Artificial intelligence Archives | Digital Watch Observatory

OpenAI expands London research hub

OpenAI is turning its London office into its largest research hub outside the US, marking a strategic shift towards deeper engagement with the UK’s rapidly developing AI landscape. The move places the company in direct competition with Google DeepMind for scientific talent.

An expansion that strengthens OpenAI’s long-term presence in Europe by building a substantial research base rather than relying on satellite operations. The firm aims to attract researchers seeking strong academic links, regulatory clarity and access to the UK’s growing AI ecosystem.

The enlarged London team is expected to support frontier model development and experimental work that aligns with OpenAI’s international ambitions. Senior leadership framed the decision as a vote of confidence in the UK’s capacity to become one of the most influential centres for advanced AI research.

The announcement intensifies debate over global competition for expertise, as major labs seek locations that balance research freedom with responsible oversight.

OpenAI’s investment signals a belief that the UK can offer such conditions while positioning itself as a key player in shaping the next generation of AI capabilities.

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Data sovereignty becomes an infrastructure strategy in the AI era

For most of the past decade, data governance was treated as a legal issue. IT built networks and bought tools, while regulators were someone else’s problem. That division no longer holds. Cloud adoption and AI have turned data sovereignty into a core infrastructure and strategy question.

Regulatory frameworks such as GDPR, NIS2, and DORA are expanding and being enforced more strictly. Governments are also scrutinising foreign cloud providers and cross-border access. Local data storage no longer ensures absolute data sovereignty if critical control layers remain outside national jurisdiction.

Traditional SASE and SSE models were not built for this environment. Many still separate outbound cloud traffic from inbound controls. That split creates blind spots in distributed architectures and complicates consistent policy enforcement.

AI workloads intensify the pressure. Retailers, banks, and manufacturers are deploying models locally, not just in hyperscale clouds. Securing east-west traffic across systems and APIs without undermining data sovereignty is becoming a central architectural challenge.

Managed sovereign infrastructure is one response. It reduces reliance on external cloud paths while preserving operational scale. Ultimately, organisations must align security, AI deployment, and governance with long-term resilience goals.

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Nano Banana 2 brings Flash speed to Gemini image generation

Google has introduced Nano Banana 2, branded Gemini 3.1 Flash Image, combining Flash speed with advanced reasoning. The update narrows the gap between rapid generation and visual quality, enabling faster edits. Improved instruction-following enhances the handling of complex prompts.

Nano Banana 2 integrates real-time web grounding to improve subject accuracy and contextual awareness. The model supports more precise text rendering and in-image translation for marketing and localisation tasks. It can also assist with diagrams, infographics, and data visualisations.

Upgrades include stronger subject consistency across multiple characters and objects within a single workflow. Users can create assets in aspect ratios and resolutions from 512px to 4K. Google highlighted improvements in lighting, textures, and photorealism while maintaining Flash-level speed.

The model is rolling out across the Gemini app, Search, Lens, AI Studio, Vertex AI, Flow, and Google Ads. In Gemini, Nano Banana 2 replaces Nano Banana Pro by default, though Pro remains available for specialised tasks. Availability is expanding to additional countries and languages.

Google also reinforced its provenance strategy by combining SynthID watermarking with C2PA Content Credentials. The company said verification tools in Gemini have been used millions of times to identify AI-generated media. C2PA verification will be added to the app in a future update.

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European businesses gain AI-powered contract tools with local data hosting

Workday has rolled out its Contract Lifecycle Management (CLM) platform with EU-hosted data in Frankfurt, allowing European organisations to use AI contract tools while keeping all data within the EU.

German, French, and Spanish language support is live, with more languages planned. The update is part of Workday’s EU Sovereign Cloud strategy, targeting the CLM market, which is set to grow to $1.9 billion by 2033.

The platform uses AI agents to automate contracts. The Contract Intelligence Agent extracts terms, obligations, and renewal dates to create a searchable repository, while the Contract Negotiation Agent flags deviations, drafts redlines, and speeds approvals.

