Despite the hype surrounding AI, new data suggests corporate adoption of AI is slowing.
A biweekly survey by the US Census Bureau found AI use among firms with over 250 employees dropped from nearly 14 percent in mid-June to under 12 percent in August, marking the largest decline since the survey began in November 2023.
Smaller companies with fewer than four workers saw a slight increase, but mid-sized businesses largely reported flat or falling AI adoption. The findings are worrying for tech investors and CEOs, who have invested heavily in enterprise AI in the hope of boosting productivity and revenue across industries.
So far, up to 95 per cent of companies using AI have not generated new income from the technology.
The decline comes amid underwhelming performance from high-profile AI releases. OpenAI’s GPT-5, expected to revolutionise enterprise AI, underperformed in benchmark tests, while some companies are rehiring human staff after previously reducing headcount based on AI promises.
Analysts warn that AI innovations may have plateaued, leaving enterprise adoption struggling to justify prior investments.
Unless enterprise AI starts delivering measurable results, corporate usage could continue to decline, signalling a potential slowdown in the broader AI-driven growth many had anticipated.
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Quantum computers could become more efficient with a new quantum router that directs data more quickly within machines. Researchers at Stanford have built the component, which could eventually form the backbone of quantum random access memory (QRAM).
The router utilises superconducting qubits, controlled by electromagnetic pulses, to transmit information to quantum addresses. Unlike classical routers, it can encode addresses in superposition, allowing data to be stored in two places simultaneously.
In tests with three qubits, the router achieved a fidelity of around 95%. If integrated into QRAM, it could unlock new algorithms by placing information into quantum states where locations remain indeterminate.
Experts say the advance could benefit areas such as quantum machine learning and database searches. It may also support future ideas, such as quantum IP addresses, although more reliable designs with larger qubit counts are still required.
The Stanford team acknowledges the device needs refinement to reduce errors. But with further development, the quantum router could be a vital step toward practical QRAM and more powerful quantum computing applications.
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Researchers combine human tissue models with explainable AI to analyse patient data and identify treatments that work best for specific patients. First applied to inflammatory bowel disease, the approach could improve clinical trial success rates and accelerate drug discovery.
REPROCELL, IBM, and the STFC Hartree Centre have developed Pharmacology-AI, a platform uniting tissue models with machine learning. Delivered through the Hartree National Centre for Digital Innovation, it reduces costs, enhances trial design, and enables more targeted therapies.
Unlike tools that seek to replace human expertise, the platform acts as a decision-support system. It helps scientists detect patterns in complex datasets while keeping outputs interpretable for clinical trial use. Developers emphasised usability, ensuring non-technical staff can work with the system.
Human fresh tissue models play a central role, preserving biological complexity and simulating drug effects before trials. However, this generates reliable data that can be paired with AI to identify optimal patient profiles and reduce the risk of costly trial failures.
The project’s success suggests broad applications beyond IBD. With explainable AI and high-quality patient data, Pharmacology-AI could improve outcomes across multiple disease areas, making drug development faster, more efficient, and more precise.
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Stablecoins have become central to the digital economy, with billions in daily transactions and stronger regulatory backing under the GENIUS Act. Yet experts warn that advances in quantum computing could undermine their very foundations.
Elliptic curve and RSA cryptography, widely used in stablecoin systems, are expected to be breakable once ‘Q-Day’ arrives. Quantum-equipped attackers could instantly derive private keys from public addresses, exposing entire networks to theft.
The immutability of blockchains makes upgrading cryptographic schemes especially challenging. Dormant wallets and legacy addresses may prove vulnerable, putting billions of dollars at risk if issuers fail to take action promptly.
Researchers highlight lattice-based and hash-based algorithms as viable ‘quantum-safe’ alternatives. Stablecoins built with crypto-agility, enabling seamless upgrades, will better adapt to new standards and avoid disruptive forks.
Regulators are also moving. NIST is finalising post-quantum cryptographic standards, and new rules will likely be established before 2030. Stablecoins that embed resilience today may set the global benchmark for digital trust in the quantum age.
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The rise of AI puts traditional entry-level roles under pressure, raising concerns that career ladders may no longer function as they once did. Industry leaders, including Anthropic CEO Dario Amodei, warn that AI could replace half of all entry-level jobs as machines operate nonstop.
A venture capital firm, SignalFire, found that hiring for graduates with under one year of experience at major tech firms fell by 50% between 2019 and 2024. The decline has been consistent across business functions, from sales and marketing to engineering and operations.
Analysts argue that while career pathways are being reshaped, the ladder’s bottom rung is disappearing, forcing graduates to acquire skills independently before entering the workforce.
Experts stress that the shift does not mean careers are over for new graduates, but it does signal a more challenging transition. Universities are already adapting by striking partnerships with AI companies, while some economists point out that past technological revolutions took decades to reshape employment.
