Development

Reddit tests AI shopping search

Reddit has begun testing an AI-powered shopping search tool with a limited group of users in the US. Search queries for product ideas now generate interactive carousels featuring prices, images and direct links to retailers.

Items appearing in the results are drawn from recommendations shared in posts and comments across the platform. Listings are connected to Reddit’s advertising and shopping partners, bringing community discussions closer to online purchasing.

Expansion into AI-led commerce builds on the company’s earlier launch of Dynamic Product Ads, designed to deliver personalised suggestions. Closer integration of search and shopping signals a broader effort to strengthen digital revenue streams.

Chief executive Steve Huffman recently described AI search as a significant business opportunity beyond product development alone. Weekly search users increased from 60 million to 80 million over the past year, while engagement with the AI-powered Reddit Answers tool rose sharply throughout 2025.

Developments place Reddit alongside other technology platforms investing in AI-driven retail features. Growing user engagement suggests the company sees search as central to its future commercial strategy.

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India’s UIDAI rolls out AI-enabled biometric deduplication and document verification platform

UIDAI has deployed an advanced platform that uses AI-enabled models to improve biometric deduplication, the process of ensuring that each resident has a unique identity record, by checking fingerprints, facial images and iris scans against the entire Aadhaar database.

The authority describes this system, developed with the International Institute of Information Technology, Hyderabad, as an ‘Invisible Shield’ that can perform billions of computations efficiently at a population scale, running on high-performance inference infrastructure such as NVIDIA DGX systems to enhance accuracy and speed nationwide.

In addition to biometric matching, the platform incorporates AI-based document metadata extraction and verification to curb enrolment fraud, using secure APIs (e.g. DigiLocker) for source-of-truth checks against submitted documents.

The system is already being rolled out in several states. It is expected to expand across India in the coming months, boosting service quality, reducing turnaround times for Aadhaar enrolment and update transactions, and reinforcing trust in the digital identity infrastructure.

The initiative is part of a broader push to leverage AI for fraud detection and identity assurance at a national scale. It comes amid ongoing efforts by UIDAI to modernise authentication processes as biometric and AI-based systems evolve.

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Bremen trials AI-based safety system ‘AI Watch’ on city trams

The city of Bremen, Germany, has begun piloting an AI-based safety system called AI Watch on its tram fleet. The technology uses onboard cameras and computer vision models to automatically detect potential safety issues, such as passengers too close to doors, objects on the tracks, or unexpected pedestrian behaviour, and alerts tram operators in real time.

The goal is to reduce accidents and enhance situational awareness without replacing human oversight.

Developed with transport and AI specialists, AI Watch integrates with vehicles’ existing sensor suites and is designed to function in real-time operational environments. During the pilot, the system has been tested under various traffic and lighting conditions to refine hazard recognition accuracy and minimise false alarms.

BSAG representatives say the AI support tool complements human judgement, helping drivers focus on decision-making rather than continuously scanning for hazards.

The initiative comes as cities explore AI applications in urban mobility, from predictive maintenance to intelligent traffic management and automated incident detection, to improve safety, efficiency and passenger experience.

Bremen’s pilot will be evaluated for scalability across additional routes and potentially other types of public transport vehicles.

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Google’s Lyria 3 advances generative AI music with transparency and copyright safeguards

Google has introduced Lyria 3 inside its Gemini app, marking its expansion into AI-generated music. The model enables users to create 30-second tracks from text prompts, images, or short videos. It also supports Dream Track on YouTube Shorts, strengthening AI integration in creator tools.

The development reflects the growing convergence of multimodal AI systems. Gemini can already generate text, images, and video, and music is now added to this ecosystem. This positions Google within the broader race to embed generative AI across digital content infrastructures.

Lyria 3 lowers technical barriers to music production. Users can generate instrumentals and lyrics without prior composition skills, simply by describing a mood, genre, or memory. This aligns with wider efforts to democratise creative expression through AI tools.

