Why AI-Generated Code with Less Oversight Means More Dangerous Bugs—and Why Human Review Is Crucial
Introduction AI coding tools—like Copilot, GitHub’s Codex, and others—have enabled teams to write code faster than ever. Enterprise leaders from CIOs to CTOs are excited about the potential for increased throughput and efficiency. But recent research paints a more nuanced picture: AI-generated code increases dangerous security issues dramatically. This makes it more essential than ever […]
The Roles You Could Replace with AI – But Shouldn’t
The promise of AI in enterprise organisations is often framed around cost savings, productivity boosts, and “doing more with less.” The temptation is real: if an algorithm can complete a task faster and cheaper than a human, why keep the human? But here’s the hard truth: while many roles in an organisation could be replaced with AI […]
The Roles You Could Replace with AI—But Shouldn’t
AI has become the buzzword in boardrooms. Business leaders are told daily that artificial intelligence can cut costs, speed up processes, and give them a competitive edge. While it’s true that AI can automate many functions, there’s a growing risk that some organisations are reaching too quickly for replacements in roles that should never be […]
What Really Happens When You Upload a Contract to ChatGPT?
Generative AI tools like ChatGPT have become everyday assistants in business. From drafting emails to summarising long reports, they can save hours of work. Increasingly, however, business leaders are testing AI in riskier territory: uploading legal contracts to ask for plain-English explanations or even advice. At first glance, this seems harmless. Why not let an […]
When Users Upload Contracts to ChatGPT: Legal, Compliance, and Regulatory Risks Enterprises Must Address
The rise of generative AI has created a new reality in the workplace: people are quietly, and often without permission, pasting sensitive contracts into AI tools like ChatGPT to “make sense” of them. AI can explain clauses and answer questions far faster than a colleague. But unlike asking a lawyer, this raises serious issues around intellectual […]
When AI Goes Wrong: The $1.5 Billion Wake-Up Call
In early September 2025, AI company Anthropic agreed to a staggering $1.5 billion class-action settlement with authors who alleged their works were pirated to train Anthropic’s Claude chatbot. That works out to around $3,000 per book, for roughly 500,000 affected works . To put that in perspective: While Anthropic frames the settlement as a resolution to legacy issues and a commitment to […]
The Rising Tide of Financial Risk in AI: When Training Cuts Corners, Fines Cut Deep
1. A Billion-Dollar Reality Check—Anthropic’s $1.5B Settlement In September 2025, AI startup Anthropic stunned the industry by agreeing to pay $1.5 billion to settle a class-action copyright lawsuit filed by authors who accused the company of using pirated books to train its Claude language model . The authors alleged Anthropic downloaded hundreds of thousands of copyrighted books from illicit […]
When AI Moves Too Fast: How Strategic Oversight Could Have Prevented the Home Office’s Asylum AI Missteps
In the relentless drive to modernise public services and reduce operational backlogs, the UK Home Office’s decision to roll out an AI-driven Asylum Case Summarisation (ACS) tool might appear, at first glance, like a bold step forward. But with 9% of reviewed cases showing “serious errors” and nearly a quarter of caseworkers lacking confidence in […]
Data Drift by Design: How AI Can Erode Confidence Across the Workflow Chain
Introduction: When Trust in Data Becomes a Liability In today’s enterprise landscape, artificial intelligence is no longer a future proposition — it’s already embedded in analytics dashboards, automation systems, customer service platforms, and operational workflows. But as AI starts touching more of the data journey, a subtle yet dangerous phenomenon can creep in: data confidence drift. […]
AI-Assisted Workflows and the Hidden Trust Trap: Why Data Confidence Needs Clear Labelling
As more SMEs integrate artificial intelligence (AI) into their business operations, the promise of increased efficiency, automation, and insight can seem irresistible. From generating financial forecasts to auto-classifying support tickets, AI is being embedded deeper into workflows across industries. But beneath this excitement lies a subtle and often overlooked risk: AI-modified data can unintentionally carry forward […]
AI in the Data Chain: Hidden Adjustments, Overstated Confidence, and the Need for Transparent Labelling
As artificial intelligence becomes more deeply integrated into enterprise operations, it brings efficiency, scalability, and speed to traditionally manual processes. However, it also introduces a more subtle—and potentially dangerous—consequence: overconfidence in data that has been transformed or generated by AI. When AI is embedded into early stages of a workflow, its outputs are often accepted […]
The Personality Paradox: Does Giving AI a Human Touch Undermine Business Accuracy?
In the race to make artificial intelligence more accessible, engaging, and “human-like,” businesses and platforms have increasingly leaned into giving their AI tools a personality. From sassy customer service bots to witty assistants that remember your preferences and crack jokes, personality-driven AI is fast becoming the norm. The goal? A more relatable, enjoyable user experience that […]