Where AI Is (and Isn't) Deployed Today

AI is genuinely transforming some industries while barely touching others. Customer service, content creation, software development and data analysis have seen rapid adoption. Healthcare is using AI for imaging and drug discovery but clinical deployment remains cautious and heavily regulated. Financial services use AI extensively for fraud detection, trading and risk assessment. Manufacturing and logistics use it for quality control and supply chain optimisation. Legal, education and government are experimenting but face significant barriers around accuracy, accountability and regulation. Where AI isn't deployed is equally telling: high-stakes decisions with limited data, situations requiring physical dexterity in unstructured environments, tasks demanding genuine emotional understanding, and domains where errors are unacceptable and hard to detect. Many organisations have also discovered a gap between proof-of-concept and production deployment - getting AI to work impressively in a demo is much easier than getting it to work reliably at scale in a real business process. The most successful deployments tend to be those where AI augments human work rather than attempting to replace it entirely.