Multilingual support ensures smooth workflows across Europe’s largest commercial languages, improving compliance and efficiency.

GDPR compliance remains critical, with fines up to €20 million or 4% of global turnover. EU-hosted CLM removes offshore data risks, which are crucial for the finance, healthcare, and defence sectors. Workday combines AI efficiency with full legal compliance.

Decision-makers should focus on three priorities: EU data residency, leveraging AI agents to accelerate contracts, and integrating CLM with HR and finance systems to maximise value. Workday aims to capture market share in Europe against competitors such as Icertis and DocuSign.

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Pakistan’s digital transformation highlighted as UNESCO advances AI ethics

UNESCO used the Pakistan Governance Forum 2026 to highlight the need for a structured Ethical AI and Data Governance Framework as the country accelerates its digital transformation.

Federal leaders, provincial authorities and civil society convened to examine governance reforms, with UNESCO urging Pakistan to align its expanding digital public infrastructure with coherent standards that protect rights while enabling innovation.

Speaking at the Forum, Fuad Pashayev underlined that Pakistan’s reform priority should centre on the Recommendation on the Ethics of Artificial Intelligence, adopted unanimously by all 193 Member States.

Anchoring national systems in transparency, accountability and meaningful human oversight was framed as essential for maintaining public trust as digital services reshape access to benefits and interactions between citizens and the state.

To support the shift, UNESCO promoted its AI Readiness Assessment Methodology (RAM), which is already deployed in more than 50 countries. The tool helps governments identify regulatory gaps, strengthen institutional coordination and design safeguards against discrimination and algorithmic bias.

UNESCO has already contributed to Pakistan’s draft National AI Policy, ensuring alignment with international ethical frameworks while accommodating national development needs.

Capacity building formed a major pillar of UNESCO’s engagement. In partnership with the University of Oxford, the organisation launched a global course on AI and Digital Transformation in Government in 2025, attracting over nineteen thousand enrolments worldwide.

Pakistan leads participation globally, reflecting both the country’s momentum and growing demand for structured training.

UNESCO’s ongoing work aims to reinforce data governance, improve AI readiness and embed ethical safeguards across Pakistan’s digital transformation strategy.

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Agentic AI network slicing launches in 5G Advanced with Nokia and AWS

Nokia and Amazon Web Services have introduced what they describe as the first agentic AI-powered network slicing solution operating in commercial 5G-Advanced networks. Early pilot projects with du and Orange are already underway, marking the transition from laboratory testing to commercial deployment.

For an extended period, network slicing has been presented as a way to tailor connectivity to the needs of enterprises and end users, yet static configurations have until now limited its commercial impact. A more autonomous approach is now being tested, designed to convert operational intent directly into concrete network actions.

The joint system combines Nokia’s network slicing portfolio with AI services delivered via the Amazon Web Services (AWS) Bedrock platform. Software agents analyse real-time data, including traffic levels, location information, and significant events, and automatically adjust radio access network policies. However, this enables capacity to be prioritised in response to congestion, emergencies, or large gatherings.

Enterprise use is central to the deployment. Campuses, factories, and urban areas can receive connectivity aligned with predefined service level targets (SLAs), while public safety teams can activate dedicated network slices during critical incidents. Premium consumer services, such as gaming and streaming, may also benefit from more stable performance during peak demand periods.

The solution spans the radio, transport, and core networks and will be showcased at the Mobile World Congress 2026. Commercial success will depend on whether intent-based slicing can transform what has long been a promised feature into a sustainable and scalable revenue source for operators.

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Google API keys exposed after Gemini privilege expansion

Security researchers warn that exposed Google API keys in public client-side code could be used to authenticate with the Gemini AI assistant and access private data. The issue arose after developers enabled the Generative Language API in existing projects without updating key permissions.

Truffle Security scanned the November 2025 Common Crawl dataset and identified more than 2,800 live Google API keys publicly exposed in website source code. Some belonged to financial institutions, security firms, recruitment companies, and Google infrastructure.

