Digital business models Archives | Page 278 of 563

UK estate agents adopt AI tools to offset hiring challenges

UK property agents are increasingly leveraging AI and automation to tackle a growing skills shortage in the sector, according to an analysis by PropTech provider Reapit.

Reapit’s Property Outlook Report 2025 shows that although agencies continue hiring, most face recruitment difficulties: more than half receive fewer than five qualified applicants per vacancy. Growth in payrolled employees is minimal, and the slowest year-on-year rise since May 2021 reflects wider labour market tightness.

In response, agencies are turning to time-saving technologies. A majority report that automation is more cost-effective than expanding headcount, with nearly 80 percent citing increased productivity from these tools.

This shift towards PropTech and AI reflects deeper structural pressures in the UK real estate sector: high employment costs, slower workforce growth, and increasing demands for efficiency are reshaping the role of technology in agency operations.

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Candidates urged to balance AI support with integrity

Taylor Wessing has released guidance for early-career applicants on using AI tools such as ChatGPT, Copilot, Claude and Bing Chat during the application process. The firm frames AI as a helpful ally, not a shortcut, and emphasises responsible and authentic use.

AI can assist with refining cover letters, improving structure, and articulating motivations. It can also support interview preparation through mock question practice and help candidates deepen their understanding of legal issues.

However, authenticity is paramount. Taylor Wessing encourages applicants to ensure their work reflects their voice. Using AI to complete online assessments is explicitly discouraged, as these are designed to evaluate natural ability and personal fit.

According to the firm, while AI can bolster readiness for training schemes, over-reliance or misuse may backfire. They advise transparency about any AI assistance and underscore the importance of integrity throughout the process.

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Top cybersecurity vendors double down on AI-powered platforms

The cybersecurity market is consolidating as AI reshapes defence strategies. Platform-based solutions replace point tools to cut complexity, counter AI threats, and ease skill shortages. IDC predicts that security spending will rise 12% in 2025 to $377 billion by 2028.

Vendors embed AI agents, automation, and analytics into unified platforms. Palo Alto Networks’ Cortex XSIAM reached $1 billion in bookings, and its $25 billion CyberArk acquisition expands into identity management. Microsoft blends Azure, OpenAI, and Security Copilot to safeguard workloads and data.

Cisco integrates AI across networking, security, and observability, bolstered by its acquisition of Splunk. CrowdStrike rebounds from its 2024 outage with Charlotte AI, while Cloudflare shifts its focus from delivery to AI-powered threat prediction and optimisation.

Fortinet’s platform spans networking and security, strengthened by Suridata’s SaaS posture tools. Zscaler boosts its Zero Trust Exchange with Red Canary’s MDR tech. Broadcom merges Symantec and Carbon Black, while Check Point pushes its AI-driven Infinity Platform.

Identity stays central, with Okta leading access management and teaming with Palo Alto on integrated defences. The companies aim to platformise, integrate AI, and automate their operations to dominate an increasingly complex cyberthreat landscape.

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OpenAI’s GPT-5 faces backlash for dull tone

OpenAI’s GPT-5 launched last week to immense anticipation, with CEO Sam Altman likening it to the iPhone’s Retina display moment. Marketing promised state-of-the-art performance across multiple domains, but early user reactions suggested a more incremental step than a revolution.

Many expected transformative leaps, yet improvements mainly were in cost, speed, and reliability. GPT-5’s switch system, which automatically routes queries to the most suitable model, was new, but its writing style drew criticism for being robotic and less nuanced.

Social media buzzed with memes mocking its mistakes, from miscounting letters in ‘blueberry’ to inventing US states. OpenAI quickly reinstated GPT-4 for users who missed its warmer tone, underlining a disconnect between expectations and delivery.

Expert reviews mirrored public sentiment. Gary Marcus called GPT-5 ‘overhyped and underwhelming’, while others saw modest benchmark gains. Coding was the standout, with the model topping leaderboards and producing functional, if simple, applications.

OpenAI emphasised GPT-5’s practical utility and reduced hallucinations, aiming for steadiness over spectacle. At the same time, it may not wow casual users, its coding abilities, enterprise appeal, and affordability position it to generate revenue in the fiercely competitive AI market.

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Seedbox.AI backs re-training AI models to boost Europe’s competitiveness

Germany’s Seedbox.AI is betting on re-training large language models (LLMs) rather than competing to build them from scratch. Co-founder Kai Kölsch believes this approach could give Europe a strategic edge in AI.

The Stuttgart-based startup adapts models like Google’s Gemini and Meta’s Llama for medical chatbots and real estate assistant applications. Kölsch compares Europe’s role in AI to improving a car already on the road, rather than reinventing the wheel.

A significant challenge, however, is access to specialised chips and computing power. The European Union is building an AI factory in Stuttgart, Germany, which Seedbox hopes will expand its capabilities in multilingual AI training.

Kölsch warns that splitting the planned EU gigafactories too widely will limit their impact. He also calls for delaying the AI Act, arguing that regulatory uncertainty discourages established companies from innovating.

Europe’s AI sector also struggles with limited venture capital compared to the United States. Kölsch notes that while the money exists, it is often channelled into safer investments abroad.

Talent shortages compound the problem. Seedbox is hiring, but top researchers are lured by Big Tech salaries, far above what European firms typically offer. Kölsch says talent inevitably follows capital, making EU funding reform essential.

