For me the jury is out on the discussion about what synthetic data might be able to achieve in replicating human decisions and behaviour. I am worried by some of the overclaims and appalled by the number of people who reject the notions as being self-evidently wrong (without feeling the need to support their rejection with data). In this post, I want to explore one line of thinking relating to the broader debate, namely, what is the human brain doing and how might that help or hinder the creation of predictive models (AKA synthetic data).

Here is an example of using a simple agent to make your life slightly easier. I will show the example using Copilot, but you could just as easily use ChatGPT, Gemini, Claude etc. You can use the same Instructions that I use for the Copilot.

Every so often, a new term captures the imagination of the tech world. “Agent” is one such word. From boardrooms to blogs, organisations are talking about how agents will transform work. Industry surveys suggest this is more than hype. KPMG’s Q2 2025 AI Quarterly Pulse Survey reports that agents are moving beyond experiments: a third of organisations already use AI agents in production[1] and nearly nine in ten leaders expect agents to necessitate fundamental organisational change[1]. Gartner goes further, predicting that by 2028, one-third of enterprise software applications will include agentic AI (up from less than 1% in 2024) and at least 15% of business decisions will be made autonomously via agents[2]. Deloitte anticipates that 25% of companies using generative AI will launch agentic pilots in 2025, rising to 50% by 2027[3]. When market leaders and consultancies align on the direction of travel, it is worth paying attention.