.

Researchers will gain priority access to DeepMind’s AI models, including AlphaEvolve, AlphaGenome, and WeatherNext, with joint initiatives supporting automated R&D and lab facilities in the UK. The partnership seeks to accelerate innovation in strategically important areas such as fusion energy.

AI security will be strengthened through the UK AI Security Institute, which will share model insights, address emerging risks, and enhance national cyber preparedness. The MoU is voluntary, spans 36 months, and ensures compliance with data privacy laws, including UK GDPR.

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Vietnam passes first AI law to strict safeguards

Vietnam’s National Assembly has passed its first AI Law, advancing the regulation and development of AI nationwide. The legislation was approved with overwhelming support, alongside amendments to the Intellectual Property Law and a revised High Technology Law.

The AI Law will take effect on March 1, 2026.

The law establishes core principles, prohibits certain acts, and outlines a risk management framework for AI systems. The law combines safeguards for high-risk AI with incentives for innovation, including sandbox testing, a National AI Development Fund, and startup vouchers.

AI oversight will be centralised under the Government, led by the Ministry of Science and Technology, with assessments needed only for high-risk systems approved by the Prime Minister. The law allows real-time updates to this list to keep pace with technological advances.

Flexible provisions prevent obsolescence by avoiding fixed technology lists or rigid risk classifications. Lawmakers emphasised the balance between regulation and innovation, aiming to create a safe yet supportive environment for AI growth in Vietnam.

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EU advances ambitious gigafactory programme for AI leadership

The Council has agreed on a significant amendment to the EuroHPC Joint Undertaking regulation, aiming to establish AI gigafactories across Europe alongside a new quantum pillar.

The plan advances earlier efforts to build AI factories and redirects unused EU funds toward larger and more ambitious facilities. Up to five gigafactories are expected, supported through public and private partnerships that promise a stronger technological base for European research and industry.

AI gigafactories will combine high-performance computing, energy-efficient data centres and automated systems to give Europe world-class AI capacity. The regulation sets out firm rules for funding and procurement while protecting start-ups and scale-ups.

It also allows gigafactories to be spread across multiple countries, creating a flexible model that can strengthen European resilience, competitiveness and security instead of relying heavily on American or Chinese infrastructure.

An agreement that updates the governance of EuroHPC and introduces safeguards for participation from partners outside the EU. Quantum research and innovation activities will move from Horizon Europe to EuroHPC in order to consolidate work on critical technologies.

In a shift that aims to widen the impact of supercomputing and quantum infrastructure while supporting the development of essential skills for science and industry.

The next stage involves the European Parliament delivering its opinion on 17 December.

A final Council adoption will follow once legal and linguistic checks have been completed, marking a decisive step towards Europe’s new AI and quantum capability.

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AI agents redefine knowledge work through cognitive collaboration

A new study by Perplexity and Harvard researchers sheds light on how people use AI agents at scale.

Millions of anonymised interactions were analysed to understand who relies on agent technology, how intensively it is used and what tasks users delegate. The findings challenge the notion of a digital concierge model and reveal a shift toward more profound cognitive collaboration, rather than merely outsourcing tasks.

More than half of all activity involves cognitive work, with strong emphasis on productivity, learning and research. Users depend on agents to scan documents, summarise complex material and prepare early analysis before making final decisions.

Students use AI agents to navigate coursework, while professionals rely on them to process information or filter financial data. The pattern suggests that users adopt agents to elevate their own capability instead of avoiding effort.

Usage also evolves. Early queries often involve low-pressure tasks, yet long-term behaviour moves sharply toward productivity and sustained research. Retention rates are highest among users working on structured workflows or tasks that require knowledge.

The trajectory mirrors the early personal computer, which gained value through spreadsheets and text processing rather than recreational use.

Six main occupations now drive most agent activity, with firm reliance among digital specialists as well as marketing, management and entrepreneurial roles. Context shapes behaviour, as finance users concentrate on efficiency while students favour research.

Designers and hospitality staff follow patterns linked to their professional needs. The study argues that knowledge work is increasingly shaped by the ability to ask better questions and that hybrid intelligence will define future productivity.

The pace of adaptation across the broader economy remains an open question.

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