For many businesses, large language models have been the first practical encounter with artificial intelligence, helping staff draft content, summarise documents and save time on routine tasks. That alone has been enough to shift AI from abstract debate to everyday business tool.

But large language models are only the beginning. The next stage is often described as agentic AI, systems that can not only produce responses, but also work towards a goal, retrieve information, use software tools and carry out a sequence of actions with less human prompting. IBM describes agentic AI as a more autonomous, goal-driven and adaptable form of AI, built around systems that can reason, act and use tools in pursuit of a task.

The attraction for business is clear. IBM highlights several potential benefits: agentic systems can operate with greater autonomy, take a more proactive role by interacting with tools and data sources, specialise in particular tasks, adapt through feedback, and offer a more intuitive natural-language interface for users. In business terms, that suggests AI moving beyond content generation towards workflow support, coordination and execution.

Our own evidence suggests members are open to that direction of travel. The Chamber’s 2026 Skills Survey found that 88% of respondents were already using or exploring AI, while every respondent said they would invest more, or possibly more, if practical local support was available. At the same time, firms told us that adoption is spreading faster than capability, with lack of in-house expertise, limited time and unclear practical use cases still acting as constraints.

That is why the conversation now needs to mature. The question is no longer whether AI is relevant, but how it should be adopted. For business, that means approaching AI in a way that is ethical, responsible and properly governed, with human oversight and sensible handling of sensitive information built in from the outset. If you have an idea for your business and want to check if AI is the right tool to use, check out AICC’s free Responsible Hub Reasonable Test. AICC’s free Responsible Hub Reasonable Test.

For members who want to explore the concept further, IBM’s explainer on agentic AI  is a useful starting point.

Takeaway

Large language models opened the door to mainstream AI adoption; agentic AI points to what may come next, making responsible deployment just as important as capability itself.