Organisations undergoing finance transformations are discovering that traditional system cutovers rarely go as planned. Hidden manual workarounds and undocumented processes often surface late, creating operational risks and delays during ERP migrations.
Agentic AI is emerging as a solution by deploying autonomous software agents that discover real workflows directly from system data. Scout agents analyse transaction logs to uncover hidden dependencies, allowing companies to build more accurate future systems based on actual operations.
Simulator agents to stress test new systems by generating thousands of realistic transactions continuously. When problems arise, agents analyse errors and automatically recommend fixes, turning testing into a continuous improvement process rather than a one-time checkpoint.
Sentinel agents monitor financial records in real time to detect discrepancies before they escalate into compliance risks. Leaders say the approach shifts focus from single go-live milestones to ongoing resilience, with teams increasingly managing intelligent systems instead of manual processes.
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The UAE Ministry of Higher Education and Scientific Research has partnered with Microsoft to develop AI agents to help university students find jobs. The initiative was announced in Dubai during a major policy gathering in the UAE.
The collaboration in the UAE will use Microsoft Azure to build prototype AI agents supporting personalised learning and career navigation. Dubai-based officials said the tools are designed to align higher education with labour market needs in the UAE.
Four AI agents are being developed in the UAE, covering lifelong skills planning, personalised learning, course co creation and research alignment. Dubai remains central to the project as a hub for higher education innovation in the UAE.
Officials in the UAE said the partnership reflects national priorities around innovation and a knowledge based economy. Microsoft said Dubai offers an ideal environment to scale AI driven education tools across the UAE.
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Researchers at Mass General Brigham have unveiled BrainIAC, an artificial intelligence model capable of analysing brain MRI scans to predict age, dementia risk, tumour mutations, and cancer survival. The model demonstrates remarkable flexibility, handling a wide variety of medical tasks with high accuracy.
BrainIAC employs self-supervised learning to identify features from unlabeled MRI datasets, allowing it to adapt to numerous clinical applications without requiring extensive annotated data. Its performance surpasses that of conventional task-specific AI frameworks.
Tests on nearly 49,000 MRI scans across seven different tasks revealed the model’s ability to generalise across both healthy and abnormal images. It successfully tackled both straightforward tasks, such as scan classification, and complex challenges, including tumour mutation detection.
The team highlights BrainIAC’s potential to accelerate biomarker discovery, improve diagnostic tools, and personalise patient care. While results are promising, researchers note that further studies on additional imaging techniques and larger datasets are necessary to validate its broader clinical use.
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Renowned physicist John Martinis, a Nobel Prize winner, is pursuing a new quantum computing breakthrough. His early work proved electrical circuits could behave like quantum particles, enabling modern quantum machines.
Momentum grew when Martinis led Google’s ‘quantum supremacy’ experiment, outperforming classical computers in specialised tasks. Scaling remains difficult because fragile qubits, complex wiring and manufacturing limits reduce reliability.
Startup QoLab, founded in 2024, is redesigning quantum chip architecture to solve those hardware problems. Integrating components onto chips could reduce wiring, improve stability and enable larger systems.
Useful quantum computers could transform chemistry, materials science and complex simulations beyond classical limits. Martinis believes hardware innovation and scalable manufacturing will determine future industry leaders.
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Artificial intelligence is becoming a cornerstone of India’s economic and industrial growth. The upcoming AI summit highlights the goal of building AI as national infrastructure, reflecting India’s languages, values, and knowledge systems.
Indian IT and service industries are moving beyond software maintenance to providing AI infrastructure and intelligent systems. Such a transformation can automate workflows, boost productivity, and create new opportunities domestically and globally.
Industrial AI is set to transform manufacturing, enabling next-generation factories through virtual twin technologies. AI grounded in physics and industrial knowledge allows faster prototyping, efficient resource use, and greater competitiveness for large enterprises and MSMEs.
Collaborations between NVIDIA and Dassault Systèmes showcase AI-driven factories and industrial intelligence. India’s talent, scale, and digital ecosystem position it to lead in industrial and generative AI, setting global technological and economic benchmarks.
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Enterprises in France are accelerating the use of AI to manage increasingly complex multicloud environments, according to new ISG research. Companies in France are balancing innovation, compliance and rising cost pressures.
The report says multicloud adoption in France now extends beyond large corporations to midsize firms and regulated sectors. Organisations in France are spreading workloads across hyperscalers and sovereign clouds to reduce risk.
AI driven automation is becoming central to cloud governance in France as manual oversight proves unsustainable. French enterprises are using AI tools for performance optimisation, anomaly detection and real time policy enforcement.
Data sovereignty and cost control are also shaping cloud strategies in France. Companies in France are adopting FinOps practices and sovereign cloud services to meet regulatory demands and strengthen cybersecurity.
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A senior German official has voiced frustration over joint tech sovereignty efforts with France, describing the experience as disillusioning. The remarks followed a high profile digital summit hosted by Germany and France in Berlin.
The comments came from Luise Hölscher of Germany, who said approaches to buying European technology differ sharply between Germany and France. Germany tends to accept solutions from across Europe, while France often favours domestic providers.
Despite tensions, Hölscher said the disagreement has not damaged the wider partnership between Germany and France. Germany is now exploring closer cooperation with other European countries.
The debate unfolds as the EU considers new rules on cloud services and AI procurement across Germany and France. European institutions are weighing how far public bodies should prioritise European suppliers.
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Cape Town is preparing to introduce AI-assisted cameras to monitor motorists for cellphone use and seatbelt violations. Approval is awaited from the National Director of Public Prosecutions before the technology can be fully deployed.
Similar systems have been in operation in Australia for several years, where drivers face fines and demerit points for offences. Authorities report a noticeable decline in illegal phone use, showing that AI can effectively influence driver behaviour.
The cameras allow law enforcement to focus on other priorities instead of constantly monitoring mobile phone offences. Each AI-detected violation is reviewed by a human before fines are issued, adding a layer of accuracy and transparency.
Motorists retain the right to request camera images if they believe fines were unfairly applied. The Australian model demonstrates that combining technology with human oversight can improve road safety while maintaining accountability for drivers.
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Carbon Robotics has introduced a new artificial intelligence system designed to identify plant species in real time, changing how weeds are managed in agriculture. The model allows farmers to decide what should be removed directly in the field without retraining machines.
Called the Large Plant Model, the system is trained on more than 150 million plant images gathered from farms across 15 countries. The technology now powers Carbon AI, which controls the company’s autonomous LaserWeeder robots.
Earlier systems required new data labelling whenever unfamiliar weeds appeared or conditions changed. With the new model, farmers can instantly flag unwanted plants through the robot interface, even if the species has never been seen before.
Carbon Robotics says continuous data from its machines will further improve accuracy over time. Backed by more than $185 million in funding, the company aims to scale AI-driven weed control while reducing reliance on herbicides.
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Fresh investment is fuelling Polaron’s ambition to become the intelligence layer for materials science. The London startup raised $8 million to scale its AI platform and expand deployments across automotive, energy and advanced manufacturing.
Founded after seven years of research at Imperial College London, Polaron applies AI to one of manufacturing’s toughest challenges. Its models analyse microscopy images and material performance data to show how processing affects structure and behaviour.
Engineers are already using the platform to speed up analysis that once took thousands of hours. Early commercial projects, including battery electrode design, have delivered energy density gains of more than 10 per cent.
The company is now focusing on generative materials design to explore optimal configurations. The approach aims to shorten the path from laboratory research to large-scale, reliable manufacturing.
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