AI is becoming central to industrial networking strategies, but it is also creating new security challenges, according to Cisco’s 2026 State of Industrial AI Report.
Based on a survey of 1,000 professionals across 19 countries and 21 sectors, the report shows organisations view cybersecurity as both a barrier and an opportunity for AI adoption. About 40% cited cybersecurity concerns as a major obstacle, while 48% named security their biggest networking challenge.
At the same time, many organisations believe AI will strengthen their cyber resilience. Cisco noted that ‘while security gaps are limiting AI scale today, organisations view AI as a tool to strengthen detection, monitoring and resilience’.
The report also highlights organisational challenges, particularly collaboration between IT and operational technology teams. Only 20% of organisations report fully collaborative IT and OT cybersecurity operations, despite the growing importance of coordination for AI deployment.
Cisco said industrial AI adoption is accelerating, with 61% of organisations already deploying AI in industrial environments. However, only one in five reports mature, scaled adoption, suggesting many deployments remain in early stages.
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A new study from the Bitcoin Policy Institute, testing 36 AI models across more than 9,000 responses, found that AI agents overwhelmingly prefer Bitcoin over other forms of money.
Bitcoin was the most frequently selected monetary instrument overall, chosen in 48.3% of all responses, whilst almost 91% of responses favoured some form of digital currency over traditional fiat, with no model ranking fiat as its top overall preference.
The preference for Bitcoin was especially pronounced in long-term savings scenarios, where 79.1% of AI responses chose it as the best way to preserve purchasing power over multi-year horizons. For payments and cross-border transfers, however, stablecoins edged ahead, selected in 53.2% of responses compared to Bitcoin’s 36%.
The Bitcoin Policy Institute acknowledged that the study’s methodology had limitations, noting that scenario framing may have influenced results and that the models’ preferences reflect patterns in training data rather than real-world adoption.
Anthropic models showed the strongest Bitcoin preference at 68%, compared to 43% for Google, 39% for xAI, and 26% for OpenAI.
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Junyang Lin, a central technical leader of Alibaba’s Qwen AI project, has stepped down just one day after the company unveiled its Qwen 3.5 small models. Lin, who joined Alibaba in 2019 and joined the Qwen team in 2023, did not provide details about his decision.
His departure comes at a sensitive moment, as Qwen has emerged as one of China’s most prominent open-weight AI initiatives. The project is a core element of Alibaba’s strategy to compete with leading US developers such as OpenAI, Google, and Anthropic amid intensifying global AI competition.
Alibaba’s newly launched Qwen 3.5 Small Model series comprises four multimodal models with 0.8B to 9B parameters. The systems are designed for on-device deployment and lightweight AI agents, reflecting a focus on efficient and adaptable AI applications.
The release attracted attention from figures including Elon Musk, who commented on the models’ performance. Internally and across the AI ecosystem, including partners linked to Hugging Face, Lin’s exit was described as a significant loss, particularly given his role in advancing open-source development and strengthening global developer engagement.
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OneTrust has entered a new leadership phase in the US after appointing John Heyman as chief executive, replacing founder Kabir Barday. Barday will remain on the board in an advisory role as the US-based compliance technology firm continues to push into AI governance.
John Heyman said organisations across the US and globally are rapidly integrating AI into daily operations. Companies deploying large numbers of AI agents increasingly need tools to manage risk, data use and regulatory compliance.
OneTrust believes demand for governance technology will grow as AI systems multiply inside businesses in the US and worldwide. John Heyman described a future where automated monitoring tools oversee AI agents operating within company systems.
Leadership at OneTrust in the US aims to build systems that track how AI agents collect and share data while maintaining enterprise control. Growing adoption of AI in the US and globally continues to drive demand for responsible governance platforms.
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Spanish banking giant Banco Santander and Mastercard have completed what they describe as Europe’s first live end-to-end payment executed by an AI agent. The pilot combined Santander’s live payments infrastructure with Mastercard Agent Pay to enable autonomous, permission-based transactions.
Mastercard Agent Pay, launched in April 2025, allows AI agents to initiate and complete payments within predefined consumer limits. The transaction was orchestrated with support from PayOS and integrates Microsoft Azure OpenAI Service and Copilot Studio.
Following the pilot, Santander plans to expand testing and explore new partnerships across agentic commerce use cases. The bank, which manages around €1.84 trillion in assets, is positioning AI as a core driver of innovation.
AI initiatives at Santander are led by chief data and AI officer Ricardo Martín Manjón, hired from BBVA. A strategic partnership with OpenAI has also connected up to 30,000 employees to ChatGPT Enterprise in one of the fastest deployments of its kind.
Global competition in agentic payments is intensifying as Citi, US Bank and Westpac trial Mastercard Agent Pay. Westpac recently completed New Zealand’s first authenticated agentic transaction, while DBS, Visa, Axis Bank and RBL Bank are advancing similar intelligent commerce pilots.