The model also introduces technical improvements over earlier audio systems. It offers greater control over tempo, vocals, and style, while producing more realistic and musically complex outputs. However, tracks are currently limited to 30 seconds, suggesting a phased rollout approach.

Transparency measures are embedded through SynthID watermarking technology. All AI-generated tracks include an imperceptible identifier to signal synthetic origin. Such mechanisms respond to increasing policy discussions on labelling and traceability of AI-generated content.

Google also emphasises safeguards related to intellectual property. The system is designed for original expression rather than direct imitation of specific artists. Prompts referencing known artists are treated as stylistic inspiration, and outputs are filtered against existing works, with reporting mechanisms available for potential rights violations.

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AI productivity gap reveals critical enterprise adoption challenges

AI continues to generate expectations of broad economic transformation, particularly in productivity and employment. However, the extent of measurable economy-wide gains remains uncertain, and the overall impact of AI on business performance is still being assessed.

An extensive survey conducted by the National Bureau of Economic Research (NBER) found that while around 70% of firms across the US, UK, Germany, and Australia report using AI, nearly 9 in 10 companies have seen no significant effect on productivity or employment over the past 3 years. The findings suggest a gap between adoption rates and tangible outcomes.

Current enterprise use of AI remains concentrated in specific functions, including text generation with large language models, visual content creation, and data processing. Although previous studies have identified productivity gains in targeted areas such as customer support and writing tasks, these improvements have not yet translated into broad organisational performance increases.

Despite limited results to date, business leaders expect AI to deliver modest productivity gains in the coming years. The survey highlights a divergence in expectations, with senior executives anticipating slight reductions in employment, while employees foresee small job growth linked to AI adoption.

At the same time, some technology leaders predict more immediate disruption. Microsoft AI leader has argued that AI could soon reach human-level performance in many professional tasks, potentially reshaping white-collar work within the next few years.

The survey also indicates limited engagement with AI tools among top executives, with many reporting minimal or no direct use of them. This suggests that while AI investment is widespread, its integration into day-to-day leadership practices remains uneven.

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South Africa balances fintech innovation with financial stability

South Africa’s fintech sector has evolved from a niche disruptor into a pillar of the digital economy, fuelled by rapid digital adoption and entrepreneurial growth. Regulators are now tasked with supporting innovation in decentralised finance and AI while safeguarding market stability and consumer protection.

Coordinated oversight has been central to that effort. The Intergovernmental Fintech Working Group, bringing together the National Treasury, the South African Reserve Bank and the Financial Sector Conduct Authority, promotes a harmonised and principle-based regulatory approach.

A significant turning point came when crypto assets were classified as financial products under the Financial Advisory and Intermediary Services Act. Licensing requirements for Crypto Asset Service Providers and alignment with Financial Action Task Force standards strengthened consumer safeguards and anti-money laundering controls.

Fintech also plays a growing role in financial inclusion, particularly through mobile money, digital lending and digital payments. Wider access to affordable financial tools supports inclusive economic growth across underserved communities.

AI presents fresh regulatory questions around bias, transparency and operational resilience. Ensuring compliance with the Protection of Personal Information Act while encouraging responsible experimentation remains central to South Africa’s evolving fintech strategy.

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Global South at the heart of India AI plan

India has unveiled the New Delhi Frontier AI Impact Commitments, a new initiative aimed at promoting inclusive and responsible AI, particularly across the Global South. The announcement was made by Union Minister for Electronics and Information Technology Ashwini Vaishnaw at the opening of the India AI Impact Summit 2026.

Vaishnaw described India’s AI strategy as focused on democratisation, scale, and technological sovereignty. He outlined a comprehensive approach spanning the whole AI ecosystem, including applications, models, computing infrastructure, talent, and energy, with a strong emphasis on practical use in sectors such as healthcare, agriculture, education, and public services.

Framing AI as a transformative technology, the minister stressed that its benefits must reach the widest possible population. He called for a human-centric approach that prioritises safety and dignity, while also addressing risks linked to rapid technological change.

