From the moment GPT-5 was unveiled, a realisation seems to have rippled across the tech world: perhaps we have been mistaking noise for signal. The latest flagship model didn’t deliver a radical leap; instead it brought a routing mechanism to dispatch tasks among existing models.
While generative systems can deliver speed and consistency, a sizable share of end users remains uneasy. Over half of consumers harbour doubts about relying on AI, especially when it handles sensitive or nuanced tasks. Many prefer human agents to resolve complex issues.
Behind the veneer of reasoning, most large language models are still drawing patterns from vast data sets, not thinking in the way humans do. They excel at mimicry, not genuine insight. In benchmark tests and real-world tasks alike, advanced models stumble. Agentic systems that perform well in simple steps falter once complexity increases.
The real winners will be those who embed AI pragmatically, where gains are predictable, error rates manageable, and integration into existing workflows seamless. Industries such as telecoms, where Cerillion operates, already offer examples of AI supplementing rather than supplanting.
Cerillion plc (LON:CER) is a leading provider of billing, charging and customer management systems with more than 20 years’ experience delivering its solutions across a broad range of industries including the telecommunications, finance, utilities and transportation sectors.