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MIT researchers have developed a new AI approach that helps engineers solve complex design problems faster, from power grid optimisation to vehicle safety.
The method adapts a foundation model trained on tabular data, enabling high-dimensional optimisation without retraining and significantly speeding up results.
The system uses a foundation model with Bayesian optimisation to pinpoint the variables that most impact outcomes. Focusing on key variables, the model finds top solutions 10 to 100 times faster than existing optimisation methods.
Early tests show the approach excels in costly, time-consuming scenarios like car crash testing and power system design. The technique lowers computational demands and suits large-scale, high-frequency engineering challenges across multiple domains.
Researchers aim to expand the method to even higher-dimensional problems, such as naval ship design, while highlighting the broader potential of foundation models as algorithmic engines in scientific and engineering tools.
Experts see it as a practical step toward making advanced optimisation more accessible in real-world applications.
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Google’s Gemini 3.1 Flash-Lite has launched in preview for developers via AI Studio and for enterprises through Vertex AI. Designed for high-volume workloads, it promises fast, cost-effective performance while maintaining high-quality outputs.
Priced at just $0.25 per million input tokens and $1.50 per million output tokens, 3.1 Flash-Lite offers 2.5X faster response times and 45% higher output speed than the previous 2.5 Flash model.
Benchmarks show strong performance across reasoning and multimodal tasks, including an Elo score of 1432 on Arena.ai, 86.9% on GPQA Diamond, and 76.8% on MMMU Pro, surpassing some older, larger Gemini models.
The model also provides adaptive intelligence features, allowing developers to adjust how much the AI ‘thinks’ for each task. The model handles both high-frequency tasks, such as translation, and complex tasks, such as interface generation and simulations.
Early-access developers and companies report that 3.1 Flash-Lite handles complex workloads with precision comparable to larger models. Its speed, affordability, and reasoning capabilities make it an attractive choice for scalable, real-time AI applications.
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Google is accelerating Chrome’s release cycle rather than maintaining its long-standing four-week cadence.
From September, users on desktop and mobile platforms will receive new stable versions every two weeks, doubling the frequency of feature milestones across speed, stability and usability. Weekly security updates introduced in 2023 remain unchanged.
The faster pace comes as AI-driven browsers seek a foothold in a market long dominated by Chrome.
Products, such as ChatGPT Atlas and Perplexity’s Comet, embed agentic assistants directly into the browsing experience, automating tasks from summarising pages to scheduling meetings.
Chrome has responded with deeper Gemini integration, including the rollout of autonomous features across its interface.
Google maintains that the accelerated schedule reflects the needs of the evolving web platform, arguing that developers require quicker access to updated tools.
Yet the timing aligns with growing competitive pressure from AI-native browsers, prompting speculation that Chrome’s dominance can no longer be taken for granted.
The shift will begin with Chrome version 153 in beta and stable channels on 8 September 2026. Enterprise administrators and Chromebook users will continue to rely on the eight-week Extended Stable branch, which remains unchanged for organisations that need slower, controlled deployments.
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Ransomware attacks are increasingly relying on stolen passwords rather than traditional malware, according to Cloudflare’s latest annual threat report. Attackers now exploit legitimate account credentials to blend into regular traffic, making breaches harder to detect and contain.
Manufacturing and critical infrastructure organisations account for over half of targeted attacks, reflecting their high operational stakes.
Cloudflare highlighted that AI is enabling attackers to prioritise speed and scale over technical sophistication. Generative AI lets criminals automate fraud, hijacking email threads and targeting a ~$49,000 sweet spot to maximise profit while avoiding scrutiny.
Nation-state actors also leverage legitimate platforms for command-and-control operations, with Russia, China, Iran, and North Korea each following distinct cyber strategies.
Researchers warned that modern ransomware is less a malware crisis and more an identity and access challenge. Attackers using authorised credentials can bypass defences and execute high-impact extortion, marking a significant shift in global threat vectors.
The report urges businesses to strengthen identity security, monitor access, and defend against AI-driven attacks that exploit impersonation and automation at scale.
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The European Commission is preparing more stringent requirements for ageing data centres rather than allowing legacy infrastructure to operate under looser rules.
A draft strategy tied to the EU’s tech sovereignty package signals that older sites will face higher efficiency expectations and stricter sustainability checks as part of an effort to modernise the digital backbone of the EU.
The proposal outlines minimum performance standards for new data centres by 2030, aiming to align the entire sector with the bloc’s climate and resilience goals. Officials want to reduce energy waste and improve monitoring across facilities that have long operated without uniform benchmarks.
The draft points to an expanded role for the Cloud and AI Development Act, which is expected to frame future obligations for cloud providers instead of relying on fragmented national measures.
Brussels sees consistent rules as essential for supporting secure cloud services, AI infrastructure and cross-border digital operations.
The strategy underscores that modernisation is central to the EU’s vision of tech sovereignty. Older centres would need upgrades to maintain compliance, ensuring that Europe’s digital infrastructure remains competitive, efficient and less dependent on external providers.
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