The voluntary commitments bring together Indian innovators such as Sarvam, BharatGen, Gnani.ai, and Soket alongside leading global AI companies. Together, they aim to ensure that AI systems are developed and deployed in ways that reflect equity, cultural diversity, and local realities.

One of the core pledges focuses on improving understanding of how AI is used in the real world. Participating organisations will share anonymised and aggregated insights to help policymakers assess AI’s impact on jobs, skills, productivity, and economic transformation, supporting more informed decision-making.

Another key commitment seeks to strengthen multilingual and context-sensitive AI evaluation. By developing datasets and benchmarks in underrepresented languages and cultural settings, the initiative aims to improve system performance for diverse populations and expand access to high-quality AI tools globally.

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Geneva to host 2027 global AI summit

Switzerland will host the 2027 edition of the global AI summit in Geneva, President Guy Parmelin announced on Thursday at the 2026 AI Summit in New Delhi. Speaking at a high-level session attended by Indian Prime Minister Narendra Modi and Brazilian President Luiz Inácio Lula da Silva, Parmelin said Switzerland was ready to welcome global leaders to discuss the future of AI.

Calling Geneva ‘the epicentre of multilateralism,’ Parmelin said the city offers a natural platform for international cooperation on emerging technologies. He added that Switzerland looks forward to organising the event and collaborating with the United Arab Emirates, which is set to host the summit in 2028.

The Swiss Federal Council had already signalled its interest in hosting the 2027 edition ahead of the New Delhi meeting. Last month, the government confirmed that financing had been secured and that organisational preparations were already complete.

The summit has been held annually since 2023, beginning in the United Kingdom and then in South Korea and France. The gatherings aim to promote global dialogue on both the opportunities and risks of AI, including its impact on healthcare, climate action, agriculture, and broader society.

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Adoption of agentic AI slowed by data readiness and governance gaps

Agentic AI is emerging as a new stage of enterprise automation, enabling systems to reason, plan, and act across workflows. Adoption, however, remains uneven, with far fewer organisations scaling deployments beyond pilots.

Unlike traditional analytics or generative tools, agentic systems make decisions rather than simply producing insights. Without sufficient context, they struggle to align actions with real business conditions, revealing a persistent context gap.

Recent survey data highlights this disconnect. Although executives express confidence in AI ambitions, significant shares cite data readiness, infrastructure, and skills as barriers. Many identify AI as central to strategy, yet only a limited proportion tie deployments to measurable business outcomes.

Effective agentic AI depends on layered data foundations. Public data provides baseline capability, organisational data enables operational competence, and third-party context supports differentiation. Weak governance or integration can undermine autonomy at scale.

Enterprises that align data governance, enrichment, and AI oversight are more likely to scale beyond pilots. Progress depends less on model sophistication than on trusted data foundations that support transparency and measurable outcomes.

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MIT study finds AI chatbots underperform for vulnerable users

Research from the MIT Centre for Constructive Communication (CCC) finds that leading AI chatbots often provide lower-quality responses to users with lower English proficiency, less education, or who are outside the US.

Models tested include GPT-4, Claude 3 Opus, and Llama 3, which sometimes refuse to answer or respond condescendingly. Using TruthfulQA and SciQ datasets, researchers added user biographies to simulate differences in education, language, and country.

Accuracy fell sharply among non-native English speakers and less-educated users, with the most significant drop among those affected by both; users from countries like Iran also received lower-quality responses.

Refusal behaviour was notable. Claude 3 Opus declined 11% of questions for less-educated, non-native English speakers versus 3.6% for control users. Manual review showed 43.7% of refusals contained condescending language.

Some users were denied access to specific topics even though they answered correctly for others.

The study echoes human sociocognitive biases, in which non-native speakers are often perceived as less competent. Researchers warn AI personalisation could worsen inequities, providing marginalised users with subpar or misleading information when they need it most.

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