Yet others warn that unchecked AI could eventually threaten entry-level roles and all levels of work, raising questions about the future stability of corporate structures.
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The United States, Japan, and South Korea held two Trilateral Quantum Cooperation meetings this week in Seoul and Tokyo. Officials and experts from government and industry gathered to discuss securing quantum ecosystems against cyber, physical, and intellectual property threats.
The US State Department stressed that joint efforts will ensure breakthroughs in quantum computing benefit citizens while safeguarding innovation. Officials said cooperation is essential as quantum technologies could reshape industries, global power balances, and economic prosperity.
The President of South Korea, Lee Jae Myung, described the partnership as entering a ‘golden era’, noting that Seoul, Washington, and Tokyo must work together both to address North Korea and to drive technological progress.
The talks come as Paul Dabbar, the former CEO of Bohr Quantum Technology, begins his role as US Deputy Secretary of Commerce. Dabbar brings experience in deploying emerging quantum network technologies to the new trilateral framework.
North Korea has also signalled interest in quantum computing for economic development. Analysts note that quantum’s lower energy demand compared to supercomputers could appeal to a country plagued by chronic power shortages.
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Ransomware groups have evolved into billion-dollar operations targeting critical infrastructure across multiple countries, employing increasingly sophisticated extortion schemes. Between 2020 and 2022, more than 865 documented attacks were recorded across Australia, Canada, New Zealand, and the UK.
Criminals have escalated from simple encryption to double and triple extortion, threatening to leak stolen data as added leverage. Attack vectors include phishing, botnets, and unpatched flaws. Once inside, attackers use stealthy tools to persist and spread.
BlackSuit, formerly known as Conti, led with 141 attacks, followed by LockBit’s 129, according to data from the Australian Institute of Criminology. Ransomware-as-a-Service groups hit higher volumes by splitting developers from affiliates handling breaches and negotiations.
Industrial targets bore the brunt, with 239 attacks on manufacturing and building products. The consumer goods, real estate, financial services, and technology sectors also featured prominently. Analysts note that industrial firms are often pressured into quick ransom payments to restore production.
Experts warn that today’s ransomware combines military-grade encryption with advanced reconnaissance and backup targeting, raising the stakes for defenders. The scale of activity underscores how resilient these groups remain, adapting rapidly to law enforcement crackdowns and shifting market opportunities.
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Apple is facing a new copyright lawsuit after two authors alleged the company used pirated copies of their books to train its OpenELM AI models. Filed in Northern California, the case claims Apple used the authors’ works without permission, payment, or credit.
The lawsuit seeks class-action status, adding Apple to a growing list of technology firms accused of misusing copyrighted works for AI training.
The action comes amid a wider legal storm engulfing AI companies. Anthropic recently agreed to a $1.5 billion settlement with authors who alleged its Claude chatbot was trained on their works without authorisation, in what lawyers called the most significant copyright recovery in history.
Microsoft, Meta, and OpenAI also face similar lawsuits over alleged reliance on unlicensed material in their datasets.
Analysts warn Apple could face heightened scrutiny given its reputation as a privacy-focused company. Any finding that its AI models were trained on pirated material could cause serious reputational harm alongside potential financial penalties.
The case also underscores the broader unresolved debate over whether AI training constitutes fair use or unlawful exploitation of creative works.
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ASML has reportedly become the top shareholder in French AI company Mistral after investing €1.3 billion. The deal forms part of a wider €2 billion funding round that values Mistral at $14 billion, marking a significant milestone for the Paris-based startup.
The Dutch chip-making equipment giant will also gain a board seat at Mistral, with Bank of America advising on the investment. The move is seen as a step towards reinforcing European technological sovereignty by reducing reliance on American and Chinese AI systems.
The partnership could help Mistral expand its generative AI tools and open-source platforms while enhancing ASML’s ability to integrate data analytics into its operations.
Industry analysts suggest the collaboration will unite two European technology leaders at a critical moment in the global race for AI dominance.
Founded by Timothée Lacroix, Guillaume Lample, and Arthur Mensch, Mistral has quickly become one of Europe’s most valuable AI startups.
The company, backed by investors including Microsoft, Databricks, and General Catalyst, develops open-source generative AI models that directly compete with those produced by OpenAI.
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Nigeria has pledged to become one of the top 50 AI-ready nations, according to presidential adviser Hadiza Usman. Speaking in Abuja at a colloquium on AI policy, she said the country needs strong leadership, investment, and partnerships to meet its goals.
She stressed that policies must address Nigeria’s unique challenges and not simply replicate foreign models. The government will offer collaboration opportunities with local institutions and international partners.
The Nigerian Deposit Insurance Commission reinforced its support, noting that technology should secure depositors without restricting innovators.
Private sector voices said AI could transform healthcare, agriculture, and public services if policies are designed with inclusion and trust in mind.
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