AI Agents: Ready for Your Business (If Your Infrastructure Isn't Rubbish)

Quick answer

AI Agents: Ready for Your Business (If Your Infrastructure Isn't Rubbish) explains what the change means for UK SMEs and how to turn it into a practical next step. The process is to identify the business decision, connect the data, then automate only the parts that improve speed or reliability.

Picture this. You've just read another headline about AI agents doing the work of entire departments. Your mate down the pub reckons his company's using "agentic AI" to handle all their customer service. And you're thinking, is this actually real, or is it another blockchain-shaped bubble?

It's real. But there's a catch, and it's the same catch as always.

What the research actually says

McKinsey just published research on reimagining tech infrastructure for agentic AI. One of their case studies found that up to 80% of service requests were automated, with 50% of agent capacity freed up for higher-value work. Customer satisfaction hit 4.8 out of 5.

That's not a future prediction. That's a thing that happened, in a real company, right now.

The shift is from single AI chatbots that answer FAQ pages to agentic AI, multiple AI agents that work together, make decisions, and actually complete tasks end-to-end. McKinsey's got their "Agents-at-Scale" suite. PwC built an Agent OS. KPMG's got their Workbench. The big consultancies are all in.

"The transformation resulted in up to 80 percent of requests being automated, 50 percent of service agent capacity redeployed to higher-value activities."

Here's the bit nobody tells you

None of that works if your underlying infrastructure is held together with Excel formulas and hope.

I've seen it dozens of times. A company buys the AI tool, plugs it in, and wonders why it gives rubbish answers. It's because the AI is pulling from the same messy data, broken processes, and disconnected systems that were causing problems before. You've just automated the chaos.

Mckinsey's research is clear: the companies seeing these results sorted their infrastructure first. Clean data, proper APIs, documented processes. The boring stuff that nobody wants to spend money on.

What to actually do

• Get your data house in order. AI agents are only as good as the information they can access. If your customer data lives in five spreadsheets and a SharePoint site nobody's looked at since 2023, fix that first.
• Map one process end-to-end. Don't try to AI-ify everything. Pick one high-volume, repetitive process. Document it properly. Then automate it.
• Think agents, not chatbots. A chatbot answers questions. An agent actually does the work, raises the order, updates the system, sends the confirmation. That's where the real value is.

The technology is genuinely ready. The question is whether your business is. And if the answer's "not quite," that's fine, but sort the foundations before you start building on top.