December 2025

Generative AI’s experimental phase is concluding, making way for truly autonomous systems in 2026 that act rather than merely summarise. 2026 will lose the focus on model parameters and be about agency, energy efficiency, and the ability to navigate complex industrial environments. The next twelve months represent a departure from chatbots toward autonomous systems executing […]

BBVA is embedding AI into core banking workflows using ChatGPT Enterprise to overhaul risk and service in the sector. For the banking industry, the challenge of generative AI is rarely about adoption; it is about value extraction. BBVA has addressed this by integrating OpenAI’s platform directly into its operational backbone, a decision that will see

F. Scott Fitzgerald once observed that “in a real dark night of the soul, it is always three o’clock in the morning.” Microsoft’s latest Copilot usage analysis suggests this nocturnal tendency toward existential contemplation persists in the AI age—with religion and philosophy conversations rising through the rankings during early morning hours. The Microsoft AI (MAI) research team

Microsoft believes it has a fix for AI prompts being given, the response missing the mark, and the cycle repeating. This inefficiency is a drain on resources. The “trial-and-error loop can feel unpredictable and discouraging,” turning what should be a productivity booster into a time sink. Knowledge workers often spend more time managing the interaction

New adoption data from Perplexity reveals how AI agents are driving workflow efficiency gains by taking over complex enterprise tasks. For the past year, the technology sector has operated under the assumption that the next evolution of generative AI would advance beyond conversation into action. While Large Language Models (LLMs) serve as a reasoning engine,

Many companies are still working out how to use AI in a steady and practical way, but a small group is already pulling ahead. New research from NTT DATA outlines a playbook that shows how these “AI leaders” set themselves apart through strong plans, firm decisions, and a disciplined approach to building and using AI

Accenture and Anthropic are setting out to boost enterprise AI integration with a newly-expanded partnership. While 2024 was defined by corporate curiosity regarding Large Language Models (LLMs), the current mandate for business leaders is operationalising these tools to achieve a return on investment. The new Accenture Anthropic Business Group combines Anthropic’s model capabilities with Accenture’s

Adoption of generative AI has outpaced workforce capability, prompting OpenAI to target the skills gap with new certification standards. While it’s safe to say OpenAI’s tools have reached mass adoption, organisations struggle to convert this usage into reliable output. To address this, OpenAI has announced ‘AI Foundations,’ a structured initiative designed to standardise how employees

Artificial intelligence is transforming the way information is created, summarised, and delivered. For publishers, the shift is already visible. Search engines provide AI-generated overviews, users get answers without clicking, and content is scraped by large language models that train on decades of journalism. In this environment one question remains: How does a publisher survive when

For the past year, we’ve been told that artificial intelligence is revolutionising productivity—helping us write emails, generate code, and summarise documents. But what if the reality of how people actually use AI is completely different from what we’ve been led to believe? A data-driven study by OpenRouter has just pulled back the curtain on real-world AI usage by analysing over 100