Before Gemini’s launch, Google Cloud API keys were widely treated as non-sensitive identifiers for services such as Maps, YouTube embeds, analytics, and Firebase. After Gemini was introduced, those duplicate Google API keys also acted as authentication credentials for the AI assistant, expanding their privileges.

Researchers demonstrated the risk by using one exposed key to query the Gemini API models endpoint and list available models. They warned that attackers could exploit such access to extract private data or generate substantial API charges on victim accounts.

Google was notified in November 2025 and later classified the issue as a single-service privilege escalation. The company said it has introduced controls to block leaked keys, limit new AI Studio keys to Gemini-only scope, and notify developers of detected exposure.

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Financial crime risks are reshaped by the rise of autonomous AI agents

Autonomous AI agents are transforming finance by executing transactions independently and speeding up workflows in digital assets and programmable finance. Software can manage wallets and move funds across blockchains in seconds, narrowing detection windows.

AI agents don’t create new crimes but increase speed and complexity, making accountability essential. Responsibility rests with developers, operators, and beneficiaries, with investigators tracing control, configuration, and economic benefit to determine liability.

Weak oversight or misconfigured rules can lead to significant compliance and enforcement consequences.

Investigations face new challenges as autonomous agents operate across multiple blockchains, decentralised exchanges, and global jurisdictions.

Real-time analytics and automated tracing are essential to link transactions to accountable actors before funds move. Governance architecture and monitoring systems increasingly serve as evidence in regulatory or criminal actions.

Institutions and law enforcement are using AI monitoring, anomaly detection, and automated containment systems. Autonomous AI impacts sanctions and national security, emphasising the need for human oversight alongside automation.

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AI becomes central to biotech discovery and drug development

The biotechnology industry is moving from early AI experimentation to fully integrated discovery systems that embed AI into everyday research operations.

According to the 2026 Biotech AI Report from Benchling, leading organisations are reshaping data environments and R&D structures, making AI a core part of the drug development process.

Predictive models, such as protein structure prediction and docking simulations, are accelerating early-stage discovery, helping scientists identify targets faster and improve accuracy.

Challenges persist in generative design, biomarker analysis, and ADME prediction, where adoption lags due to fragmented or poor-quality data.

Organisations overcoming these hurdles invest in high-quality, well-annotated measurements and strong integration between wet and dry lab work. It creates a continuous learning cycle that drives faster insights and reduces experimental dead ends.

Talent strategies are evolving to place AI expertise directly in R&D teams. Many firms upskill existing scientific staff to act as ‘scientific translators,’ bridging biology, regulatory needs, and machine learning.

Embedding AI leadership within research teams or using hybrid models reduces handoffs and ensures AI tools remain practical in real-world experiments.

Biotech firms combine in-house development with commercial components, following a ‘build what differentiates, buy what scales’ strategy. Confidence in AI is rising, driving investment in infrastructure, modelling, and integrated AI workflows for research.

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AI use among students surges as chatbots reshape schoolwork

More than half of US teenagers use AI tools to help with schoolwork, according to a new Pew Research Center study. The survey found that 54% of students aged 13 to 17 have used chatbots such as OpenAI’s ChatGPT or Microsoft’s Copilot to research assignments or solve maths problems.

Usage has risen in recent years. In 2024, 26% of US teens reported using ChatGPT for schoolwork, up from 13% in 2023. The latest survey of 1,458 teens and parents found 44% use AI for some schoolwork, while 10% rely on chatbots for most tasks.

Researchers say AI assistance is becoming routine in classrooms. Colleen McClain, a senior researcher at Pew and co-author of the report, said chatbot use for schoolwork is now a common practice among teens.

Findings come amid an intensifying debate over generative AI in education. Supporters argue that schools should teach students to use and evaluate AI tools, while critics warn of misinformation, reduced critical thinking, and increased cheating.

Recent research has raised questions about learning outcomes. One study by Cambridge University Press & Assessment and Microsoft Research found that students who took notes without chatbot support showed stronger reading comprehension than those using AI assistance.

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