When a human expert makes a recommendation, you can ask them why. They can explain their reasoning, show the evidence, and walk you through the logic. When most AI systems make a recommendation, the answer to “why?” is a matrix of billions of weighted numbers — technically accurate but practically useless for understanding and validating … Read more
The energy cost of AI inference is rarely discussed in business AI adoption conversations, but it is material and growing. Training large AI models makes headlines for its energy consumption, but the ongoing cost of inference — running the model to generate each response, at billions of queries per day across all users — is … Read more
Businesses currently run on stacks of specialised software subscriptions: a CRM, a project management tool, an email marketing platform, an accounting tool, a communication platform, a file storage service. Each does a specific set of things well. A growing question in technology strategy circles is whether AI-first tools will replace many of these single-purpose subscriptions … Read more
AI tools have moved from experimental to operational across most industries, yet many teams lack the foundational understanding needed to use them effectively, safely, and with appropriate judgement. AI literacy — the ability to understand what AI tools can and cannot do, how to use them productively, and when to apply human judgement rather than … Read more
The EU AI Act is the world’s first comprehensive AI regulation, and it came into force in 2024 with a phased implementation schedule. For small businesses using AI tools, the practical question is not whether the Act is a good idea — it is what it actually requires of you, when those requirements kick in, … Read more
The debate about AI and human creativity tends toward two unproductive extremes: breathless claims that AI will replace all creative work, and defensive assertions that AI could never match human creativity. The reality in 2026 is more nuanced and more useful than either position. AI is genuinely excellent at some creative tasks, genuinely inferior at … Read more
Generative AI and agentic AI are frequently used interchangeably in business media, which creates genuine confusion about what is actually being discussed. They are related but meaningfully different — understanding the distinction helps you make better decisions about which type of AI capability is relevant to a specific business problem and what implementation complexity you … Read more
For the first two years of the generative AI boom, bigger meant better. GPT-4 was celebrated because it was bigger than GPT-3. Bigger models on bigger datasets produced better benchmarks. The race was vertical — toward larger, more capable, more expensive models. In 2025 and 2026, the frontier shifted. Small Language Models (SLMs) — compact … Read more
Freelancers working in writing, design, translation, data entry, and basic coding have felt the impact of AI more acutely and more quickly than most employed workers. The question being asked across freelancer platforms and communities is not abstract: is the market for my skills contracting, and if so, what do I do about it? The … Read more
Answering the question of which jobs AI will automate requires more precision than the breathless media coverage provides. AI does not automate jobs — it automates specific tasks within jobs. Understanding which tasks are most automatable, and how those tasks distribute across different roles, gives a more useful picture of where AI’s impact will be … Read more