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Google launches small AI model for mobiles and IoT

Google has released Gemma 3 270M, an open-source AI model with 270 million parameters designed to run efficiently on smartphones and Internet of Things devices.

Drawing on technology from the larger Gemini family, it focuses on portability, low energy use and quick fine-tuning, enabling developers to create AI tools that work on everyday hardware instead of relying on high-end servers.

The model supports instruction-following and text structuring with a 256,000-token vocabulary, offering scope for natural language processing and on-device personalisation.

Its design includes quantisation-aware training to work in low-precision formats such as INT4, reducing memory use and improving speed on mobile processors instead of requiring extensive computational power.

Industry commentators note that the model could help meet demand for efficient AI in edge computing, with applications in healthcare wearables and autonomous IoT systems. Keeping processing on-device also supports privacy and reduces dependence on cloud infrastructure.

Google highlights the environmental benefits of the model, pointing to reduced carbon impact and greater accessibility for smaller firms and independent developers. While safeguards like ShieldGemma aim to limit risks, experts say careful use will still be needed to avoid misuse.

Future developments may bring new features, including multimodal capabilities, as part of Google’s strategy to blend open and proprietary AI within hybrid systems.

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Cohere secures $500m funding to expand secure enterprise AI

Cohere has secured $500 million in new funding, lifting its valuation to $6.8 billion and reinforcing its position as a secure, enterprise-grade AI specialist.

The Toronto-based firm, which develops large language models tailored for business use, attracted backing from AMD, Nvidia, Salesforce, and other investors.

Its flagship multilingual model, Aya 23, supports 23 languages and is designed to help companies adopt AI without the risks linked to open-source tools, reflecting growing demand for privacy-conscious, compliant solutions.

The round marks renewed support from chipmakers AMD and Nvidia, who had previously invested in the company.

Salesforce Ventures’ involvement hints at potential integration with enterprise software platforms, while other backers include Radical Ventures, Inovia Capital, PSP Investments, and the Healthcare of Ontario Pension Plan.

The company has also strengthened its leadership, appointing former Meta AI research head Joelle Pineau as Chief AI Scientist, Instagram co-founder Mike Krieger as Chief Product Officer, and ex-Uber executive Saroop Bharwani as Chief Technology Officer for Applied R&D.

Cohere intends to use the funding to advance agentic AI, systems capable of performing tasks autonomously, while focusing on security and ethical development.

With over $1.5 billion raised since its 2019 founding, the company targets adoption in regulated sectors such as healthcare and finance.

The investment comes amid a broader surge in AI spending, with industry leaders betting that secure, customisable AI will become essential for enterprise operations.

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Tokenised stocks bring limited benefits and high risks

The cryptocurrency sector has promoted tokenised stocks, allowing shares to be traded via blockchain. While fractional ownership and 24/7 trading are possible, most brokers already offer commission-free fractional shares, limiting the benefits for individual investors.

Tokenised stocks require a custodian to hold the underlying asset, a digital token representing the share, and smart contracts granting rights such as dividends and voting. Platforms like Kraken and Robinhood now offer tokenised trading, while asset managers like BlackRock explore tokenised funds.

Proponents cite transparency, security, and direct access to companies as advantages.

Risks remain significant. Transactions may be irrevocable, and uncertain legal protections, and smart contracts cannot cover all scenarios. Experts warn that tokenisation may bypass securities laws, risking market trust and investor protections.

Many analysts suggest the crypto industry’s push for tokenisation is driven more by a desire to integrate with traditional finance and attract institutional capital than by benefits to retail investors. Advantages are limited while risks, including regulatory uncertainty and potential fraud, are substantial.

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State-controlled messaging alters crypto usage in Russia

The Russian government limits secure calls on WhatsApp and Telegram, citing terrorism and fraud concerns. The measures aim to push users toward state-controlled platforms like MAX, raising privacy concerns.

With over 100 million users relying on encrypted messaging, these restrictions threaten the anonymity essential for cryptocurrency transactions. Government-monitored channels may let authorities track crypto transactions, deterring users and businesses from adopting digital currencies.

State-backed messaging platforms also open the door to regulatory oversight, complicating private crypto exchanges and noncustodial wallets.

In response, fintech startups and SMEs may turn to decentralised applications and privacy-focused tools, including zero-knowledge proofs, to maintain secure communication and financial operations.

The clampdown could boost crypto payroll adoption in Russia, reducing costs and shielding firms from economic instability. Using decentralised finance tools in alternative channels allows companies to protect privacy and support cross-border payments and remote work.

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New framework planned for crypto asset flows in South Africa

South Africa is preparing a new regulatory framework for cross-border cryptocurrency transactions, according to Finance Minister Enoch Godongwana. The South African Reserve Bank will release the framework this year, focusing on cross-border crypto asset transfers.

The move comes after a High Court ruling left cryptocurrencies exempt from exchange control regulations. Instead of a broad exemption framework for exchanges, authorities aim to regulate the activities of crypto asset service providers involved in moving value across borders.

The framework will set conditions, administrative duties, and reporting requirements to curb illicit flows and prevent regulatory loopholes.

SARB works closely with the National Treasury, the Financial Sector Conduct Authority, and other financial bodies to finalise the rules.

Officials say the goal is to align South Africa’s exchange control laws with the realities of the digital asset market while addressing the risks identified by the Intergovernmental Fintech Working Group.

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