For the past year, the message to employees has been fairly consistent: embrace AI. Experiment. Find ways to work faster. Build your capability so you don’t get left behind. Now another message is arriving: be careful how much you use. A video about Accenture’s AI spending recently caught my attention. According to reporting on an internal announcement, the company has introduced a centrally funded allowance of US$29 per person per month for Claude, with additional usage char

There is a question missing from much of the conversation about artificial intelligence. We hear about productivity, efficiency and the opportunity for businesses to achieve more with fewer people. We hear that workers need to adapt, learn new skills and prepare for a changing world. But follow that thinking a little further. If businesses need fewer workers, and fewer people receive wages, who buys what those businesses produce? An automated business still needs customers. A

Some of the most useful contributions I have made at work have come from noticing something outside the immediate brief. A content problem that turns out to be a service problem. A technology decision that creates an accessibility barrier. A beautifully designed experience that falls apart because the process behind it cannot support what it promises. Recognising those connections has shaped how I work. It is also why I am increasingly interested in what the pace of AI means