Most manufacturers plan AI spending, but few know where to start
Eighty-two percent of manufacturing companies plan to increase spending on AI and automation. Only one in three feel confident about how to begin.
This gap between intent and execution has a name: the AI Strategy Gap. Organisations recognise they need to move, but struggle to identify which problems matter most, which type of AI to apply, and how to turn plans into real operational gains.
Four types of AI, four different jobs
The confusion often stems from treating AI as a single tool. It isn't. Different problems require different approaches.
- Automation removes repetitive steps, cuts administrative peaks, and streamlines manual processes.
- Machine Learning and prediction detect anomalies, identify demand signals, forecast lead times, and surface data-driven insights.
- Generative AI summarises information, explains concepts, translates content, and speeds up knowledge work.
- Intelligent agents take action, self-correct, and drive workflow decisions without human intervention at each step.
Real organisations across the UK are already applying these approaches to free up capacity, reduce delays, and build resilience in supply chains.
A workshop designed for executives, not technologists
HSO is running an AI + Intelligent Agents Workshop on 9 July aimed at closing this gap for manufacturing leaders. The session is deliberately non-technical-no laptops, no jargon, no data science background required.
Attendees work through interactive exercises to map their own operational challenges, spot where AI can deliver measurable returns, and build an actionable path forward.
For manufacturing executives tasked with AI strategy, understanding AI for Executives & Strategy and how it applies to AI for Operations has become essential to making the right investment decisions.
Your membership also unlocks:
